academic.oup.com Open in urlscan Pro
52.224.90.245  Public Scan

Submitted URL: https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehz455/5556353
Effective URL: https://academic.oup.com/eurheartj/article/41/1/111/5556353
Submission: On September 12 via manual from US — Scanned from DE

Form analysis 1 forms found in the DOM

GET /Citation/Download

<form action="/Citation/Download" method="get" id="citationModal">
  <input type="hidden" name="resourceId" value="5556353">
  <input type="hidden" name="resourceType" value="3">
  <label for="selectFormat" class="hide js-citation-format-label">Select Format</label>
  <select required="" name="citationFormat" class="citation-download-format js-citation-format" id="selectFormat">
    <option selected="" disabled="">Select format</option>
    <option value="0">.ris (Mendeley, Papers, Zotero)</option>
    <option value="1">.enw (EndNote)</option>
    <option value="2">.bibtex (BibTex)</option>
    <option value="3">.txt (Medlars, RefWorks)</option>
  </select>
  <button class="btn citation-download-link disabled" type="submit">Download citation</button>
</form>

Text Content

We use cookies to enhance your experience on our website. By clicking 'continue'
or by continuing to use our website, you are agreeing to our use of cookies. You
can change your cookie settings at any time.
 * Continue
 * Find out more



We use cookies to enhance your experience on our website.By continuing to use
our website, you are agreeing to our use of cookies. You can change your cookie
settings at any time. Find out more Skip to Main Content
Advertisement
Journals
Books
 * Search Menu
 * 
 * 
 * Menu
 * 
 * 


Navbar Search Filter European Heart JournalThis issueESC Publications
Cardiovascular MedicineBooksJournalsOxford Academic Mobile Microsite Search Term
Search
 * Sign In
   * 

 * Issues
 * More Content
   * Advance Articles
   * Braunwald's Corner
   * Cardio Image Bank
   * CardioPulse
   * Editor's Choice
   * EHJ Dialogues
   * ESC Journals App
   * European Heart Journal Supplements
   * Guidelines
   * In the News
   * Podcasts
   * Weekly Journal Scan
   * Year in Cardiovascular Medicine 2021
 * Submit
   * Author Guidelines
   * Submission Site
   * Open Access Options
   * Author Resources
   * Self-Archiving Policy
   * Read & Publish
 * Purchase
 * Advertise
   * Advertising and Corporate Services
   * Advertising
   * Reprints and ePrints
   * Sponsored Supplements
   * Journals Career Network
 * About
   * About European Heart Journal
   * Editorial Board
   * About the European Society of Cardiology
   * ESC Membership
   * Alerts
   * Developing Countries Initiative
   * Dispatch Dates
   * Terms and Conditions
 * Journals on Oxford Academic
 * Books on Oxford Academic

ESC Publications

 * Issues
 * More Content
   * Advance Articles
   * Braunwald's Corner
   * Cardio Image Bank
   * CardioPulse
   * Editor's Choice
   * EHJ Dialogues
   * ESC Journals App
   * European Heart Journal Supplements
   * Guidelines
   * In the News
   * Podcasts
   * Weekly Journal Scan
   * Year in Cardiovascular Medicine 2021
 * Submit
   * Author Guidelines
   * Submission Site
   * Open Access Options
   * Author Resources
   * Self-Archiving Policy
   * Read & Publish
 * Purchase
 * Advertise
   * Advertising and Corporate Services
   * Advertising
   * Reprints and ePrints
   * Sponsored Supplements
   * Journals Career Network
 * About
   * About European Heart Journal
   * Editorial Board
   * About the European Society of Cardiology
   * ESC Membership
   * Alerts
   * Developing Countries Initiative
   * Dispatch Dates
   * Terms and Conditions

Close
Navbar Search Filter European Heart JournalThis issueESC Publications
Cardiovascular MedicineBooksJournalsOxford Academic Microsite Search Term Search
Advanced Search
Search Menu

Article Navigation
Close mobile search navigation
Article Navigation
Volume 41
Issue 1
1 January 2020


ARTICLE CONTENTS

 * Table of contents
 * Tables of Recommendations
 * List of tables
 * List of figures
 * List of boxes
 * Abbreviations and acronyms
 * 1 Preamble
 * 2 Introduction
 * 3 What is cardiovascular disease prevention?
 * 4 Total cardiovascular risk
 * 5 Lipids and lipoproteins
 * 6 Treatment targets and goals
 * 7 Lifestyle modifications to improve the plasma lipid profile
 * 8 Drugs for treatment of dyslipidaemias
 * 9 Management of dyslipidaemias in different clinical settings
 * 10 Inflammation
 * 11 Monitoring of lipids and enzymes in patients on lipid-lowering therapy
 * 12 Cost-effectiveness of cardiovascular disease prevention by lipid
   modification
 * 13 Strategies to encourage adoption of healthy lifestyle changes and
   adherence to lipid-modifying therapies
 * 14 Key messages
 * 15 Gaps in the evidence
 * 16 ‘What to do’ and ‘what not to do’ messages from the Guidelines
 * 17 Supplementary data
 * 18 Appendix
 * 19 References
 * Author notes
 * Supplementary data

 * < Previous
 * Next >


Article Navigation
Article Navigation
Journal Article


2019 ESC/EAS GUIDELINES FOR THE MANAGEMENT OF DYSLIPIDAEMIAS: LIPID MODIFICATION
TO REDUCE CARDIOVASCULAR RISK: THE TASK FORCE FOR THE MANAGEMENT OF
DYSLIPIDAEMIAS OF THE EUROPEAN SOCIETY OF CARDIOLOGY (ESC) AND EUROPEAN
ATHEROSCLEROSIS SOCIETY (EAS)

François Mach,
François Mach
Chairperson Switzerland
Corresponding authors: François Mach, Cardiology Department, Geneva University
Hospital, 4 Gabrielle-Perret-Gentil, 1211 Geneva, Switzerland. Tel: +41 223 727
192, Fax: +41 223 727 229, Email: francois.mach@hcuge.ch. Colin Baigent,
Nuffield Department of Population Health, University of Oxford, Richard Doll
Building, Roosevelt Drive, Oxford OX3 7LF, United Kingdom. Tel: +44 1865 743
741, Fax: +44 1865 743 985, Email: colin.baigent@ndph.ox.ac.uk. Alberico L.
Catapano, Department of Pharmacological and Biomolecular Sciences, University of
Milan, Via Balzaretti, 9, 20133 Milan, and Multimedica IRCCS, Milan, Italy. Tel:
+39 02 5031 8401, Fax: +39 02 5031 8386, Email: alberico.catapano@unimi.it.
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Colin Baigent,
Colin Baigent
Chairperson United Kingdom
Corresponding authors: François Mach, Cardiology Department, Geneva University
Hospital, 4 Gabrielle-Perret-Gentil, 1211 Geneva, Switzerland. Tel: +41 223 727
192, Fax: +41 223 727 229, Email: francois.mach@hcuge.ch. Colin Baigent,
Nuffield Department of Population Health, University of Oxford, Richard Doll
Building, Roosevelt Drive, Oxford OX3 7LF, United Kingdom. Tel: +44 1865 743
741, Fax: +44 1865 743 985, Email: colin.baigent@ndph.ox.ac.uk. Alberico L.
Catapano, Department of Pharmacological and Biomolecular Sciences, University of
Milan, Via Balzaretti, 9, 20133 Milan, and Multimedica IRCCS, Milan, Italy. Tel:
+39 02 5031 8401, Fax: +39 02 5031 8386, Email: alberico.catapano@unimi.it.
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Alberico L Catapano,
Alberico L Catapano
Chairperson Italy
Corresponding authors: François Mach, Cardiology Department, Geneva University
Hospital, 4 Gabrielle-Perret-Gentil, 1211 Geneva, Switzerland. Tel: +41 223 727
192, Fax: +41 223 727 229, Email: francois.mach@hcuge.ch. Colin Baigent,
Nuffield Department of Population Health, University of Oxford, Richard Doll
Building, Roosevelt Drive, Oxford OX3 7LF, United Kingdom. Tel: +44 1865 743
741, Fax: +44 1865 743 985, Email: colin.baigent@ndph.ox.ac.uk. Alberico L.
Catapano, Department of Pharmacological and Biomolecular Sciences, University of
Milan, Via Balzaretti, 9, 20133 Milan, and Multimedica IRCCS, Milan, Italy. Tel:
+39 02 5031 8401, Fax: +39 02 5031 8386, Email: alberico.catapano@unimi.it.
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Konstantinos C Koskinas,
Konstantinos C Koskinas
Switzerland
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Manuela Casula,
Manuela Casula
Italy
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Lina Badimon,
Lina Badimon
Spain
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
M John Chapman,
M John Chapman
France
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Guy G De Backer,
Guy G De Backer
Belgium
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Victoria Delgado,
Victoria Delgado
Netherlands
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Brian A Ference,
Brian A Ference
United Kingdom
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
... Show more
Ian M Graham,
Ian M Graham
Ireland
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Alison Halliday,
Alison Halliday
United Kingdom
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Ulf Landmesser,
Ulf Landmesser
Germany
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Borislava Mihaylova,
Borislava Mihaylova
United Kingdom
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Terje R Pedersen,
Terje R Pedersen
Norway
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Gabriele Riccardi,
Gabriele Riccardi
Italy
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Dimitrios J Richter,
Dimitrios J Richter
Greece
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Marc S Sabatine,
Marc S Sabatine
United States of America
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Marja-Riitta Taskinen,
Marja-Riitta Taskinen
Finland
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Lale Tokgozoglu,
Lale Tokgozoglu
Turkey
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
Olov Wiklund,
Olov Wiklund
Sweden
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar
ESC Scientific Document Group
ESC Scientific Document Group
Search for other works by this author on:
Oxford Academic
PubMed
Google Scholar

François Mach, Colin Baigent and Alberico L. Catapano chairpersons contributed
equally to the document.

Alberico L. Catapano, Manuela Casula, Gabriele Riccardi, Marja-Riitta Taskinen,
Lale Tokgozoglu, Olov Wiklund, Alberto Corsini, Meral Kayikcioglu, Philippe
Moulin, Xavier Pintó, Kausik K. Ray, Željko Reiner, Erik Stroes, Alexandros D.
Tselepis, Margus Viigimaa and Michal Vrablik: representing the EAS.

Author Notes
European Heart Journal, Volume 41, Issue 1, 1 January 2020, Pages 111–188,
https://doi.org/10.1093/eurheartj/ehz455
Published:
31 August 2019
A correction has been published: European Heart Journal, Volume 41, Issue 44, 21
November 2020, Page 4255, https://doi.org/10.1093/eurheartj/ehz826
 * PDF
 * Split View
 * Views
     
   * Article contents
   * Figures & tables
   * Supplementary Data
 * Cite
   
   
   CITE
   
   François Mach, Colin Baigent, Alberico L Catapano, Konstantinos C Koskinas,
   Manuela Casula, Lina Badimon, M John Chapman, Guy G De Backer, Victoria
   Delgado, Brian A Ference, Ian M Graham, Alison Halliday, Ulf Landmesser,
   Borislava Mihaylova, Terje R Pedersen, Gabriele Riccardi, Dimitrios J
   Richter, Marc S Sabatine, Marja-Riitta Taskinen, Lale Tokgozoglu, Olov
   Wiklund, ESC Scientific Document Group, 2019 ESC/EAS Guidelines for the
   management of dyslipidaemias: lipid modification to reduce cardiovascular
   risk: The Task Force for the management of dyslipidaemias of the European
   Society of Cardiology (ESC) and European Atherosclerosis Society (EAS),
   European Heart Journal, Volume 41, Issue 1, 1 January 2020, Pages 111–188,
   https://doi.org/10.1093/eurheartj/ehz455
   
   Select Format Select format .ris (Mendeley, Papers, Zotero) .enw (EndNote)
   .bibtex (BibTex) .txt (Medlars, RefWorks) Download citation
   Close
 * Permissions Icon Permissions
 * Share
     
   * Email
   * Twitter
   * Facebook
   * More
     

Navbar Search Filter European Heart JournalThis issueESC Publications
Cardiovascular MedicineBooksJournalsOxford Academic Mobile Microsite Search Term
Search
 * Sign In
   * 


Close
Navbar Search Filter European Heart JournalThis issueESC Publications
Cardiovascular MedicineBooksJournalsOxford Academic Microsite Search Term Search
Advanced Search
Search Menu
Guidelines, dyslipidaemias, cholesterol, triglycerides, low-density
lipoproteins, high-density lipoproteins, apolipoprotein B, lipoprotein(a),
lipoprotein remnants, total cardiovascular risk, treatment (lifestyle),
treatment (drugs), treatment (adherence), very low-density lipoproteins,
familial hypercholesterolaemia
Topic:
 * atherosclerosis
 * dyslipidemias
 * ldl cholesterol lipoproteins
 * high density lipoprotein cholesterol
 * triglycerides
 * statins
 * lipoproteins
 * cardiovascular diseases
 * heart disease risk factors
 * cholesterol
 * apolipoproteins b
 * plasma
 * guidelines
 * lipids
 * mortality

Issue Section:
ESC/EAS GUIDELINES

For the Supplementary Data which include background information and detailed
discussion of the data that have provided the basis for the Guidelines see
https://academic.oup.com/eurheartj/article-lookup/doi/10.1093/eurheartj/ehz455#supplementary-data


TABLE OF CONTENTS



 * Abbreviations and acronyms  114

 * 1 Preamble  116

 * 2 Introduction  118

 *  2.1 What is new in the 2019 Guidelines?  118

 * 3 What is cardiovascular disease prevention?  118

 *  3.1 Definition and rationale  118

 *  3.2 Development of the Joint Task Force Guidelines for the management of
   dyslipidaemias  118

 * 4 Total cardiovascular risk  118

 *  4.1 Total cardiovascular risk estimation  118

 *   4.1.1 Rationale for assessing total cardiovascular disease risk  121

 *   4.1.2 How to use the risk estimation charts  124

 *  4.2 Risk levels  125

 *   4.2.1 Role of non-invasive cardiovascular imaging techniques in the
   assessment of total cardiovascular disease risk  126

 *   4.2.2 Risk-based intervention strategies  127

 * 5 Lipids and lipoproteins  127

 *  5.1 Biological role of lipids and lipoproteins  127

 *  5.2 Role of lipids and lipoproteins in the pathophysiology of
   atherosclerosis  127

 *  5.3 Evidence for the causal effects of lipids and lipoproteins on the risk
   of atherosclerotic cardiovascular disease  128

 *   5.3.1 Low-density lipoprotein cholesterol and risk of atherosclerosis  128

 *   5.3.2 Triglyceride-rich lipoproteins and risk of atherosclerosis  128

 *   5.3.3 High-density lipoprotein cholesterol and risk of atherosclerosis  129

 *   5.3.4 Lipoprotein(a) and risk of atherosclerosis  129

 *  5.4 Laboratory measurement of lipids and lipoproteins  129

 *   5.4.1 Lipoprotein measurement  129

 *   5.4.2 Lipid measurements  20

 *   5.4.3 Fasting or non-fasting?  130

 *  5.5 Recommendations for measuring lipids and lipoproteins to estimate risk
   of atherosclerotic cardiovascular disease  130

 * 6 Treatment targets and goals  131

 * 7 Lifestyle modifications to improve the plasma lipid profile  132

 *  7.1 Influence of lifestyle on total cholesterol and low-density lipoprotein
   cholesterol levels  134

 *  7.2 Influence of lifestyle on triglyceride levels  134

 *  7.3 Influence of lifestyle on high-density lipoprotein cholesterol
   levels  135

 *  7.4 Lifestyle recommendations to improve the plasma lipid profile  135

 *   7.4.1 Body weight and physical activity  135

 *   7.4.2 Dietary fat  135

 *   7.4.3 Dietary carbohydrate and fibre  136

 *   7.4.4 Alcohol  136

 *   7.4.5 Smoking  136

 *  7.5 Dietary supplements and functional foods for the treatment of
   dyslipidaemias  136

 *   7.5.1 Phytosterols  136

 *   7.5.2 Monacolin and red yeast rice  136

 *   7.5.3 Dietary fibre  137

 *   7.5.4 Soy  137

 *   7.5.5 Policosanol and berberine  27

 *   7.5.6 n-3 unsaturated fatty acids  137

 * 8 Drugs for treatment of dyslipidaemias  137

 *  8.1 Statins  137

 *   8.1.1 Mechanism of action  137

 *   8.1.2 Effects on lipids  137

 *    8.1.2.1 Low-density lipoprotein cholesterol  137

 *    8.1.2.2 Triglycerides  137

 *    8.1.2.3 High-density lipoprotein cholesterol  137

 *    8.1.2.4 Lipoprotein(a)  137

 *   8.1.3 Other effects of statins  138

 *    8.1.3.1 Effect on cardiovascular morbidity and mortality  138

 *   8.1.4 Adverse effects and interactions of statins  138

 *    8.1.4.1 Adverse effects on muscle  138

 *    8.1.4.2 Adverse effects on the liver  139

 *    8.1.4.3 Increased risk of new-onset diabetes mellitus  139

 *    8.1.4.4 Increased risk of haemorrhagic stroke  139

 *    8.1.4.5 Adverse effects on kidney function  139

 *    8.1.4.6 Interactions  139

 *  8.2 Cholesterol absorption inhibitors  140

 *   8.2.1 Mechanism of action  140

 *   8.2.2 Effects on lipids  140

 *   8.2.3 Effect on cardiovascular morbidity and mortality  140

 *   8.2.4 Adverse effects and interactions  140

 *  8.3 Bile acid sequestrants  140

 *   8.3.1 Mechanism of action  140

 *   8.3.2 Effects on lipids  140

 *   8.3.3 Effect on cardiovascular morbidity and mortality  140

 *   8.3.4 Adverse effects and interactions  141

 *  8.4 Proprotein convertase subtilisin/kexin type 9 inhibitors  141

 *   8.4.1 Mechanism of action  141

 *   8.4.2 Effects on lipids  141

 *    8.4.2.1 Low-density lipoprotein cholesterol  141

 *    8.4.2.2 Triglycerides and high-density lipoprotein cholesterol  141

 *    8.4.2.3 Lipoprotein(a)  141

 *   8.4.3 Effect on cardiovascular morbidity and mortality  141

 *   8.4.4 Adverse effects and interactions  142

 *  8.5 Lomitapide  142

 *  8.6 Mipomersen  142

 *  8.7 Fibrates  142

 *   8.7.1 Mechanism of action  142

 *   8.7.2 Effects on lipids  142

 *   8.7.3 Effect on cardiovascular morbidity and mortality  143

 *   8.7.4 Adverse effects and interactions  143

 *  8.8 n-3 fatty acids  143

 *   8.8.1 Mechanism of action  143

 *   8.8.2 Effects on lipids  143

 *   8.8.3 Effect on cardiovascular morbidity and mortality  143

 *   8.8.4 Safety and interactions  144

 *  8.9 Nicotinic acid  144

 *  8.10 Cholesteryl ester transfer protein inhibitors  144

 *  8.11 Future perspectives  144

 *   8.11.1 New approaches to reduce low-density lipoprotein cholesterol  144

 *   8.11.2 New approaches to reduce triglyceride-rich lipoproteins and their
   remnants  144

 *   8.11.3 New approaches to increase high-density lipoprotein cholesterol  145

 *   8.11.4 New approaches to reduce lipoprotein(a) levels  145

 *  8.12 Strategies to control plasma cholesterol  145

 *  8.13 Strategies to control plasma triglycerides  145

 * 9 Management of dyslipidaemias in different clinical settings  148

 *  9.1 Familial dyslipidaemias  148

 *   9.1.1 Familial combined hyperlipidaemia  148

 *   9.1.2 Familial hypercholesterolaemia  148

 *    9.1.2.1 Heterozygous familial hypercholesterolaemia  148

 *    9.1.2.2 Homozygous familial hypercholesterolaemia  151

 *    9.1.2.3 Familial hypercholesterolaemia in children  151

 *   9.1.3 Familial dysbetalipoproteinaemia  151

 *   9.1.4 Genetic causes of hypertriglyceridaemia  151

 *    9.1.4.1 Action to prevent acute pancreatitis in severe
   hypertriglyceridaemia  151

 *   9.1.5 Other genetic disorders of lipoprotein metabolism  152

 *  9.2 Women  152

 *   9.2.1 Effects of statins in primary and secondary prevention  152

 *   9.2.2 Non-statin lipid-lowering drugs  152

 *   9.2.3 Hormone therapy  152

 *  9.3 Older people  152

 *   9.3.1 Effects of statins in primary and secondary prevention  153

 *   9.3.2 Adverse effects, interactions, and adherence  153

 *  9.4 Diabetes and metabolic syndrome  153

 *   9.4.1 Specific features of dyslipidaemia in insulin resistance and type 2
   diabetes  153

 *   9.4.2 Evidence for lipid-lowering therapy  154

 *    9.4.2.1 Low-density lipoprotein cholesterol  154

 *    9.4.2.1 Triglycerides and high-density lipoprotein cholesterol  154

 *   9.4.3 Type 1 diabetes  155

 *   9.4.4 Management of dyslipidaemia for pregnant women with diabetes  155

 *  9.5 Patients with acute coronary syndromes and patients undergoing
   percutaneous coronary intervention  156

 *   9.5.1 Lipid-lowering therapy in patients with acute coronary syndromes  156

 *    9.5.1.1 Statins  156

 *    9.5.1.2 Ezetimibe  156

 *    9.5.1.3 Proprotein convertase subtilisin/kexin type 9 inhibitors  156

 *    9.5.1.4 n-3 polyunsaturated fatty acids  157

 *    9.5.1.5 Cholesteryl ester transfer protein inhibitors  157

 *   9.5.2 Lipid-lowering therapy in patients undergoing percutaneous coronary
   intervention  157

 *  9.6 Stroke  158

 *  9.7 Heart failure and valvular diseases  158

 *   9.7.1 Prevention of incident heart failure in coronary artery disease
   patients  158

 *   9.7.2 Chronic heart failure  158

 *   9.7.3 Valvular heart diseases  158

 *  9.8 Chronic kidney disease  159

 *   9.8.1 Lipoprotein profile in chronic kidney disease  159

 *   9.8.2 Evidence for risk reduction through statin-based therapy in patients
   with chronic kidney disease  159

 *   9.8.3 Safety of lipid management in patients with chronic kidney
   disease  159

 *  9.9 Transplantation  160

 *  9.10 Peripheral arterial disease  160

 *   9.10.1 Lower extremity arterial disease  160

 *   9.10.2 Carotid artery disease  161

 *   9.10.3 Retinal vascular disease  161

 *   9.10.4 Secondary prevention in patients with abdominal aortic aneurysm  161

 *   9.10.5 Renovascular atherosclerosis  161

 *  9.11 Other special populations at risk of atherosclerotic cardiovascular
   disease  161

 * 10 Inflammation  161

 * 11 Monitoring of lipids and enzymes in patients on lipid-lowering
   therapy  162

 * 12 Cost-effectiveness of cardiovascular disease prevention by lipid
   modification  162

 * 13 Strategies to encourage adoption of healthy lifestyle changes and
   adherence to lipid-modifying therapies  166

 * 14 Key messages  166

 * 15 Gaps in evidence  167

 * 16 Evidence-based ‘to do’ and ‘not to do’ messages from the Guidelines  168

 * 17 Supplementary data   170

 * 18 Appendix  170

 * 19 References  171




TABLES OF RECOMMENDATIONS



 * Recommendations for cardiovascular imaging for risk assessment of
   atherosclerotic cardiovascular disease  127

 * Recommendations for cardiovascular disease risk estimation  127

 * Recommendations for lipid analyses for cardiovascular disease risk
   estimation  131

 * Recommendations for treatment goals for low-density lipoprotein
   cholesterol  132

 * Recommendations for pharmacological low-density lipoprotein cholesterol
   lowering  145

 * Recommendations for drug treatment of patients with
   hypertriglyceridaemia  148

 * Recommendations for the detection and treatment of patients with heterozygous
   familial hypercholesterolaemia  150

 * Recommendations for the treatment of dyslipidaemias in older people (aged >65
   years)  153

 * Recommendations for the treatment of dyslipidaemias in diabetes mellitus  155

 * Recommendations for lipid-lowering therapy in very- high-risk patients with
   acute coronary syndromes  157

 * Recommendations for lipid-lowering therapy in very-high-risk patients
   undergoing percutaneous coronary intervention  157

 * Recommendations for lipid-lowering therapy for prevention of atherosclerotic
   cardiovascular disease events in patients with prior ischaemic stroke  158

 * Recommendations for the treatment of dyslipidaemias in chronic heart failure
   or valvular heart diseases  159

 * Recommendations for lipid management in patients with moderate to severe
   (Kidney Disease Outcomes Quality Initiative stages 3–5) chronic kidney
   disease  159

 * Recommendations for low-density lipoprotein lowering in solid organ
   transplant patients  160

 * Recommendations for lipid-lowering drugs in patients with peripheral arterial
   disease (including carotid artery disease)  161




LIST OF TABLES



 * Table 1 Classes of recommendations  117

 * Table 2 Levels of evidence  117

 * Table 3 New recommendations, and new and revised concepts  119

 * Table 4 Cardiovascular risk categories  125

 * Table 5 Intervention strategies as a function of total cardiovascular risk
   and untreated low-density lipoprotein cholesterol levels  126

 * Table 6 Physical and chemical characteristics of human plasma
   lipoproteins  128

 * Table 7 Treatment targets and goals for cardiovascular disease
   prevention  133

 * Table 8 Impact of specific lifestyle changes on lipid levels  134

 * Table 9 Food choices to lower low-density lipoprotein cholesterol and improve
   the overall lipoprotein profile  135

 * Table 10 Drugs potentially interacting with statins metabolized by cytochrome
   P450 3A4 leading to increased risk of myopathy and rhabdomyolysis  139

 * Table 11 Genetic disorders of lipoprotein metabolism  149

 * Table 12 Dutch Lipid Clinic Network diagnostic criteria for familial
   hypercholesterolaemia  149

 * Table 13 Summary of recommendations for monitoring lipids and enzymes in
   patients, before and on lipid-lowering therapy  163




LIST OF FIGURES



 * Figure 1 Systematic Coronary Risk Estimation chart for European populations
   at high cardiovascular disease risk  122

 * Figure 2 Systematic Coronary Risk Estimation chart for European populations
   at low cardiovascular disease risk  123

 * Figure 3 Expected clinical benefit of low-density lipoprotein
   cholesterol-lowering therapies  146

 * Figure 4 Treatment goals and algorithm for low-density lipoprotein
   cholesterol-lowering according to cardiovascular disease risk  147

 * Figure 5 Health impact pyramid  164

 * Figure 6 Absolute reductions in major vascular events with statin
   therapy  165




LIST OF BOXES



 * Box 1 How to use the risk estimation charts  124

 * Box 2 Risk estimation charts for different countries  124

 * Box 3 Qualifiers  124

 * Box 4 Factors modifying Systematic Coronary Risk Estimation risks  124

 * Box 5 Risk estimation: key messages  125

 * Box 6 Management of dyslipidaemia in women  152

 * Box 7 Summary of dyslipidaemia in metabolic syndrome and type 2 diabetes
   mellitus  154

 * Box 8 Key messages  165

 * Box 9 Gaps in the evidence  165

 * Box 10 Methods for enhancing adherence to lifestyle changes  166




ABBREVIATIONS AND ACRONYMS



   Abbreviations and acronyms
    
 * ABI
   
   Ankle–brachial index

    
 * ACCELERATE
   
   Assessment of Clinical Effects of Cholesteryl Ester Transfer Protein
   Inhibition with Evacetrapib in Patients at a High-Risk for Vascular Outcomes

    
 * ACCORD
   
   Action to Control Cardiovascular Risk in Diabetes

    
 * ACS
   
   Acute coronary syndrome

    
 * ALT
   
   Alanine aminotransferase

    
 * ANGPTL3
   
   Angiopoietin-like protein 3

    
 * Apo
   
   Apolipoprotein

    
 * ART
   
   Antiretroviral treatment

    
 * ASCEND
   
   A Study of Cardiovascular Events iN Diabetes

    
 * ASCOT-LLA
   
   Anglo-Scandinavian Cardiac Outcomes Trial – Lipid-Lowering Arm

    
 * ASCVD
   
   Atherosclerotic cardiovascular disease

    
 * ASSIGN
   
   CV risk estimation model from the Scottish Intercollegiate Guidelines Network

    
 * AURORA
   
   A study to evaluate the Use of Rosuvastatin in subjects On Regular
   haemodialysis: an Assessment of survival and cardiovascular events

    
 * b.i.d.
   
   Twice a day (bis in die)

    
 * BIOSTAT-CHF
   
   BIOlogy Study to TAilored Treatment in Chronic Heart Failure

    
 * BIP
   
   Bezafibrate Infarction Prevention

    
 * BMI
   
   Body mass index

    
 * BP
   
   Blood pressure

    
 * CABG
   
   Coronary artery bypass graft surgery

    
 * CAC
   
   Coronary artery calcium

    
 * CAD
   
   Coronary artery disease

    
 * CANTOS
   
   Canakinumab Antiinflammatory Thrombosis Outcome Study

    
 * CETP
   
   Cholesteryl ester transfer protein

    
 * CHD
   
   Coronary heart disease

    
 * CI
   
   Confidence interval

    
 * CIID
   
   Chronic immune-mediated inflammatory diseases

    
 * CIRT
   
   Cardiovascular Inflammation Reduction Trial

    
 * CK
   
   Creatine kinase

    
 * CKD
   
   Chronic kidney disease

    
 * COM-B
   
   Capability, Opportunity and Motivation

    
 * CORONA
   
   Controlled Rosuvastatin Multinational Trial in Heart Failure

    
 * CPG
   
   Committee for Practice Guidelines

    
 * CT
   
   Computed tomography

    
 * CTT
   
   Cholesterol Treatment Trialists

    
 * CV
   
   Cardiovascular

    
 * CVD
   
   Cardiovascular disease

    
 * CYP
   
   Cytochrome P450

    
 * 4D
   
   Die Deutsche Diabetes Dialyse Studie

    
 * dal-OUTCOMES
   
   Effects of Dalcetrapib in Patients with a Recent Acute Coronary Syndrome

    
 * DASH
   
   Dietary Approaches to Stop Hypertension

    
 * DGAT-2
   
   Diacylglycerol acyltransferase-2

    
 * DHA
   
   Docosahexaenoic acid

    
 * DM
   
   Diabetes mellitus

    
 * EAPC
   
   European Association of Preventive Cardiology

    
 * EAS
   
   European Atherosclerosis Society

    
 * EBBINGHAUS
   
   Evaluating PCSK9 Binding Antibody Influence on Cognitive Health in High
   Cardiovascular Risk Subjects

    
 * eGFR
   
   Estimated glomerular filtration rate

    
 * EMA
   
   European Medicines Agency

    
 * EPA
   
   Eicosapentaenoic acid

    
 * ESC
   
   European Society of Cardiology

    
 * EVOLVE
   
   EpanoVa fOr Lowering Very high triglyceridEs

    
 * EVOPACS
   
   EVOlocumab for early reduction of LDL-cholesterol levels in patients with
   Acute Coronary Syndromes

    
 * FCH
   
   Familial combined hyperlipidaemia

    
 * FCS
   
   Familial chylomicronaemia syndrome

    
 * FDA
   
   US Food and Drug Administration

    
 * FH
   
   Familial hypercholesterolaemia

    
 * FIELD
   
   Fenofibrate Intervention and Event Lowering in Diabetes

    
 * FOCUS
   
   Fixed-Dose Combination Drug for Secondary Cardiovascular Prevention

    
 * FOURIER
   
   Further Cardiovascular Outcomes Research with PCSK9 Inhibition in Subjects
   with Elevated Risk

    
 * GFR
   
   Glomerular filtration rate

    
 * GI
   
   Gastrointestinal

    
 * GISSI
   
   Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico

    
 * HbA1c
   
   Glycated haemoglobin

    
 * HeFH
   
   Heterozygous familial hypercholesterolaemia

    
 * HDL
   
   High-density lipoprotein

    
 * HDL-C
   
   High-density lipoprotein cholesterol

    
 * HF
   
   Heart failure

    
 * HHS
   
   Helsinki Heart Study

    
 * HIV
   
   Human immunodeficiency virus

    
 * HMG-CoA
   
   Hydroxymethylglutaryl-coenzyme A

    
 * HoFH
   
   Homozygous familial hypercholesterolaemia

    
 * HPS2-THRIVE
   
   Heart Protection Study 2-Treatment of HDL to Reduce the Incidence of Vascular
   Events

    
 * HR
   
   Hazard ratio

    
 * HTG
   
   Hypertriglyceridaemia

    
 * IDEAL
   
   Incremental Decrease In End-points Through Aggressive Lipid-lowering

    
 * IDL
   
   Intermediate-density lipoproteins

    
 * IL
   
   Interleukin

    
 * ILLUMINATE
   
   Investigation of Lipid Level Management to Understand its Impact in
   Atherosclerotic Events

    
 * IMPROVE-IT
   
   Improved Reduction of Outcomes: Vytorin Efficacy International Trial

    
 * IPD
   
   Individual participant data

    
 * JUPITER
   
   Justification for the Use of Statins in Prevention: an Intervention Trial
   Evaluating Rosuvastatin

    
 * KDIGO
   
   Kidney Disease: Improving Global Outcomes

    
 * LCAT
   
   Lecithin cholesterol acyltransferase

    
 * LDL
   
   Low-density lipoprotein

    
 * LDL-C
   
   Low-density lipoprotein cholesterol

    
 * LDLR
   
   Low-density lipoprotein receptor

    
 * LEAD
   
   Lower extremity arterial disease

    
 * LEADER
   
   Lower Extremity Arterial Disease Event Reduction

    
 * LPL
   
   Lipoprotein lipase

    
 * Lp(a)
   
   Lipoprotein(a)

    
 * mAb
   
   Monoclonal antibody

    
 * MACE
   
   Major adverse cardiovascular events

    
 * MESA
   
   Multi-Ethnic Study of Atherosclerosis

    
 * MetS
   
   Metabolic syndrome

    
 * MI
   
   Myocardial infarction

    
 * mRNA
   
   Messenger RNA

    
 * MTP
   
   Microsomal triglyceride transfer protein

    
 * NAFLD
   
   Non-alcoholic fatty liver disease

    
 * NNT
   
   Number needed to treat

    
 * NPC1L1
   
   Niemann-Pick C1-like protein 1

    
 * NSTE-ACS
   
   Non-ST elevation acute coronary syndrome

    
 * o.d.
   
   Once a day (omni die)

    
 * ODYSSEY Outcomes
   
   Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During
   Treatment With Alirocumab

    
 * PAD
   
   Peripheral arterial disease

    
 * PCI
   
   Percutaneous coronary intervention

    
 * PCSK9
   
   Proprotein convertase subtilisin/kexin type 9

    
 * PPAR-α
   
   Peroxisome proliferator-activated receptor-α

    
 * PREDIMED
   
   Prevención con Dieta Mediterránea

    
 * PROCAM
   
   Prospective Cardiovascular Munster Study

    
 * PROMINENT
   
   Pemafibrate to Reduce Cardiovascular OutcoMes by Reducing Triglycerides IN
   PatiENts With DiabeTes

    
 * PUFA
   
   Polyunsaturated fatty acid

    
 * PURE
   
   Prospective Urban Rural Epidemiology

    
 * RA
   
   Rheumatoid arthritis

    
 * RCT
   
   Randomized controlled trial

    
 * REDUCE-IT
   
   Reduction of Cardiovascular Events with EPA-Intervention Trial

    
 * REVEAL
   
   Randomized EValuation of the Effects of Anacetrapib Through Lipid
   modification

    
 * RR
   
   Relative risk

    
 * RYR
   
   Red yeast rice

    
 * SAMS
   
   Statin-associated muscle symptoms

    
 * SBP
   
   Systolic blood pressure

    
 * SCORE
   
   Systematic Coronary Risk Estimation

    
 * SEAS
   
   Simvastatin and Ezetimibe in Aortic Stenosis

    
 * SECURE-PCI
   
   Statins Evaluation in Coronary Procedures and Revascularization

    
 * SFA
   
   Saturated fatty acid

    
 * SHARP
   
   Study of Heart and Renal Protection

    
 * siRNA
   
   Small interfering RNA

    
 * SMI
   
   Severe mental illness

    
 * SPARCL
   
   Stroke Prevention by Aggressive Reduction in Cholesterol Levels

    
 * STAREE
   
   STAtin Therapy for Reducing Events in the Elderly

    
 * STEMI
   
   ST-elevation myocardial infarction

    
 * STRENGTH
   
   Outcomes Study to Assess STatin Residual Risk Reduction with EpaNova in HiGh
   CV Risk PatienTs with Hypertriglyceridemia

    
 * TC
   
   Total cholesterol

    
 * T1DM
   
   Type 1 diabetes mellitus

    
 * T2DM
   
   Type 2 diabetes mellitus

    
 * TGs
   
   Triglycerides

    
 * TIA
   
   Transient ischaemic attack

    
 * TIMI
   
   Thrombolysis In Myocardial Infarction

    
 * TNF
   
   Tumour necrosis factor

    
 * TNT
   
   Treating to New Targets

    
 * TRL
   
   Triglyceride-rich lipoprotein

    
 * ULN
   
   Upper limit of normal

    
 * VA-HIT
   
   Veterans Affairs High Density Lipoprotein Intervention Trial

    
 * VITAL
   
   VITamin D and OmegA-3 Trial

    
 * VLDL
   
   Very low-density lipoprotein

    
 * WHO
   
   World Health Organization

    
 * WOSCOPS
   
   West of Scotland Coronary Prevention Study




1 PREAMBLE

Guidelines summarize and evaluate available evidence with the aim of assisting
health professionals in proposing the best management strategies for an
individual patient with a given condition. Guidelines and their recommendations
should facilitate decision making of health professionals in their daily
practice. However, the final decisions concerning an individual patient must be
made by the responsible health professional(s) in consultation with the patient
and caregiver as appropriate.

A great number of guidelines have been issued in recent years by the European
Society of Cardiology (ESC) and its partners such as European Atherosclerosis
Society (EAS), as well as by other societies and organisations. Because of their
impact on clinical practice, quality criteria for the development of guidelines
have been established in order to make all decisions transparent to the user.
The recommendations for formulating and issuing ESC Guidelines can be found on
the ESC website
(http://www.escardio.org/Guidelines-&-Education/Clinical-Practice-Guidelines/Guidelines-development/Writing-ESC-Guidelines).
The ESC Guidelines represent the official position of the ESC on a given topic
and are regularly updated.

The ESC carries out a number of registries which are essential to assess
diagnostic/therapeutic processes, use of resources and adherence to Guidelines.
These registries aim at providing a better understanding of medical practice in
Europe and around the world, based on data collected during routine clinical
practice.

The guidelines are developed together with derivative educational material
addressing the cultural and professional needs for cardiologists and allied
professionals. Collecting high-quality observational data, at appropriate time
interval following the release of ESC Guidelines, will help evaluate the level
of implementation of the Guidelines, checking in priority the key end points
defined with the ESC Guidelines and Education Committees and Task Force members
in charge.

The Members of this Task Force were selected by the ESC and EAS, including
representation from relevant ESC sub-specialty groups, in order to represent
professionals involved with the medical care of patients with this pathology.
Selected experts in the field from both societies undertook a comprehensive
review of the published evidence for management of a given condition according
to ESC Committee for Practice Guidelines (CPG) policy. A critical evaluation of
diagnostic and therapeutic procedures was performed, including assessment of the
risk–benefit ratio. The level of evidence and the strength of the recommendation
of particular management options were weighed and graded according to predefined
ESC scales, as outlined in the tables below.

Table 1

Classes of recommendations

 

 

Open in new tab
Table 1

Classes of recommendations

 

 

Open in new tab
Table 2

Levels of evidence

 

 

Open in new tab
Table 2

Levels of evidence

 

 

Open in new tab

The experts of the writing and reviewing panels provided declaration of interest
forms for all relationships that might be perceived as real or potential sources
of conflicts of interest. These forms were compiled into one file and can be
found on the ESC website (http://www.escardio.org/guidelines). Any changes in
declarations of interest that arise during the writing period were notified to
the ESC and EAS Chairpersons and updated. The Task Force received its entire
financial support from the ESC and EAS without any involvement from the
healthcare industry.

The ESC CPG supervises and coordinates the preparation of new Guidelines. The
Committee is also responsible for the endorsement process of these Guidelines.
The ESC Guidelines undergo extensive review by the CPG and external experts.
After appropriate revisions the Guidelines are approved by all the experts
involved in the Task Force. The finalized document is approved by the CPG and
EAS for publication in the European Heart Journal and Atherosclerosis Journal.
The Guidelines were developed after careful consideration of the scientific and
medical knowledge and the evidence available at the time of their dating.

The task of developing ESC/EAS Guidelines also includes the creation of
educational tools and implementation programmes for the recommendations
including condensed pocket guideline versions, summary slides, booklets with
essential messages, summary cards for non-specialists and an electronic version
for digital applications (smartphones, etc.). These versions are abridged and
thus, for more detailed information, the user should always access the full text
version of the Guidelines, which is freely available via the ESC and EAS
websites and hosted on their journals’ websites (EHJ and Atherosclerosis
Journal). The National Cardiac Societies of the ESC are encouraged to endorse,
translate and implement all ESC Guidelines. Implementation programmes are needed
because it has been shown that the outcome of disease may be favourably
influenced by the thorough application of clinical recommendations.

Health professionals are encouraged to take the ESC/EAS Guidelines fully into
account when exercising their clinical judgment, as well as in the determination
and the implementation of preventive, diagnostic or therapeutic medical
strategies. However, the ESC/EAS Guidelines do not override in any way
whatsoever the individual responsibility of health professionals to make
appropriate and accurate decisions in consideration of each patient's health
condition and in consultation with that patient or the patient's caregiver where
appropriate and/or necessary. It is also the health professional's
responsibility to verify the rules and regulations applicable in each country to
drugs and devices at the time of prescription.


2 INTRODUCTION

The previous ESC/EAS lipid Guidelines were published in August 2016.1 The
emergence of a substantial body of evidence over the last few years has required
new, up-to-date Guidelines.

New evidence has confirmed that the key initiating event in atherogenesis is the
retention of low-density lipoprotein (LDL) cholesterol (LDL-C) and other
cholesterol-rich apolipoprotein (Apo) B-containing lipoproteins within the
arterial wall.2 Several recent placebo-controlled clinical studies have shown
that the addition of either ezetimibe or anti-proprotein convertase
subtilisin/kexin type 9 (PCSK9) monoclonal antibodies (mAbs) to statin therapy
provides a further reduction in atherosclerotic cardiovascular disease (ASCVD)
risk, which is directly and positively correlated with the incrementally
achieved absolute LDL-C reduction. Furthermore, these clinical trials have
clearly indicated that the lower the achieved LDL-C values, the lower the risk
of future cardiovascular (CV) events, with no lower limit for LDL-C values, or
‘J’-curve effect. In addition, studies of the clinical safety of these very low
achieved LDL-C values have proved reassuring, albeit monitoring for longer
periods is required. For raising high-density lipoprotein (HDL) cholesterol
(HDL-C), recent studies have indicated that the currently available therapies do
not reduce the risk of ASCVD. Finally, human Mendelian randomization studies
have demonstrated the critical role of LDL-C, and other cholesterol-rich
ApoB-containing lipoproteins, in atherosclerotic plaque formation and related
subsequent CV events. Thus, there is no longer an ‘LDL-C hypothesis’, but
established facts that increased LDL-C values are causally related to ASCVD, and
that lowering LDL particles and other ApoB-containing lipoproteins as much as
possible reduces CV events.

In order to be aligned with these new findings, the ESC/EAS Task Force members
who have written these Guidelines have proposed new LDL-C goals, as well as a
revised CV risk stratification, which are especially relevant to high- and
very-high-risk patients.

These novel ESC/EAS Guidelines on lipids provide important new advice on patient
management, which should enable more clinicians to efficiently and safely reduce
CV risk through lipid modification.


2.1 WHAT IS NEW IN THE 2019 GUIDELINES?

New recommendations, and new and revised concepts, are presented in Table 3.

Table 3

New recommendations, and new and revised concepts

   

   

ACS = acute coronary syndrome; ApoB = apolipoprotein B; ASCVD = atherosclerotic
cardiovascular disease; CAC = coronary artery calcium; CHD = coronary heart
disease; CT = computed tomography; CV = cardiovascular; CVD = cardiovascular
disease; DM = diabetes mellitus; FH = familial hypercholesterolaemia; HDL =
high-density lipoprotein; LDL-C = low-density lipoproteins cholesterol; Lp(a) =
lipoprotein(a); PCSK9 = proprotein convertase subtilisin/kexin type 9; PUFAs =
polyunsaturated fatty acids; RCTs = randomized controlled trials; T1DM = type 1
diabetes mellitus; T2DM = type 2 diabetes mellitus; TGs = triglycerides.

Open in new tab
Table 3

New recommendations, and new and revised concepts

   

   

ACS = acute coronary syndrome; ApoB = apolipoprotein B; ASCVD = atherosclerotic
cardiovascular disease; CAC = coronary artery calcium; CHD = coronary heart
disease; CT = computed tomography; CV = cardiovascular; CVD = cardiovascular
disease; DM = diabetes mellitus; FH = familial hypercholesterolaemia; HDL =
high-density lipoprotein; LDL-C = low-density lipoproteins cholesterol; Lp(a) =
lipoprotein(a); PCSK9 = proprotein convertase subtilisin/kexin type 9; PUFAs =
polyunsaturated fatty acids; RCTs = randomized controlled trials; T1DM = type 1
diabetes mellitus; T2DM = type 2 diabetes mellitus; TGs = triglycerides.

Open in new tab


3 WHAT IS CARDIOVASCULAR DISEASE PREVENTION?


3.1 DEFINITION AND RATIONALE

Cardiovascular disease (CVD), of which ASCVD is the major component, is
responsible for >4 million deaths in Europe each year. It kills more women (2.2
million) than men (1.8 million), although CV deaths before the age of 65 years
are more common in men (490 000 vs. 193 000).3 Prevention is defined as a
co-ordinated set of actions, either at the population or individual level, aimed
at eliminating or minimizing the impact of CV diseases and their related
disabilities. More patients are surviving their first CVD event and are at
high-risk of recurrences. In addition, the prevalence of some risk factors,
notably diabetes (DM) and obesity, is increasing. The importance of ASCVD
prevention remains undisputed and should be delivered at the general population
level by promoting healthy lifestyle behaviour,4 and at the individual level by
tackling unhealthy lifestyles and by reducing increased levels of causal CV risk
factors, such as LDL cholesterol or blood pressure (BP) levels.


3.2 DEVELOPMENT OF THE JOINT TASK FORCE GUIDELINES FOR THE MANAGEMENT OF
DYSLIPIDAEMIAS

The present Guidelines represent an evidence-based consensus of the European
Task Force, including the ESC and the EAS.

By appraising the current evidence and identifying remaining knowledge gaps in
the management of dyslipidaemias, the Task Force has formulated recommendations
to guide action in clinical practice to prevent ASCVD by modifying plasma lipid
levels.

This document has been developed for healthcare professionals to facilitate
informed communication with individuals about their CV risk and the benefits of
adopting and sustaining a healthy lifestyle, and of early modification of their
lipid-related CV risk. In addition, the Guidelines provide tools for healthcare
professionals to promote up-to-date intervention strategies, integrate these
strategies into national or regional prevention frameworks, and to translate
them into locally delivered healthcare services, in line with the
recommendations of the World Health Organization (WHO) Global Status Report on
Noncommunicable Diseases 2014.5

A lifetime approach to CV risk should be considered.1 This implies that—apart
from improving lifestyle habits and reducing risk factor levels in patients with
established ASCVD, and in those at increased risk of developing ASCVD—people of
all ages should be encouraged to adopt or sustain a healthy lifestyle.


4 TOTAL CARDIOVASCULAR RISK


4.1 TOTAL CARDIOVASCULAR RISK ESTIMATION

CV risk in the context of these Guidelines means the likelihood of a person
developing an atherosclerotic CV event over a defined period of time. Total CVD
risk expresses the combined effect of a number of risk factors on this risk
estimate. In these Guidelines, we address the lipid-related contribution to
total CV risk and how to manage it at the clinical level.

4.1.1 RATIONALE FOR ASSESSING TOTAL CARDIOVASCULAR DISEASE RISK

All current guidelines on the prevention of ASCVD in clinical practice recommend
the assessment of total CVD risk. Prevention of ASCVD in a given person should
relate to his or her total CV risk: the higher the risk, the more intense the
action should be.

Many risk assessment systems are available and have been comprehensively
reviewed (Supplementary Table 1 in the Supplementary Data). Most guidelines use
one of these risk assessment systems.6–8 Ideally, risk charts should be based on
country-specific cohort data. These are not available for most countries. The
SCORE (Systematic Coronary Risk Estimation) system can be recalibrated for use
in different populations by adjusting for secular changes in CVD mortality and
risk factor prevalence. Calibrated country-specific versions are available for
many European countries and can be found at http://www.heartscore.org. These are
now being updated to provide recalibrated, contemporaneous country-specific
charts for all European countries. Other risk estimation systems—using both
fatal and non-fatal events—can also be recalibrated, but the process is easier
and scientifically more robust for mortality than for total events. The European
Guidelines on CVD prevention in clinical practice (both the 20129 and 201610
versions) recommend the use of the SCORE system because it is based on large,
representative European cohort data sets and because it is relatively
straightforward to recalibrate for individual countries.

Persons with documented ASCVD, type 1 or type 2 DM (T1DM and T2DM,
respectively), very high levels of individual risk factors, or chronic kidney
disease (CKD) are generally at very-high or high total CV risk. No risk
estimation models are needed for such persons; they all need active management
of all risk factors. For other, apparently healthy people, the use of a risk
estimation system such as SCORE, which estimates the 10 year cumulative risk of
a first fatal atherosclerotic event, is recommended to estimate total CV risk,
since many people have several risk factors that, in combination, may result in
high levels of total CV risk.

Risk estimates have been produced as charts for high- and low-risk regions in
Europe (Figures 1 and 2).11 All International Classification of Diseases codes
that are related to deaths from vascular origin caused by atherosclerosis are
included. The reasons for retaining a system that estimates fatal as opposed to
total fatal + non-fatal events are that non-fatal events are dependent on
definition, developments in diagnostic tests, and methods of ascertainment, all
of which can vary, resulting in very variable multipliers to convert fatal to
total events. In addition, total event charts, in contrast to those based on
mortality, are more difficult to recalibrate to suit different populations. That
said, work is in progress to produce regional total event charts.

Figure 1
Open in new tabDownload slide

Systematic Coronary Risk Estimation chart for European populations at high
cardiovascular disease risk. The 10-year risk of fatal cardiovascular disease in
populations at high cardiovascular disease risk based on the following risk
factors: age, gender, smoking, systolic blood pressure, and total cholesterol.
To convert the risk of fatal cardiovascular disease to risk of total (fatal +
non-fatal) cardiovascular disease, multiply by 3 in men and by 4 in women, and
slightly less in older people. Note: the Systematic Coronary Risk Estimation
chart is for use in people without overt cardiovascular disease, diabetes (type
1 and 2), chronic kidney disease, familial hypercholesterolaemia, or very high
levels of individual risk factors because such people are already at high-risk
and need intensive risk factor management. Cholesterol: 1 mmol/L = 38.67 mg/dL.
The SCORE risk charts presented above differ slightly from those in the 2016
European Society of Cardiology/European Atherosclerosis Society Guidelines for
the management of dyslipidaemias and the 2016 European Guidelines on
cardiovascular disease prevention in clinical practice, in that: (i) age has
been extended from age 65 to 70; (ii) the interaction between age and each of
the other risk factors has been incorporated, thus reducing the overestimation
of risk in older persons in the original Systematic Coronary Risk Estimation
charts; and (iii) the cholesterol band of 8 mmol/L has been removed, since such
persons will qualify for further evaluation in any event. SCORE = Systematic
Coronary Risk Estimation.

Figure 2
Open in new tabDownload slide

Systematic Coronary Risk Estimation chart for European populations at low
cardiovascular disease risk. The 10-year risk of fatal cardiovascular disease in
populations at low cardiovascular disease risk based on the following risk
factors: age, gender, smoking, systolic blood pressure, and total cholesterol.
To convert the risk of fatal cardiovascular disease to risk of total (fatal +
non-fatal) cardiovascular disease, multiply by 3 in men and by 4 in women, and
slightly less in older people. Note: the Systematic Coronary Risk Estimation
chart is for use in people without overt cardiovascular disease, diabetes (type
1 and 2), chronic kidney disease, familial hypercholesterolaemia, or very high
levels of individual risk factors because such people are already at high-risk
and need intensive risk factor management. Cholesterol: 1 mmol/L=38.67 mg/dL.
The SCORE risk charts presented above differ slightly from those in the 2016
European Society of Cardiology/European Atherosclerosis Society Guidelines for
the management of dyslipidaemias and the 2016 European Guidelines on
cardiovascular disease prevention in clinical practice, in that: (i) age has
been extended from age 65 to 70; (ii) the interaction between age and each of
the other risk factors has been incorporated, thus reducing the overestimation
of risk in older persons in the original Systematic Coronary Risk Estimation
charts; and (iii) the cholesterol band of 8 mmol/L has been removed since such
persons will qualify for further evaluation in any event. SCORE = Systematic
Coronary Risk Estimation.

The SCORE data indicate that the total CVD event risk is about three times
higher than the risk of fatal CVD for men, so a SCORE risk of 5% translates into
a CVD risk of ∼15% of total (fatal + non-fatal) CVD endpoints; the multiplier is
higher in women and lower in older people.

Clinicians often ask for thresholds to trigger certain interventions. This is
problematic since risk is a continuum and there is no threshold at which, for
example, a drug is automatically indicated. This is true for all continuous risk
factors such as plasma cholesterol or systolic BP (SBP). Therefore, the goals
that are proposed in this document reflect this concept.

A particular problem relates to young people with high levels of risk factors; a
low absolute risk may conceal a very high relative risk requiring at least
intensive lifestyle advice. To motivate young people (i.e. aged <40 years) not
to delay changing their unhealthy lifestyle, an estimate of their relative
risk—illustrating that lifestyle changes can reduce relative risk
substantially—may be helpful (Supplementary Figure 1).

Another approach to this problem is to use CV risk age. The risk age of a person
with several CV risk factors is the age of a person with the same level of risk
but with ideal levels of risk factors. Thus, a high-risk 40-year-old would have
a risk age ≥65 years. Risk age can be estimated visually by looking at the SCORE
chart (as illustrated in Supplementary Figure 2). In this chart, the risk age of
a person with risk factors is defined as the age at which a person with ideal
risk factor levels would reach the same risk level. Ideal risk factors are
non-smoking, total cholesterol (TC) ≤4 mmol/L (≤155 mg/dL), and SBP ≤120 mmHg.
Risk age is also automatically calculated as part of the latest revision of
HeartScore (http://www.HeartScore.org).

Risk age has been shown to be independent of the CV endpoint used,6,8 can be
used in any population regardless of baseline risk or secular changes in
mortality, and therefore avoids the need for recalibration.

Lifetime risk is another approach to illustrate the impact of risk factors that
may be useful in younger people.12 The greater the burden of risk factors, the
higher the lifetime risk. This approach produces higher risk figures for younger
people because of their longer exposure times. Therefore, it is more useful as a
way of illustrating risk than as a guide to treatment, because therapeutic
trials have been based on a fixed follow-up period and not on lifetime risk.

Another problem relates to older people. In some age categories, the majority of
people, especially males, will have estimated 10 year cumulative CV death risks
exceeding the 5–10% level, based on age only, even when other CV risk factor
levels are relatively low. Therefore, before initiating treatment in the
elderly, clinicians should evaluate patients carefully. The relative strengths
of risk factors vary with age and SCORE overestimates risk in older people (that
is, those aged >65 years).11 These Guidelines include illustrative charts for
older people (see Figures 1 and 2). While older people benefit from smoking
cessation, and control of hypertension and hyperlipidaemia (see section 9.3),
clinical judgement is required to avoid side effects from overmedication.

The additional impact of HDL-C on risk estimation is illustrated in
Supplementary Figures 3 and 4; HDL-C can be used to increase the accuracy of the
risk evaluation. In these charts, HDL-C is used categorically. The electronic
version of SCORE, HeartScore (http://www.heartscore.org/en_GB/), has been
modified to take HDL-C into consideration as a continuous variable. Clinicians
should be aware that at extremely high values [above ∼2.3 mmol/L (90 mg/dL)] of
HDL-C there appears to be an increased risk of ASCVD, so at such levels HDL-C
cannot be used as a risk predictor.

4.1.2 HOW TO USE THE RISK ESTIMATION CHARTS

Use of the low- or the high-risk SCORE charts will depend on the CVD mortality
experience in each country. While any cut-off point is arbitrary and open to
debate, in these Guidelines, the cut-off point for calling a country ‘low CVD
risk’ is based on WHO data derived from the Global Burden of Disease Study.

Countries are categorized as low-risk if their age-adjusted 2016 CVD mortality
rate was <150/100 000 (for men and women together)
(http://www.who.int/healthinfo/global_burden_disease/estimates/en/). Countries
with a CVD mortality rate of ≥150/100 000 or more are considered to be at
high-risk.

Boxes 1 to 5 summarize the main points regarding the risk estimation charts and
their use.

Box 1

How to use the risk estimation charts

To estimate a person’s 10-year risk of CVD death, find the table for his/her
gender, smoking status, and age. Within the table, find the cell nearest to the
person’s BP and TC. Risk estimates will need to be adjusted upwards as the
person approaches the next age category. Risk is initially assessed on the level
of TC and systolic BP before treatment, if known. The longer the treatment and
the more effective it is, the greater the reduction in risk, but in general it
will not be more than about one-third of the baseline risk. For example, for a
person on antihypertensive drug treatment in whom the pre-treatment BP is not
known, if the total CV SCORE risk is 6%, then the pre-treatment total CV risk
may have been 9%. Low-risk persons should be offered advice to maintain their
low-risk status. While no threshold is universally applicable, the intensity of
advice should increase with increasing risk. The charts may be used to give some
indication of the effects of reducing risk factors, given that there is
apparently a time lag before the risk reduces. In general, people who stop
smoking halve their cumulative risk over a relatively short period of time. 

To estimate a person’s 10-year risk of CVD death, find the table for his/her
gender, smoking status, and age. Within the table, find the cell nearest to the
person’s BP and TC. Risk estimates will need to be adjusted upwards as the
person approaches the next age category. Risk is initially assessed on the level
of TC and systolic BP before treatment, if known. The longer the treatment and
the more effective it is, the greater the reduction in risk, but in general it
will not be more than about one-third of the baseline risk. For example, for a
person on antihypertensive drug treatment in whom the pre-treatment BP is not
known, if the total CV SCORE risk is 6%, then the pre-treatment total CV risk
may have been 9%. Low-risk persons should be offered advice to maintain their
low-risk status. While no threshold is universally applicable, the intensity of
advice should increase with increasing risk. The charts may be used to give some
indication of the effects of reducing risk factors, given that there is
apparently a time lag before the risk reduces. In general, people who stop
smoking halve their cumulative risk over a relatively short period of time. 

BP = blood pressure; CV = cardiovascular; CVD = cardiovascular disease; SCORE =
Systematic Coronary Risk Estimation; TC = total cholesterol.

Open in new tab
Box 1

How to use the risk estimation charts

To estimate a person’s 10-year risk of CVD death, find the table for his/her
gender, smoking status, and age. Within the table, find the cell nearest to the
person’s BP and TC. Risk estimates will need to be adjusted upwards as the
person approaches the next age category. Risk is initially assessed on the level
of TC and systolic BP before treatment, if known. The longer the treatment and
the more effective it is, the greater the reduction in risk, but in general it
will not be more than about one-third of the baseline risk. For example, for a
person on antihypertensive drug treatment in whom the pre-treatment BP is not
known, if the total CV SCORE risk is 6%, then the pre-treatment total CV risk
may have been 9%. Low-risk persons should be offered advice to maintain their
low-risk status. While no threshold is universally applicable, the intensity of
advice should increase with increasing risk. The charts may be used to give some
indication of the effects of reducing risk factors, given that there is
apparently a time lag before the risk reduces. In general, people who stop
smoking halve their cumulative risk over a relatively short period of time. 

To estimate a person’s 10-year risk of CVD death, find the table for his/her
gender, smoking status, and age. Within the table, find the cell nearest to the
person’s BP and TC. Risk estimates will need to be adjusted upwards as the
person approaches the next age category. Risk is initially assessed on the level
of TC and systolic BP before treatment, if known. The longer the treatment and
the more effective it is, the greater the reduction in risk, but in general it
will not be more than about one-third of the baseline risk. For example, for a
person on antihypertensive drug treatment in whom the pre-treatment BP is not
known, if the total CV SCORE risk is 6%, then the pre-treatment total CV risk
may have been 9%. Low-risk persons should be offered advice to maintain their
low-risk status. While no threshold is universally applicable, the intensity of
advice should increase with increasing risk. The charts may be used to give some
indication of the effects of reducing risk factors, given that there is
apparently a time lag before the risk reduces. In general, people who stop
smoking halve their cumulative risk over a relatively short period of time. 

BP = blood pressure; CV = cardiovascular; CVD = cardiovascular disease; SCORE =
Systematic Coronary Risk Estimation; TC = total cholesterol.

Open in new tab
Box 2

Risk estimation charts for different countries

The low-risk charts should be considered for use in Austria, Belgium, Cyprus,
Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy,
Luxembourg, Netherlands, Norway, Malta, Portugal, Slovenia, Spain, Sweden,
Switzerland, and the UK. The high-risk charts should be considered for use in
Albania, Algeria, Armenia, Bosnia and Herzegovina, Croatia, Czech Republic,
Estonia, Hungary, Latvia, Lebanon, Libya, Lithuania, Montenegro, Morocco,
Poland, Romania, Serbia, Slovakia, Tunisia, and Turkey. Some countries have a
cardiovascular disease mortality rate >350/100 000, and the high-risk chart may
underestimate risk. These are Azerbaijan, Belarus, Bulgaria, Egypt, Georgia,
Kazakhstan, Kyrgyzstan, North Macedonia, Republic of Moldova, Russian
Federation, Syria, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. 

The low-risk charts should be considered for use in Austria, Belgium, Cyprus,
Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy,
Luxembourg, Netherlands, Norway, Malta, Portugal, Slovenia, Spain, Sweden,
Switzerland, and the UK. The high-risk charts should be considered for use in
Albania, Algeria, Armenia, Bosnia and Herzegovina, Croatia, Czech Republic,
Estonia, Hungary, Latvia, Lebanon, Libya, Lithuania, Montenegro, Morocco,
Poland, Romania, Serbia, Slovakia, Tunisia, and Turkey. Some countries have a
cardiovascular disease mortality rate >350/100 000, and the high-risk chart may
underestimate risk. These are Azerbaijan, Belarus, Bulgaria, Egypt, Georgia,
Kazakhstan, Kyrgyzstan, North Macedonia, Republic of Moldova, Russian
Federation, Syria, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. 

See http://apps.who.int/gho/data/node.home.

Open in new tab
Box 2

Risk estimation charts for different countries

The low-risk charts should be considered for use in Austria, Belgium, Cyprus,
Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy,
Luxembourg, Netherlands, Norway, Malta, Portugal, Slovenia, Spain, Sweden,
Switzerland, and the UK. The high-risk charts should be considered for use in
Albania, Algeria, Armenia, Bosnia and Herzegovina, Croatia, Czech Republic,
Estonia, Hungary, Latvia, Lebanon, Libya, Lithuania, Montenegro, Morocco,
Poland, Romania, Serbia, Slovakia, Tunisia, and Turkey. Some countries have a
cardiovascular disease mortality rate >350/100 000, and the high-risk chart may
underestimate risk. These are Azerbaijan, Belarus, Bulgaria, Egypt, Georgia,
Kazakhstan, Kyrgyzstan, North Macedonia, Republic of Moldova, Russian
Federation, Syria, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. 

The low-risk charts should be considered for use in Austria, Belgium, Cyprus,
Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy,
Luxembourg, Netherlands, Norway, Malta, Portugal, Slovenia, Spain, Sweden,
Switzerland, and the UK. The high-risk charts should be considered for use in
Albania, Algeria, Armenia, Bosnia and Herzegovina, Croatia, Czech Republic,
Estonia, Hungary, Latvia, Lebanon, Libya, Lithuania, Montenegro, Morocco,
Poland, Romania, Serbia, Slovakia, Tunisia, and Turkey. Some countries have a
cardiovascular disease mortality rate >350/100 000, and the high-risk chart may
underestimate risk. These are Azerbaijan, Belarus, Bulgaria, Egypt, Georgia,
Kazakhstan, Kyrgyzstan, North Macedonia, Republic of Moldova, Russian
Federation, Syria, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. 

See http://apps.who.int/gho/data/node.home.

Open in new tab
Box 3

Qualifiers

The charts can assist in risk assessment and management, but must be interpreted
in light of the clinician’s knowledge and experience, and of the patient’s
pre-test likelihood of CVD. Risk will be overestimated in countries with
decreasing CVD mortality, and underestimated in countries in which mortality is
increasing. This is dealt with by recalibration
(http://www.heartscore.org/en_GB/). Risk estimates are lower in women than in
men. However, risk is only deferred in women; the risk of a 60-year-old woman is
similar to that of a 50-year-old man. Ultimately, more women die from CVD than
men. Relative risks may be unexpectedly high in young persons, even if absolute
risk levels are low. The relative risk chart (Supplementary Figure 1) and the
estimated risk age (Supplementary Figure 2) may be helpful in identifying and
counselling such persons. 

The charts can assist in risk assessment and management, but must be interpreted
in light of the clinician’s knowledge and experience, and of the patient’s
pre-test likelihood of CVD. Risk will be overestimated in countries with
decreasing CVD mortality, and underestimated in countries in which mortality is
increasing. This is dealt with by recalibration
(http://www.heartscore.org/en_GB/). Risk estimates are lower in women than in
men. However, risk is only deferred in women; the risk of a 60-year-old woman is
similar to that of a 50-year-old man. Ultimately, more women die from CVD than
men. Relative risks may be unexpectedly high in young persons, even if absolute
risk levels are low. The relative risk chart (Supplementary Figure 1) and the
estimated risk age (Supplementary Figure 2) may be helpful in identifying and
counselling such persons. 

CVD = cardiovascular disease.

Open in new tab
Box 3

Qualifiers

The charts can assist in risk assessment and management, but must be interpreted
in light of the clinician’s knowledge and experience, and of the patient’s
pre-test likelihood of CVD. Risk will be overestimated in countries with
decreasing CVD mortality, and underestimated in countries in which mortality is
increasing. This is dealt with by recalibration
(http://www.heartscore.org/en_GB/). Risk estimates are lower in women than in
men. However, risk is only deferred in women; the risk of a 60-year-old woman is
similar to that of a 50-year-old man. Ultimately, more women die from CVD than
men. Relative risks may be unexpectedly high in young persons, even if absolute
risk levels are low. The relative risk chart (Supplementary Figure 1) and the
estimated risk age (Supplementary Figure 2) may be helpful in identifying and
counselling such persons. 

The charts can assist in risk assessment and management, but must be interpreted
in light of the clinician’s knowledge and experience, and of the patient’s
pre-test likelihood of CVD. Risk will be overestimated in countries with
decreasing CVD mortality, and underestimated in countries in which mortality is
increasing. This is dealt with by recalibration
(http://www.heartscore.org/en_GB/). Risk estimates are lower in women than in
men. However, risk is only deferred in women; the risk of a 60-year-old woman is
similar to that of a 50-year-old man. Ultimately, more women die from CVD than
men. Relative risks may be unexpectedly high in young persons, even if absolute
risk levels are low. The relative risk chart (Supplementary Figure 1) and the
estimated risk age (Supplementary Figure 2) may be helpful in identifying and
counselling such persons. 

CVD = cardiovascular disease.

Open in new tab
Box 4

Factors modifying Systematic Coronary Risk Estimation risks

Social deprivation: the origin of many of the causes of CVD. Obesity and central
obesity as measured by the body mass index and waist circumference,
respectively. Physical inactivity. Psychosocial stress including vital
exhaustion. Family history of premature CVD (men: <55 years and women: <60
years). Chronic immune-mediated inflammatory disorder. Major psychiatric
disorders. Treatment for human immunodeficiency virus infection. Atrial
fibrillation. Left ventricular hypertrophy. Chronic kidney disease. Obstructive
sleep apnoea syndrome. Non-alcoholic fatty liver disease. 

Social deprivation: the origin of many of the causes of CVD. Obesity and central
obesity as measured by the body mass index and waist circumference,
respectively. Physical inactivity. Psychosocial stress including vital
exhaustion. Family history of premature CVD (men: <55 years and women: <60
years). Chronic immune-mediated inflammatory disorder. Major psychiatric
disorders. Treatment for human immunodeficiency virus infection. Atrial
fibrillation. Left ventricular hypertrophy. Chronic kidney disease. Obstructive
sleep apnoea syndrome. Non-alcoholic fatty liver disease. 

CVD = cardiovascular disease.

Open in new tab
Box 4

Factors modifying Systematic Coronary Risk Estimation risks

Social deprivation: the origin of many of the causes of CVD. Obesity and central
obesity as measured by the body mass index and waist circumference,
respectively. Physical inactivity. Psychosocial stress including vital
exhaustion. Family history of premature CVD (men: <55 years and women: <60
years). Chronic immune-mediated inflammatory disorder. Major psychiatric
disorders. Treatment for human immunodeficiency virus infection. Atrial
fibrillation. Left ventricular hypertrophy. Chronic kidney disease. Obstructive
sleep apnoea syndrome. Non-alcoholic fatty liver disease. 

Social deprivation: the origin of many of the causes of CVD. Obesity and central
obesity as measured by the body mass index and waist circumference,
respectively. Physical inactivity. Psychosocial stress including vital
exhaustion. Family history of premature CVD (men: <55 years and women: <60
years). Chronic immune-mediated inflammatory disorder. Major psychiatric
disorders. Treatment for human immunodeficiency virus infection. Atrial
fibrillation. Left ventricular hypertrophy. Chronic kidney disease. Obstructive
sleep apnoea syndrome. Non-alcoholic fatty liver disease. 

CVD = cardiovascular disease.

Open in new tab

Social deprivation and psychosocial stress set the scene for increased risk.13
For those at moderate risk, other factors—including metabolic factors such as
increased ApoB, lipoprotein(a) [Lp(a)], triglycerides (TGs), or C-reactive
protein; the presence of albuminuria; the presence of atherosclerotic plaque in
the carotid or femoral arteries; or the coronary artery calcium (CAC) score—may
improve risk classification. Many other biomarkers are also associated with
increased CVD risk, although few of these have been shown to be associated with
appreciable reclassification. Total CV risk will also be higher than indicated
in the SCORE charts in asymptomatic persons with abnormal markers of subclinical
atherosclerotic vascular damage. Reclassification is of value in people
identified as being at moderate CV risk by using markers such as CAC score >100
Agatston units, ankle–brachial index (ABI) <0.9 or >1.40, carotid–femoral pulse
wave velocity >10 m/s, or the presence of plaques at carotid or femoral
ultrasonography. In studies comparing these markers, CAC had the best
reclassification ability.14–16

Some factors such as a high HDL-C up to 2.3 mmol/L (90mg/dL)17 or a family
history of longevity can also be associated with lower risk.

Box 5

Risk estimation: key messages

In apparently healthy persons, CVD risk is most frequently the result of
multiple, interacting risk factors. This is the basis for total CV risk
estimation and management. Risk factor screening including the lipid profile
should be considered in men >40 years old, and in women >50 years of age or
post-menopausal. A risk estimation system such as SCORE can assist in making
logical management decisions, and may help to avoid both under- and
overtreatment. Certain individuals declare themselves to be at high or very high
CVD risk without needing risk scoring, and all risk factors require immediate
attention. This is true for patients with documented CVD, older individuals with
long-standing DM, familial hypercholesterolaemia, chronic kidney disease,
carotid or femoral plaques, coronary artery calcium score >100, or extreme Lp(a)
elevation. All risk estimation systems are relatively crude and require
attention to qualifying statements. Additional factors affecting risk can be
accommodated in electronic risk estimation systems such as HeartScore
(www.heartscore.org). The total risk approach allows flexibility; if optimal
control cannot be achieved with one risk factor, trying harder with the other
factors can still reduce risk. 

In apparently healthy persons, CVD risk is most frequently the result of
multiple, interacting risk factors. This is the basis for total CV risk
estimation and management. Risk factor screening including the lipid profile
should be considered in men >40 years old, and in women >50 years of age or
post-menopausal. A risk estimation system such as SCORE can assist in making
logical management decisions, and may help to avoid both under- and
overtreatment. Certain individuals declare themselves to be at high or very high
CVD risk without needing risk scoring, and all risk factors require immediate
attention. This is true for patients with documented CVD, older individuals with
long-standing DM, familial hypercholesterolaemia, chronic kidney disease,
carotid or femoral plaques, coronary artery calcium score >100, or extreme Lp(a)
elevation. All risk estimation systems are relatively crude and require
attention to qualifying statements. Additional factors affecting risk can be
accommodated in electronic risk estimation systems such as HeartScore
(www.heartscore.org). The total risk approach allows flexibility; if optimal
control cannot be achieved with one risk factor, trying harder with the other
factors can still reduce risk. 

CV = cardiovascular; CVD = cardiovascular disease; DM = diabetes mellitus; SCORE
= Systematic Coronary Risk Estimation.

Open in new tab
Box 5

Risk estimation: key messages

In apparently healthy persons, CVD risk is most frequently the result of
multiple, interacting risk factors. This is the basis for total CV risk
estimation and management. Risk factor screening including the lipid profile
should be considered in men >40 years old, and in women >50 years of age or
post-menopausal. A risk estimation system such as SCORE can assist in making
logical management decisions, and may help to avoid both under- and
overtreatment. Certain individuals declare themselves to be at high or very high
CVD risk without needing risk scoring, and all risk factors require immediate
attention. This is true for patients with documented CVD, older individuals with
long-standing DM, familial hypercholesterolaemia, chronic kidney disease,
carotid or femoral plaques, coronary artery calcium score >100, or extreme Lp(a)
elevation. All risk estimation systems are relatively crude and require
attention to qualifying statements. Additional factors affecting risk can be
accommodated in electronic risk estimation systems such as HeartScore
(www.heartscore.org). The total risk approach allows flexibility; if optimal
control cannot be achieved with one risk factor, trying harder with the other
factors can still reduce risk. 

In apparently healthy persons, CVD risk is most frequently the result of
multiple, interacting risk factors. This is the basis for total CV risk
estimation and management. Risk factor screening including the lipid profile
should be considered in men >40 years old, and in women >50 years of age or
post-menopausal. A risk estimation system such as SCORE can assist in making
logical management decisions, and may help to avoid both under- and
overtreatment. Certain individuals declare themselves to be at high or very high
CVD risk without needing risk scoring, and all risk factors require immediate
attention. This is true for patients with documented CVD, older individuals with
long-standing DM, familial hypercholesterolaemia, chronic kidney disease,
carotid or femoral plaques, coronary artery calcium score >100, or extreme Lp(a)
elevation. All risk estimation systems are relatively crude and require
attention to qualifying statements. Additional factors affecting risk can be
accommodated in electronic risk estimation systems such as HeartScore
(www.heartscore.org). The total risk approach allows flexibility; if optimal
control cannot be achieved with one risk factor, trying harder with the other
factors can still reduce risk. 

CV = cardiovascular; CVD = cardiovascular disease; DM = diabetes mellitus; SCORE
= Systematic Coronary Risk Estimation.

Open in new tab


4.2 RISK LEVELS

A total CV risk estimate is part of a continuum. The cut-off points that are
used to define high-risk are, in part, both arbitrary and based on the risk
levels at which benefit is evident in clinical trials. In clinical practice,
consideration should be given to practical issues in relation to the local
healthcare systems. Not only should those at high risk be identified and
managed, but those at moderate risk should also receive professional advice
regarding lifestyle changes; in some cases, drug therapy will be needed to
reduce atherosclerotic risk.

Low-risk people should be given advice to help them maintain this status. Thus,
the intensity of preventive actions should be tailored to the patient’s total CV
risk. The strongest driver of total CV risk is age, which can be considered as
‘exposure time’ to risk factors.

For these reasons, the Task Force suggests the following categories of risk and
LDL-C goals, based on the best available evidence and in an ideal setting with
unlimited resources. These categories represent a counsel of perfection, but
these ideals are for guidance only and practical decision-making must be based
on what is appropriate to the local situation.

With these considerations, we propose the levels of total CV risk presented in
Table 4.

Table 4

Cardiovascular risk categories

 

 

ASCVD = atherosclerotic cardiovascular disease; ACS = acute coronary syndrome;
BP = blood pressure; CABG = coronary artery bypass graft surgery; CKD = chronic
kidney disease; CT = computed tomography; CVD = cardiovascular disease; DM =
diabetes mellitus; eGFR = estimated glomerular filtration rate; FH = familial
hypercholesterolaemia; LDL-C = low-density lipoprotein cholesterol; MI =
myocardial infarction; PCI = percutaneous coronary intervention; SCORE =
Systematic Coronary Risk Estimation; T1DM = type 1 DM; T2DM = type 2 DM; TC =
total cholesterol; TIA = transient ischaemic attack.

a

Target organ damage is defined as microalbuminuria, retinopathy, or neuropathy.

Open in new tab
Table 4

Cardiovascular risk categories

 

 

ASCVD = atherosclerotic cardiovascular disease; ACS = acute coronary syndrome;
BP = blood pressure; CABG = coronary artery bypass graft surgery; CKD = chronic
kidney disease; CT = computed tomography; CVD = cardiovascular disease; DM =
diabetes mellitus; eGFR = estimated glomerular filtration rate; FH = familial
hypercholesterolaemia; LDL-C = low-density lipoprotein cholesterol; MI =
myocardial infarction; PCI = percutaneous coronary intervention; SCORE =
Systematic Coronary Risk Estimation; T1DM = type 1 DM; T2DM = type 2 DM; TC =
total cholesterol; TIA = transient ischaemic attack.

a

Target organ damage is defined as microalbuminuria, retinopathy, or neuropathy.

Open in new tab

4.2.1 ROLE OF NON-INVASIVE CARDIOVASCULAR IMAGING TECHNIQUES IN THE ASSESSMENT
OF TOTAL CARDIOVASCULAR DISEASE RISK

Non-invasive imaging techniques can detect the presence, estimate the extent,
and evaluate the clinical consequences of atherosclerotic vascular damage.
Detection of coronary artery calcification with non-contrast computed tomography
(CT) gives a good estimate of the atherosclerotic burden and is strongly
associated with CV events.18 A recent meta-analysis from the US Preventive
Services Task Force summarized the available evidence on the value of
non-traditional risk factors for risk prediction, and found that, although there
are no randomized trials showing that the use of CAC reduces health outcomes,
nevertheless it improves both discrimination and reclassification.19 Assessment
of carotid or femoral plaque burden with ultrasound has also been demonstrated
to be predictive of CV events, comparable to CAC,20–23 while the measurement of
the carotid intima–media thickness is inferior to CAC score and carotid plaque
detection.16,24,25

In asymptomatic patients at low or moderate risk who would be eligible for
statin therapy (see Table 5), assessment of ASCVD with imaging may have an
impact on medical treatment, both from the physician’s and the patient’s points
of view. Data from the Multi-Ethnic Study of Atherosclerosis (MESA) showed that
41–57% of individuals who would be eligible for statin therapy had a CAC score
of zero and the rate of atherosclerotic CVD events in the 10 year follow-up
period was low (1.5–4.9%).26 In contrast, the rates of ASCVD and coronary heart
disease (CHD) events in individuals with a CAC score >100 Agatston were 18.9 and
12.7 per 1000 person-years, respectively.18 Compared with a strategy of treating
all patients, the use of CAC score to guide long-term statin therapy has been
shown to be cost-effective.27 Note that CAC score is often very low in patients
younger than 45 years of age with severe familial hypercholesterolaemia (FH),
including homozygous FH (HoFH), and has low specificity in this population.

Assessment of coronary luminal stenosis >50% and plaque composition with
coronary CT angiography also provides incremental prognostic value over
traditional risk stratification models.28 As a result, in asymptomatic
individuals with moderate risk, the presence of a CAC score >100 Agatston, and
carotid or femoral plaque burden on ultrasonography, may reclassify them to a
higher risk category. Therefore, the use of methods to detect these markers
should be of interest in that group (see Recommendations for cardiovascular
imaging for risk assessment of atherosclerotic cardiovascular disease
below).14–16 Overall, CAC score assessment with CT may be considered in
individuals at low or moderate risk in whom the respective LDL-C goal is not
achieved with lifestyle intervention alone, and pharmacological therapy is an
option (see Table 5). The use of imaging techniques to determine the presence
and extent of atherosclerotic vascular damage in low-risk individuals not being
considered for statin therapy is not justified due to low prognostic yield, and
the associated costs and radiation hazards when measuring CAC score,
particularly among low-risk women.29 Of note, CAC score is increased following
statin treatment; therefore, the CAC scores of statin-treated patients should be
interpreted with caution.

Recommendations for cardiovascular imaging for risk assessment of
atherosclerotic cardiovascular disease

 

 

CAC = coronary artery calcium; CT = computed tomography; CV = cardiovascular.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for cardiovascular imaging for risk assessment of
atherosclerotic cardiovascular disease

 

 

CAC = coronary artery calcium; CT = computed tomography; CV = cardiovascular.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

4.2.2 RISK-BASED INTERVENTION STRATEGIES

Table 5 presents suggested intervention strategies as a function of total CV
risk and LDL-C level. This graded approach is based on evidence from multiple
meta-analyses and individual randomized controlled trials (RCTs), which show a
consistent and graded reduction in ASCVD risk in response to reductions in TC
and LDL-C levels (see Recommendations for cardiovascular disease risk estimation
below).31–41 These data are consistent in showing that, since the relative risk
reduction is proportional to the absolute reduction in LDL-C and the absolute
reduction in LDL-C resulting from a particular drug regimen depends only on
baseline LDL-C, at any given level of baseline risk the higher the initial LDL-C
level the greater the absolute reduction in risk. Advice on individual drug
treatments is given in section 8.

Table 5

Intervention strategies as a function of total cardiovascular risk and untreated
low-density lipoprotein cholesterol levels

 

 

CV = cardiovascular; LDL-C = low-density lipoprotein cholesterol; SCORE =
Systematic Coronary Risk Estimation.

a

Class of recommendation.

b

Level of evidence.

Open in new tab
Table 5

Intervention strategies as a function of total cardiovascular risk and untreated
low-density lipoprotein cholesterol levels

 

 

CV = cardiovascular; LDL-C = low-density lipoprotein cholesterol; SCORE =
Systematic Coronary Risk Estimation.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for cardiovascular disease risk estimation

 

 

CKD = chronic kidney disease; CV= cardiovascular; CVD = cardiovascular disease;
DM = diabetes mellitus; FH = familial hypercholesterolaemia; LDL-C = low-density
lipoprotein cholesterol; SCORE = Systematic Coronary Risk Estimation.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for cardiovascular disease risk estimation

 

 

CKD = chronic kidney disease; CV= cardiovascular; CVD = cardiovascular disease;
DM = diabetes mellitus; FH = familial hypercholesterolaemia; LDL-C = low-density
lipoprotein cholesterol; SCORE = Systematic Coronary Risk Estimation.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


5 LIPIDS AND LIPOPROTEINS


5.1 BIOLOGICAL ROLE OF LIPIDS AND LIPOPROTEINS

Lipoproteins in plasma transport lipids to tissues for energy utilization, lipid
deposition, steroid hormone production, and bile acid formation. Lipoproteins
consist of esterified and unesterified cholesterol, TGs, and phospholipids and
protein components named apolipoproteins that act as structural components,
ligands for cellular receptor binding, and enzyme activators or inhibitors.

There are six major lipoproteins in blood: chylomicrons, very low-density
lipoprotein (VLDL), intermediate-density lipoprotein (IDL), LDL; Lp(a), and HDL
(Table 6 and Supplementary Figure 5).

Table 6

Physical and chemical characteristics of human plasma lipoproteins

. Density (g/mL) . Diameter (nm) . TGs (%) . Cholesteryl esters (%) . PLs (%)
. Cholesterol (%) . Apolipoproteins

--------------------------------------------------------------------------------

. Major . Others . Chylomicrons <0.95 80–100 90–95 2–4 2–6 1 ApoB-48 ApoA-I,
A-II, A-IV, A-V VLDL 0.95–1.006 30–80 50–65 8–14 12–16 4–7 ApoB-100 ApoA-I,
C-II, C-III, E,
A-V IDL 1.006–1.019 25–30 25–40 20–35 16–24 7–11 ApoB-100 ApoC-II, C-III,
E LDL 1.019–1.063 20–25 4–6 34–35 22–26 6–15 ApoB-100  HDL 1.063–1.210 8–13 7 10–20 55 5 ApoA-I ApoA-II,
C-III, E, M Lp(a) 1.006–1.125 25–30 4–8 35–46 17–24 6–9 Apo(a) ApoB-100 

. Density (g/mL) . Diameter (nm) . TGs (%) . Cholesteryl esters (%) . PLs (%)
. Cholesterol (%) . Apolipoproteins

--------------------------------------------------------------------------------

. Major . Others . Chylomicrons <0.95 80–100 90–95 2–4 2–6 1 ApoB-48 ApoA-I,
A-II, A-IV, A-V VLDL 0.95–1.006 30–80 50–65 8–14 12–16 4–7 ApoB-100 ApoA-I,
C-II, C-III, E,
A-V IDL 1.006–1.019 25–30 25–40 20–35 16–24 7–11 ApoB-100 ApoC-II, C-III,
E LDL 1.019–1.063 20–25 4–6 34–35 22–26 6–15 ApoB-100  HDL 1.063–1.210 8–13 7 10–20 55 5 ApoA-I ApoA-II,
C-III, E, M Lp(a) 1.006–1.125 25–30 4–8 35–46 17–24 6–9 Apo(a) ApoB-100 

Apo = apolipoprotein; HDL = high-density lipoprotein; IDL = intermediate-density
lipoprotein; LDL = low-density lipoprotein; Lp(a) = lipoprotein(a); PLs =
phospholipids; TGs = triglycerides; VLDL = very low-density lipoprotein.

Open in new tab
Table 6

Physical and chemical characteristics of human plasma lipoproteins

. Density (g/mL) . Diameter (nm) . TGs (%) . Cholesteryl esters (%) . PLs (%)
. Cholesterol (%) . Apolipoproteins

--------------------------------------------------------------------------------

. Major . Others . Chylomicrons <0.95 80–100 90–95 2–4 2–6 1 ApoB-48 ApoA-I,
A-II, A-IV, A-V VLDL 0.95–1.006 30–80 50–65 8–14 12–16 4–7 ApoB-100 ApoA-I,
C-II, C-III, E,
A-V IDL 1.006–1.019 25–30 25–40 20–35 16–24 7–11 ApoB-100 ApoC-II, C-III,
E LDL 1.019–1.063 20–25 4–6 34–35 22–26 6–15 ApoB-100  HDL 1.063–1.210 8–13 7 10–20 55 5 ApoA-I ApoA-II,
C-III, E, M Lp(a) 1.006–1.125 25–30 4–8 35–46 17–24 6–9 Apo(a) ApoB-100 

. Density (g/mL) . Diameter (nm) . TGs (%) . Cholesteryl esters (%) . PLs (%)
. Cholesterol (%) . Apolipoproteins

--------------------------------------------------------------------------------

. Major . Others . Chylomicrons <0.95 80–100 90–95 2–4 2–6 1 ApoB-48 ApoA-I,
A-II, A-IV, A-V VLDL 0.95–1.006 30–80 50–65 8–14 12–16 4–7 ApoB-100 ApoA-I,
C-II, C-III, E,
A-V IDL 1.006–1.019 25–30 25–40 20–35 16–24 7–11 ApoB-100 ApoC-II, C-III,
E LDL 1.019–1.063 20–25 4–6 34–35 22–26 6–15 ApoB-100  HDL 1.063–1.210 8–13 7 10–20 55 5 ApoA-I ApoA-II,
C-III, E, M Lp(a) 1.006–1.125 25–30 4–8 35–46 17–24 6–9 Apo(a) ApoB-100 

Apo = apolipoprotein; HDL = high-density lipoprotein; IDL = intermediate-density
lipoprotein; LDL = low-density lipoprotein; Lp(a) = lipoprotein(a); PLs =
phospholipids; TGs = triglycerides; VLDL = very low-density lipoprotein.

Open in new tab


5.2 ROLE OF LIPIDS AND LIPOPROTEINS IN THE PATHOPHYSIOLOGY OF ATHEROSCLEROSIS

All ApoB-containing lipoproteins <70 nm in diameter, including smaller TG-rich
lipoproteins and their remnant particles, can cross the endothelial barrier,
especially in the presence of endothelial dysfunction, where they can become
trapped after interaction with extracellular structures such as proteoglycans.42
ApoB-containing lipoproteins retained in the arterial wall provoke a complex
process that leads to lipid deposition and the initiation of an atheroma.43

Continued exposure to ApoB-containing lipoproteins leads to additional particles
being retained over time in the artery wall, and to the growth and progression
of atherosclerotic plaques. On average, people with higher concentrations of
plasma ApoB-containing lipoproteins will retain more particles and accumulate
lipids faster, resulting in more rapid growth and the progression of
atherosclerotic plaques.

Because atherosclerotic plaques grow over time as additional ApoB-containing
lipoprotein particles are retained, the size of the total atherosclerotic plaque
burden is likely to be determined by both the concentration of circulating LDL-C
and other ApoB-containing lipoproteins, and by the total duration of exposure to
these lipoproteins. Therefore, a person’s total atherosclerotic plaque burden is
likely to be proportional to the cumulative exposure to these lipoproteins.44

Eventually, the increase of the atherosclerotic plaque burden along with changes
in the composition of the plaque reaches a critical point at which disruption of
a plaque can result, with the formation of an overlying thrombus that acutely
obstructs blood flow resulting in unstable angina, myocardial infarction (MI),
or death. Therefore, the risk of experiencing an acute ASCVD event rises rapidly
as more ApoB-containing lipoproteins become retained and the atherosclerotic
plaque burden increases. This provides the rationale for encouraging a healthy
lifestyle to maintain low levels of ApoB-containing lipoproteins throughout life
to slow the progression of atherosclerosis; it also explains the motivation to
recommend treatment to lower LDL-C and other ApoB-containing lipoproteins, for
both the primary prevention of ASCVD and the secondary prevention of recurrent
CV events.44


5.3 EVIDENCE FOR THE CAUSAL EFFECTS OF LIPIDS AND LIPOPROTEINS ON THE RISK OF
ATHEROSCLEROTIC CARDIOVASCULAR DISEASE

5.3.1 LOW-DENSITY LIPOPROTEIN CHOLESTEROL AND RISK OF ATHEROSCLEROSIS

Plasma LDL-C is a measure of the cholesterol mass carried by LDL particles, by
far the most numerous of the ApoB-containing lipoproteins, and is an estimate of
the concentration of circulating LDL. Numerous epidemiological studies,
Mendelian randomization studies, and RCTs have consistently demonstrated a
log-linear relationship between the absolute changes in plasma LDL-C and the
risk of ASCVD.34,45–50 The remarkable consistency among these studies, in
addition to biological and experimental evidence, provides compelling evidence
that LDL-C is causally associated with the risk of ASCVD, and that lowering
LDL-C reduces the risk of ASCVD proportionally to the absolute achieved
reduction in LDL-C.2,51

Furthermore, Mendelian randomization studies have demonstrated that long-term
exposure to lower LDL-C levels is associated with a much lower risk of CV events
as compared with shorter-term exposure to lower LDL-C (as achieved, for example,
in randomized trials).48,52 These data provide strong support for the concept
that LDL particles have both a causal and cumulative effect on the risk of
ASCVD. Therefore, the effect of LDL-C on the risk of ASCVD appears to be
determined by both the absolute magnitude and the total duration of exposure to
LDL-C.2

The clinical benefit of lowering LDL-C is determined by the reduction in
circulating LDL particles as estimated by ApoB, which is usually mirrored by a
reduction of cholesterol carried by those particles.2,53 Therefore, the clinical
benefit of therapies that lower LDL-C by reducing LDL particle mass will be
proportional to the absolute reduction in LDL-C, because—on average—the
reduction in LDL-C and LDL particles will be concordant.34,50,54,55 In contrast,
the clinical benefit of therapies that lower LDL-C by a mechanism that may
dramatically modify their composition may not be proportional to the observed
absolute reduction in LDL-C, but instead would be expected to be proportional to
the absolute change in LDL particle concentration as measured by a reduction in
ApoB.2,53

5.3.2 TRIGLYCERIDE-RICH LIPOPROTEINS AND RISK OF ATHEROSCLEROSIS

TG-rich VLDL particles and their remnants carry most of the circulating TGs.
Therefore, the plasma TG concentration reflects the concentration of circulating
ApoB-containing TG-rich lipoproteins.

Elevated plasma TG levels are associated with an increasing risk of ASCVD, but
this association becomes null after adjusting for non-HDL-C, an estimate of the
total concentration of all ApoB-containing lipoproteins.45 Similarly, lowering
TG with fibrates reduces the risk of CV events by the same amount as
LDL-C-lowering therapies when measured per unit change of non-HDL-C,50
suggesting that the effect of plasma TGs on ASCVD is mediated by changes in the
concentration of TG-rich lipoproteins as estimated by non-HDL-C.

Mendelian randomization studies also suggest that the association between plasma
TGs and the risk of CHD may be causal; however, this evidence must be
interpreted with caution because nearly all variants associated with TGs are
also associated with HDL-C, LDL-C, or Lp(a).56–59 A recent Mendelian
randomization study demonstrated that TG-lowering lipoprotein lipase (LPL)
variants and LDL-C-lowering LDL receptor variants had the same effect on the
risk of ASCVD per unit change of ApoB, suggesting that all ApoB-containing
lipoproteins have the same effect on the risk of CHD.53 Together, these studies
strongly suggest that the causal effect of TG-rich lipoproteins and their
remnants on the risk of ASCVD is determined by the circulating concentration of
ApoB-containing particles, rather than by the TG content itself.

5.3.3 HIGH-DENSITY LIPOPROTEIN CHOLESTEROL AND RISK OF ATHEROSCLEROSIS

The inverse association between plasma HDL-C and the risk of ASCVD is among the
most consistent and reproducible associations in observational
epidemiology.45,60 In contrast, Mendelian randomization studies do not provide
compelling evidence that HDL-C is causally associated with the risk of
ASCVD.49,61,62 However, this evidence must be interpreted with caution because
most genetic variants associated with HDL-C are also associated with
directionally opposite changes in TGs, LDL-C, or both, thus making estimates of
the effect of HDL-C on the risk of ASCVD very difficult using the Mendelian
randomization study design. Furthermore, there is no evidence from randomized
trials that therapeutically increasing plasma HDL-C reduces the risk of CV
events.63–67 In the Effects of Dalcetrapib in Patients with a Recent Acute
Coronary Syndrome (dal-OUTCOMES) trial, treatment with the cholesteryl ester
transfer protein (CETP) inhibitor dalcetrapib increased HDL-C without any effect
on LDL-C or ApoB, but did not reduce the risk of major CV events.65 Similarly,
in the Assessment of Clinical Effects of Cholesteryl Ester Transfer Protein
Inhibition with Evacetrapib in Patients at a High-Risk for Vascular Outcomes
(ACCELERATE) and Randomized Evaluation of the Effects of Anacetrapib Through
Lipid Modification (REVEAL) trials, treatment with CETP inhibitors more than
doubled HDL-C levels, but did not appear to reduce the risk of ASCVD events
beyond that expected from the modest reductions in ApoB levels.2,63,64
Furthermore, several randomized trials have shown that directly infused HDL
mimetics increase plasma HDL-C concentrations, but do not reduce the progression
of atherosclerosis as measured by intravascular ultrasound.68,69

Therefore, there is currently no randomized trial or genetic evidence to suggest
that raising plasma HDL-C is likely to reduce the risk of ASCVD events. Whether
therapies that alter the function of HDL particles will reduce the risk of ASCVD
is unknown.

5.3.4 LIPOPROTEIN(A) AND RISK OF ATHEROSCLEROSIS

Lp(a) is an LDL particle with an Apo(a) moiety covalently bound to its ApoB
component.70 It is <70 nm in diameter and can freely flux across the endothelial
barrier, where it can become—similarly to LDL—retained within the arterial wall
and thus may increase the risk of ASCVD. Pro-atherogenic effects of Lp(a) have
also been attributed to pro-coagulant effects as Lp(a) has a similar structure
to plasminogen, and it has pro-inflammatory effects most likely related to the
oxidized phospholipid load carried by Lp(a).71

Higher plasma Lp(a) concentrations are associated with an increased risk of
ASCVD, but it appears to be a much weaker risk factor for most people than
LDL-C.72,73 In contrast, Mendelian randomization studies have consistently
demonstrated that lifelong exposure to higher Lp(a) levels is strongly and
causally associated with an increased risk of ASCVD.74,75 While randomized
trials evaluating therapies that lower Lp(a) by 20–30% (including niacin and
CETP inhibitors) have not provided evidence that lowering Lp(a) reduces the risk
of ASCVD beyond that which would be expected from the observed reduction in
ApoB-containing lipoproteins, recent data with PCSK9 inhibitors have suggested a
possible role for Lp(a) lowering in reducing CV risk.76

This conflicting evidence appears to have been reconciled by a recent Mendelian
randomization study that showed that the causal effect of Lp(a) on the risk of
ASCVD is proportional to the absolute change in plasma Lp(a) levels.
Importantly, this study also suggested that people with extremely high Lp(a)
levels >180 mg/dL (>430 nmol/L) may have an increased lifetime risk of ASCVD
similar to that of people with heterozygous FH (HeFH). Because about 90% of a
person’s Lp(a) level is inherited, extremely elevated Lp(a) may represent a new
inherited lipid disorder that is associated with extremely high lifetime risk of
ASCVD and is two-fold more prevalent than HeFH.77 However, this study77 and
another based on the Heart Protection Study 2-Treatment of HDL to Reduce the
Incidence of Vascular Events (HPS2-THRIVE) trial78 have shown that large
absolute changes in Lp(a) may be needed to produce a clinically meaningful
reduction in the risk of ASCVD events.


5.4 LABORATORY MEASUREMENT OF LIPIDS AND LIPOPROTEINS

Measurement of lipids and lipoproteins is used to estimate the risk of ASCVD and
guide therapeutic decision-making. Quantification of plasma lipids can be
performed on whole plasma and quantification of lipoproteins can be achieved by
measuring their protein component. Operationally, lipoproteins are classified
based on their hydrated density (see Table 6).

5.4.1 LIPOPROTEIN MEASUREMENT

Given the central causal role of ApoB-containing lipoproteins in the initiation
and progression of atherosclerosis, direct measurement of the circulating
concentration of atherogenic ApoB-containing lipoproteins to both estimate risk
and guide treatment decisions would be ideal. Because all ApoB-containing
lipoproteins—including VLDL, TG-rich remnant particles, and LDL—contain a single
ApoB molecule, quantitation of ApoB directly estimates the number of atherogenic
particles in plasma.

Standardized, automated, accurate, and inexpensive methods to measure ApoB are
available. Fasting is not required because even in the post-prandial state,
ApoB48-containing chylomicrons typically represent <1% of the total
concentration of circulating ApoB-containing lipoproteins. Furthermore, the
analytical performances of ApoB measurement methods are superior to the
measurement or calculation of LDL-C and non-HDL-C.79

5.4.2 LIPID MEASUREMENTS

In clinical practice, the concentration of plasma lipoproteins is not usually
measured directly but is instead estimated by measuring their cholesterol
content. TC in humans is distributed primarily among three major lipoprotein
classes: VLDL, LDL, and HDL. Smaller amounts of cholesterol are also contained
in two minor lipoprotein classes: IDL and Lp(a). A standard serum lipid profile
measures the concentration of TC and HDL-C, as well as TG. With these values,
the LDL-C concentration can be estimated.

Plasma LDL-C can be measured directly using enzymatic techniques or preparative
ultracentrifugation, but in clinical medicine it is most often calculated using
the Friedewald formula:



> LDL-C = TC − HDL-C − (TG/2.2) in mmol/L
> 
> or
> 
> LDL-C = TC − HDL-C − (TG/5) in mg/dL



Although convenient, the Friedewald calculated value of LDL-C has several
well-established limitations: (i) methodological errors may accumulate since the
formula necessitates three separate analyses of TC, TGs, and HDL-C; and (ii) a
constant cholesterol/TG ratio in VLDL is assumed. With high TG values (>4.5
mmol/L or >400 mg/dL) the formula cannot be used. This should especially be
considered in non-fasting samples.

To overcome the problems associated with calculated LDL-C, direct enzymatic
methods for the measurement of LDL-C have been developed. These methods are
commercially available as ready to use tools for automatic analysis. The
definition of LDL-C by the Friedewald equation and by direct measurement is the
same: non-HDL-C – VLDL-C, representing the sum of the cholesterol carried by the
biochemically defined LDL, IDL, and Lp(a) subfractions.

For the general population, calculated LDL-C and direct LDL-C show very strong
correlations.80–83 However, calculated LDL-C has been found to underestimate
LDL-C at concentrations of TG ≥2 mmol/L (177 mg/dL).81,82 Equally, at very low
levels of LDL-C, calculated LDL-C may be misleading, especially in the presence
of high TG.81,84–86 To avoid some of the problems with the Friedewald formula, a
number of modifications for the calculation of LDL-C have been suggested, but it
remains to be proved whether these modifications are superior to Friedewald’s
formula for the estimation of CV risk.81,85–87 It is important to note that
direct LDL-C measurements also have limitations, including systematic bias and
inaccuracy in patients with dyslipidaemia, especially for high TG levels.88–90

As an alternative calculated LDL-C, non-HDL-C can be calculated as TC – HDL-C
and is a measure of the TC carried by all atherogenic ApoB-containing
lipoproteins, including TG-rich particles in VLDL and their remnants.100

Several methods for the determination of Lp(a) are available. The complex
molecular structure of Lp(a) and the variation in size of Apo(a) has been a
challenge in the development of analytical methods for Lp(a). Available methods
are, to a varying degree, influenced by the Apo(a) isoform.91 Furthermore, the
concentration of Lp(a) is reported as either a molar concentration (nmol/L) or
as a mass (mg/dL) by the various assays, and conversion between molar and mass
concentrations has been found to be both size- and concentration-dependent.91–93
Therefore, standardization between assays is needed to establish a reliable and
reproducible method for the quantification of Lp(a) mass or particle number.92

5.4.3 FASTING OR NON-FASTING?

Traditionally, blood sampling for lipid analyses has been recommended in the
fasting state. Recent systematic studies comparing fasting and non-fasting
samples have suggested that the difference is small for most lipid
parameters.85,94–100 Non-fasting sampling has been used in large
population-based studies.100 In most studies, non-fasting samples display a
higher TG level of ∼0.3 mmol/L (27 mg/dL).100,101 On average, and for most
individuals, this increment will be of no clinical significance. Indeed, a
number of guidelines recommend non-fasting sampling.100,102,103

For general risk screening, non-fasting samples seem to have at least the same
prognostic value as fasting samples.104 The practical advantages of non-fasting
samples, including better patient acceptability, outweigh the potential
imprecision in some patients, although the determination of some key analytes,
such as fasting glucose, may be compromised. Furthermore, even if non-fasting
sampling can be used in most cases, in patients with metabolic syndrome (MetS),
DM, or hypertriglyceridaemia (HTG), calculated LDL-C should be interpreted with
caution.


5.5 RECOMMENDATIONS FOR MEASURING LIPIDS AND LIPOPROTEINS TO ESTIMATE RISK OF
ATHEROSCLEROTIC CARDIOVASCULAR DISEASE

Measurement of plasma TC is needed to calculate risk using SCORE, while the
inclusion of plasma HDL-C level can improve risk estimation using the online
SCORE calculator. Therefore, both TC and HDL-C should be measured to estimate a
person’s risk of ASCVD using SCORE, or one of the other risk calculators (almost
all of which also include measurements of TC and HDL-C).

Plasma LDL-C should be measured to estimate the risk of ASCVD that can be
modified with LDL-C-lowering therapies, and to identify whether markedly
elevated LDL-C levels are present that may suggest a lifetime high-risk of ASCVD
due to lifelong cumulative exposure to high levels of atherogenic lipoproteins,
such as in FH. Plasma LDL-C can be either calculated or measured directly.

Plasma TG should be assessed to identify people who may have a greater
modifiable risk of ASCVD than is reflected by LDL-C, due to the presence of an
increased concentration of atherogenic ApoB-containing TG-rich lipoproteins and
their remnants, and to identify people in whom calculated and directly measured
LDL-C may underestimate the risk of ASCVD by underestimating either the
concentration of circulating LDL particles or the cholesterol content carried by
those particles, such as those with very low levels of LDL. This may be
especially relevant in patients with DM or MetS.

In general, LDL-C, non-HDL-C, and ApoB concentrations are very highly
correlated. As a result, under most circumstances, they provide very similar
information about ASCVD risk.45,105–108 However, under certain
circumstances—including among people with elevated TG levels, DM, obesity, or
very low achieved LDL-C levels—the calculated or directly measured LDL-C level
may underestimate both the total concentration of cholesterol carried by LDL
and, more importantly, underestimate the total concentration of ApoB-containing
lipoproteins, thus underestimating the risk of ASCVD. In around 20% of patients
there may be discordance between measured LDL-C and ApoB levels.85,109

Considering the potential inaccuracy of LDL-C in dyslipidaemia, among patients
with DM or high TG levels, and in patients with very low LDL-C levels,
measurement of both ApoB and non-HDL-C is recommended as part of routine lipid
analysis for risk evaluation in patients with elevated plasma TGs. Because ApoB
provides an accurate estimate of the total concentration of atherogenic
particles under all circumstances, it is the preferred measurement to further
refine the estimate of ASCVD risk that is modifiable by lipid-lowering therapy.

Lp(a) has a similar structure to plasminogen and binds to the plasminogen
receptor, leading to increased thrombosis (pro-thrombotic factor). Measurement
of Lp(a) should be considered at least once in each person’s lifetime, if
available, to identify people who have inherited an extremely elevated level of
Lp(a) ≥180 mg/dL (≥430 nmol/L) and therefore have a very high lifetime risk of
ASCVD that is approximately equivalent to the risk associated with HeFH. In
addition, this strategy can identify people with less-extreme Lp(a) elevations
who may be at a higher risk of ASCVD, which is not reflected by the SCORE
system, or by other lipid or lipoprotein measurements. Measurement of Lp(a) has
been shown to provide clinically significant improved risk reclassification
under certain conditions, and therefore should be considered in patients who
have an estimated 10-year risk of ASCVD that is close to the threshold between
high and moderate risk.110–112

Recommendations for measuring lipids and lipoproteins to estimate the risk of
ASCVD are summarized below.

Recommendations for lipid analyses for cardiovascular disease risk estimation

 

 

Apo = apolipoprotein; ASCVD = atherosclerotic cardiovascular disease; CV =
cardiovascular; CVD = cardiovascular disease; DM = diabetes mellitus; HDL-C =
high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein
cholesterol; Lp(a) = lipoprotein(a); SCORE = Systematic Coronary Risk
Estimation; TC = total cholesterol; TG = triglyceride.

Open in new tab

Recommendations for lipid analyses for cardiovascular disease risk estimation

 

 

Apo = apolipoprotein; ASCVD = atherosclerotic cardiovascular disease; CV =
cardiovascular; CVD = cardiovascular disease; DM = diabetes mellitus; HDL-C =
high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein
cholesterol; Lp(a) = lipoprotein(a); SCORE = Systematic Coronary Risk
Estimation; TC = total cholesterol; TG = triglyceride.

Open in new tab


6 TREATMENT TARGETS AND GOALS

In previous EAS/ESC Guidelines for the management of dyslipidaemias1,113 and
other major guidelines on the treatment of blood cholesterol to reduce
atherosclerotic CV risk in adults,40,114 the importance of LDL-C lowering to
prevent ASCVD is strongly emphasized. The European Task Force felt that limiting
the current knowledge on CV prevention only to results from RCTs reduces the
exploitation of the potential that is available for the prevention of ASCVD. It
is the concordance of the conclusions from many different approaches (from basic
science, clinical observations, genetics, epidemiology, RCTs, etc.) that
contributes to the understanding of the causes of ASCVD and to the potential of
prevention. The Task Force is aware of the limitations of some of the sources of
evidence and accepts that RCTs have not examined different LDL-C goals
systematically, but felt that it was appropriate to look at the totality of the
evidence. Particular consideration was given to results from meta-analyses
confirming the dose-dependent reduction in ASCVD with LDL-C-lowering agents; the
greater the absolute LDL-C reduction, the greater the CV risk
reduction.35,36,50,115 The benefits related to LDL-C reduction are not specific
for statin therapy.33 No level of LDL-C below which benefit ceases or harm
occurs has been defined.

There is considerable individual variability in the LDL-C response to dietary
and drug treatments,31 which is traditionally taken to support a tailored
approach to management. Total CV risk reduction should be individualized, and
this can be more specific if goals are defined. The use of goals can also aid
patient–doctor communication. It is judged that a goal approach may facilitate
adherence to treatment, although this consensus opinion has not been fully
tested. For all these reasons, the European Task Force retains a goal approach
to lipid management and treatment goals are tailored to the total CV risk level.
There is also evidence suggesting that lowering of LDL-C beyond the goals that
were set in the previous EAS/ESC Guidelines is associated with fewer ASCVD
events.34,116,117 Therefore, it seems appropriate to reduce LDL-C to as low a
level as possible, at least in patients at very high CV risk, and for this
reason a minimum 50% reduction is suggested for LDL reduction, together with
reaching the tailored goal.

The lipid goals are part of a comprehensive CV risk reduction strategy and are
summarized in Table 7. The rationales for the non-lipid targets are given in the
2016 ESC Joint Prevention Guidelines.10

Table 7

Treatment targets and goals for cardiovascular disease prevention

Smoking No exposure to tobacco in any form. Diet Healthy diet low in saturated
fat with a focus on wholegrain products, vegetables, fruit, and fish. Physical
activity 3.5–7 h moderately vigorous physical activity per week or 30–60 min
most days. Body weight BMI 20–25 kg/m2, and waist circumference <94 cm (men) and
<80 cm (women). Blood pressure <140/90 mmHg.a LDL-C 

 * Very-high risk in primary or secondary prevention:

 * A therapeutic regimen that achieves ≥50% LDL-C reduction from baselineb and
   an LDL-C goal of <1.4 mmol/L (<55 mg/dL).

 * No current statin use: this is likely to require high-intensity LDL-lowering
   therapy.

 * Current LDL-lowering treatment: an increased treatment intensity is required.

 * High risk: A therapeutic regimen that achieves ≥50% LDL-C reduction from
   baselineb and an LDL-C goal of <1.8 mmol/L (<70 mg/dL).

 * Moderate risk:

 * A goal of <2.6 mmol/L (<100 mg/dL).

 * Low risk:

 * A goal of <3.0 mmol/L (<116 mg/dL).

 Non-HDL-C Non-HDL-C secondary goals are <2.2, 2.6, and 3.4 mmol/L (<85, 100,
and 130 mg/dL) for very-high-, high-, and moderate-risk people,
respectively. ApoB ApoB secondary goals are <65, 80, and 100 mg/dL for
very-high-, high-, and moderate-risk people, respectively. Triglycerides No
goal, but <1.7 mmol/L (<150 mg/dL) indicates lower risk and higher levels
indicate a need to look for other risk factors. Diabetes HbA1c: <7% (<53
mmol/mol). 

Smoking No exposure to tobacco in any form. Diet Healthy diet low in saturated
fat with a focus on wholegrain products, vegetables, fruit, and fish. Physical
activity 3.5–7 h moderately vigorous physical activity per week or 30–60 min
most days. Body weight BMI 20–25 kg/m2, and waist circumference <94 cm (men) and
<80 cm (women). Blood pressure <140/90 mmHg.a LDL-C 

 * Very-high risk in primary or secondary prevention:

 * A therapeutic regimen that achieves ≥50% LDL-C reduction from baselineb and
   an LDL-C goal of <1.4 mmol/L (<55 mg/dL).

 * No current statin use: this is likely to require high-intensity LDL-lowering
   therapy.

 * Current LDL-lowering treatment: an increased treatment intensity is required.

 * High risk: A therapeutic regimen that achieves ≥50% LDL-C reduction from
   baselineb and an LDL-C goal of <1.8 mmol/L (<70 mg/dL).

 * Moderate risk:

 * A goal of <2.6 mmol/L (<100 mg/dL).

 * Low risk:

 * A goal of <3.0 mmol/L (<116 mg/dL).

 Non-HDL-C Non-HDL-C secondary goals are <2.2, 2.6, and 3.4 mmol/L (<85, 100,
and 130 mg/dL) for very-high-, high-, and moderate-risk people,
respectively. ApoB ApoB secondary goals are <65, 80, and 100 mg/dL for
very-high-, high-, and moderate-risk people, respectively. Triglycerides No
goal, but <1.7 mmol/L (<150 mg/dL) indicates lower risk and higher levels
indicate a need to look for other risk factors. Diabetes HbA1c: <7% (<53
mmol/mol). 

Apo = apolipoprotein; BMI = body mass index; HbA1c = glycated haemoglobin; HDL-C
= high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein
cholesterol.

a

Lower treatment targets are recommended for most treated hypertensive patients,
provided that the treatment is well tolerated.118

b

The term ‘baseline’ refers to the LDL-C level in a person not taking any
lipid-lowering medication, or to the extrapolated baseline value for those who
are on current treatment.

Open in new tab
Table 7

Treatment targets and goals for cardiovascular disease prevention

Smoking No exposure to tobacco in any form. Diet Healthy diet low in saturated
fat with a focus on wholegrain products, vegetables, fruit, and fish. Physical
activity 3.5–7 h moderately vigorous physical activity per week or 30–60 min
most days. Body weight BMI 20–25 kg/m2, and waist circumference <94 cm (men) and
<80 cm (women). Blood pressure <140/90 mmHg.a LDL-C 

 * Very-high risk in primary or secondary prevention:

 * A therapeutic regimen that achieves ≥50% LDL-C reduction from baselineb and
   an LDL-C goal of <1.4 mmol/L (<55 mg/dL).

 * No current statin use: this is likely to require high-intensity LDL-lowering
   therapy.

 * Current LDL-lowering treatment: an increased treatment intensity is required.

 * High risk: A therapeutic regimen that achieves ≥50% LDL-C reduction from
   baselineb and an LDL-C goal of <1.8 mmol/L (<70 mg/dL).

 * Moderate risk:

 * A goal of <2.6 mmol/L (<100 mg/dL).

 * Low risk:

 * A goal of <3.0 mmol/L (<116 mg/dL).

 Non-HDL-C Non-HDL-C secondary goals are <2.2, 2.6, and 3.4 mmol/L (<85, 100,
and 130 mg/dL) for very-high-, high-, and moderate-risk people,
respectively. ApoB ApoB secondary goals are <65, 80, and 100 mg/dL for
very-high-, high-, and moderate-risk people, respectively. Triglycerides No
goal, but <1.7 mmol/L (<150 mg/dL) indicates lower risk and higher levels
indicate a need to look for other risk factors. Diabetes HbA1c: <7% (<53
mmol/mol). 

Smoking No exposure to tobacco in any form. Diet Healthy diet low in saturated
fat with a focus on wholegrain products, vegetables, fruit, and fish. Physical
activity 3.5–7 h moderately vigorous physical activity per week or 30–60 min
most days. Body weight BMI 20–25 kg/m2, and waist circumference <94 cm (men) and
<80 cm (women). Blood pressure <140/90 mmHg.a LDL-C 

 * Very-high risk in primary or secondary prevention:

 * A therapeutic regimen that achieves ≥50% LDL-C reduction from baselineb and
   an LDL-C goal of <1.4 mmol/L (<55 mg/dL).

 * No current statin use: this is likely to require high-intensity LDL-lowering
   therapy.

 * Current LDL-lowering treatment: an increased treatment intensity is required.

 * High risk: A therapeutic regimen that achieves ≥50% LDL-C reduction from
   baselineb and an LDL-C goal of <1.8 mmol/L (<70 mg/dL).

 * Moderate risk:

 * A goal of <2.6 mmol/L (<100 mg/dL).

 * Low risk:

 * A goal of <3.0 mmol/L (<116 mg/dL).

 Non-HDL-C Non-HDL-C secondary goals are <2.2, 2.6, and 3.4 mmol/L (<85, 100,
and 130 mg/dL) for very-high-, high-, and moderate-risk people,
respectively. ApoB ApoB secondary goals are <65, 80, and 100 mg/dL for
very-high-, high-, and moderate-risk people, respectively. Triglycerides No
goal, but <1.7 mmol/L (<150 mg/dL) indicates lower risk and higher levels
indicate a need to look for other risk factors. Diabetes HbA1c: <7% (<53
mmol/mol). 

Apo = apolipoprotein; BMI = body mass index; HbA1c = glycated haemoglobin; HDL-C
= high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein
cholesterol.

a

Lower treatment targets are recommended for most treated hypertensive patients,
provided that the treatment is well tolerated.118

b

The term ‘baseline’ refers to the LDL-C level in a person not taking any
lipid-lowering medication, or to the extrapolated baseline value for those who
are on current treatment.

Open in new tab

The targeted approach to lipid management is primarily aimed at reducing
atherosclerotic risk by substantially lowering LDL-C to levels that have been
achieved in recent large-scale trials of PCSK-9 inhibitors. Therefore, for
patients at very high CV risk, whether in secondary prevention or (rarely) in
primary prevention, LDL-C reduction of ≥50% from baseline and an LDL-C goal of
<1.4 mmol/L (<55 mg/dL) are recommended. For patients with ASCVD who experience
a second vascular event within 2 years (not necessarily of the same type as the
first event) while taking maximally tolerated statin-based therapy, an LDL-C
goal <1.0 mmol/L (<40 mg/dL) may be considered.119,120 For people at high CV
risk, an LDL-C reduction of ≥50% from baseline and an LDL-C goal <1.8 mmol/L
(<70 mg/dL) are recommended. In patients at moderate CV risk, an LDL-C goal <2.6
mmol/L (<100 mg/dL) should be considered, while for low-risk individuals a goal
of <3.0 mmol/L (<116 mg/dL) may be considered (see Recommendations for treatment
goals for low-density lipoprotein cholesterol below and Supplementary Table 2).

Recommendations for treatment goals for low-density lipoprotein cholesterol

 

 

ASCVD = atherosclerotic cardiovascular disease; FH = familial
hypercholesterolaemia; LDL-C = low-density lipoprotein cholesterol.

a

Class of recommendation.

b

Level of evidence.

c

For definitions see Table 4.

d

The term ‘baseline’ refers to the LDL-C level in a person not taking any
LDL-C-lowering medication. In people who are taking LDL-C-lowering
medication(s), the projected baseline (untreated) LDL-C levels should be
estimated, based on the average LDL-C-lowering efficacy of the given medication
or combination of medications.

Open in new tab

Recommendations for treatment goals for low-density lipoprotein cholesterol

 

 

ASCVD = atherosclerotic cardiovascular disease; FH = familial
hypercholesterolaemia; LDL-C = low-density lipoprotein cholesterol.

a

Class of recommendation.

b

Level of evidence.

c

For definitions see Table 4.

d

The term ‘baseline’ refers to the LDL-C level in a person not taking any
LDL-C-lowering medication. In people who are taking LDL-C-lowering
medication(s), the projected baseline (untreated) LDL-C levels should be
estimated, based on the average LDL-C-lowering efficacy of the given medication
or combination of medications.

Open in new tab

Secondary goals have also been defined by inference for non-HDL-C and for ApoB;
they receive a moderate grading, as they have not been extensively studied in
RCTs. The specific goal for non-HDL-C should be 0.8 mmol/L (30 mg/dL) higher
than the corresponding LDL-C goal; the adjustment of lipid-lowering therapy in
accordance with these secondary goals may be considered in patients at very high
CV risk after achievement of an LDL-C goal, although the clinical advantages of
this approach with respect to outcomes remain to be addressed. When secondary
targets are used the recommendations are: (i) non-HDL-C <2.2 mmol/L (<85 mg/dL),
<2.6 mmol/L (<100 mg/dL), and <3.4 mmol/L (<130 mg/dL) in people at very high,
high, and moderate CV risk, respectively;121–123 and (ii) ApoB <65 mg/dL, <80
mg/dL, and <100 mg/dL in very-high, high, and moderate total CV risk,
respectively.121,123,124

To date, no specific goals for HDL-C or TG levels have been determined in
clinical trials, although increases in HDL-C predict atherosclerosis regression,
and low HDL-C is associated with excess events and mortality in coronary artery
disease (CAD) patients, even at low LDL levels. Clinicians should use clinical
judgment when considering further treatment intensification in patients at high
or very high total CV risk.


7 LIFESTYLE MODIFICATIONS TO IMPROVE THE PLASMA LIPID PROFILE

The pivotal role of nutrition in the prevention of ASCVD has been extensively
reviewed.125–129 Dietary factors influence the development of CVD either
directly or through their action on traditional risk factors, such as plasma
lipids, BP, or glucose levels.

Convincing evidence of the causal association between diet and ASCVD risk is,
nevertheless, available indirectly from randomized ‘metabolic ward’ studies
showing that high saturated fat intake causes increased LDL-C concentrations,
and from cohort studies, genetic epidemiological studies, and randomized trials
showing that higher LDL-C levels cause ASCVD.

The lack of concordance between studies is due both to methodological problems
(particularly inadequate sample sizes or short study durations) and the
difficulties of evaluating the impact of a single dietary factor independently
of any other changes in the diet.130 In fact, as foods are mixtures of different
nutrients and other components, it is not appropriate to attribute the health
effects of a food to only one of its components. Moreover, if energy intake must
be kept constant, eating less of one macronutrient implies necessarily eating
more of others. The quality of the replacement (for instance, unsaturated fat
vs. highly refined grains) can influence the effect observed, significantly
modifying the impact on health of the nutrient replaced. These limitations
suggest caution in interpreting the results of RCTs or even meta-analyses of
RCTs in relation to the effect of a single dietary change on ASCVD.130

To overcome, at least in part, these problems, in recent years nutrition
research has focused on the relationship between ASCVD on the one hand, and
foods and dietary patterns—rather than single nutrients—on the other. Consistent
evidence from epidemiological studies indicates that higher consumption of
fruit, non-starchy vegetables, nuts, legumes, fish, vegetable oils, yoghurt, and
wholegrains, along with a lower intake of red and processed meats, foods higher
in refined carbohydrates, and salt, is associated with a lower incidence of CV
events.131 Moreover, it indicates that the replacement of animal fats, including
dairy fat, with vegetable sources of fats and polyunsaturated fatty acids
(PUFAs) may decrease the risk of CVD.132

Dietary patterns that have been more extensively evaluated are the Dietary
Approaches to Stop Hypertension (DASH) diet—particularly in relation to BP
control—and the Mediterranean diet; both have proved to be effective in reducing
CV risk factors and, possibly, to contribute to ASCVD prevention.133 The most
relevant difference between the Mediterranean and the DASH diet is the emphasis
of the former on extra-virgin olive oil. The Mediterranean diet is associated
with a reduced incidence of CV and other non-communicable diseases in
epidemiological studies,134,135 and has been proved in RCTs to be effective in
reducing CV events in primary and secondary prevention.136 In particular, the
Prevención con Dieta Mediterránea (PREDIMED) trial indicated that participants
allocated to a Mediterranean-type diet, supplemented with extra-virgin olive oil
or nuts, had a significantly lower (around 30%) incidence of major CV events
compared with those who were on a low-fat diet.137

In summary, despite the results of PREDIMED and a few other intervention studies
with ASCVD endpoints that support a healthy lifestyle for ASCVD prevention, RCTs
cannot represent the sole grounds on which dietary recommendations should rely.
They also need to be based on the combination of large observational cohort
studies and relatively short-term randomized trials having intermediate risk
factors (such as blood lipids) as outcomes.

Table 8 summarizes the currently available evidence on the influences of
lifestyle changes and functional foods on lipoproteins, indicating the
magnitudes of the effects and the levels of evidence in relation to the impacts
on the specific lipoprotein class; for the reasons outlined above, the levels of
evidence are not based on RCTs with ASCVD endpoints. Moreover, within the
Guidelines on the management of dyslipidaemias, information on the potential to
improve plasma lipoprotein profiles by dietary means is clinically relevant,
even in the absence of a clear demonstration of CV benefits.

Table 8

Impact of specific lifestyle changes on lipid levels

 

 

The magnitude of the effect (+++ = >10%, ++ = 5–10%, + = <5%) and the level of
evidence refer to the impact of each dietary modification on plasma levels of a
specific lipoprotein class.

HDL-C = high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein
cholesterol; TC = total cholesterol; TG = triglyceride.

Open in new tab
Table 8

Impact of specific lifestyle changes on lipid levels

 

 

The magnitude of the effect (+++ = >10%, ++ = 5–10%, + = <5%) and the level of
evidence refer to the impact of each dietary modification on plasma levels of a
specific lipoprotein class.

HDL-C = high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein
cholesterol; TC = total cholesterol; TG = triglyceride.

Open in new tab


7.1 INFLUENCE OF LIFESTYLE ON TOTAL CHOLESTEROL AND LOW-DENSITY LIPOPROTEIN
CHOLESTEROL LEVELS

Saturated fatty acids (SFAs) are the dietary factor with the greatest impact on
LDL-C levels (0.02–0.04 mmol/L or 0.8–1.6 mg/dL of LDL-C increase for every
additional 1% energy coming from saturated fat).164 Quantitatively, dietary
trans fatty acids have a similar elevating effect on LDL-C to that of SFAs;
however, while SFAs increase HDL-C levels, trans fats decrease them.137 Trans
unsaturated fatty acids can be found in limited amounts (usually <5% of total
fat) in dairy products and in meats from ruminants. ‘Partially hydrogenated
fatty acids’ of industrial origin represent the major source of trans fatty
acids in the diet; the average consumption of trans fatty acids ranges from
0.2–6.5% of the total energy intake in different populations.165 Unsaturated
fat-rich oils from safflower, sunflower, rapeseed, flaxseed, corn, olives, or
soybean were shown to reduce LDL-C levels (−0.42 to −0.20 mmol/L) when used in
substitution of SFA-rich foods like butter or lard.166 The effects of
carbohydrate consumption on LDL-C are described in section 7.4.3.

Body weight reduction also influences TC and LDL-C levels, but the magnitude of
the effect is small: in obese people, a decrease in LDL-C concentration of 0.2
mmol/L (8 mg/dL) is observed for every 10 kg of weight loss.147,167 The
reduction of LDL-C levels induced by regular physical exercise is even
smaller.151,168 The benefits of weight reduction and physical exercise on the CV
risk profile likely impact on other risk factors, especially hypertension and
diabetes.

Table 9 summarizes the possible choices of foods to lower TC and LDL-C levels.
Given the cultural diversity of the European populations, they should be
translated into practical behaviours, considering local habits and
socio-economic factors.

Table 9

Food choices to lower low-density lipoprotein cholesterol and improve the
overall lipoprotein profile

. To be preferred . To be used in moderation . To be chosen occasionally in
limited amounts . Cereals Wholegrains Refined bread, rice, and pasta, biscuits,
corn flakes Pastries, muffins, pies, croissants Vegetables Raw and cooked
vegetables Potatoes Vegetables prepared in butter or cream Legumes Lentils,
beans, fava beans, peas, chickpeas, soybean   Fruit Fresh or frozen fruit Dried
fruit, jelly, jam, canned fruit, sorbets, ice lollies/popsicles, fruit
juice  Sweets and sweeteners Non-caloric sweeteners Sucrose, honey, chocolate,
sweets/candies Cakes, ice creams, fructose, soft drinks Meat and fish Lean and
oily fish, poultry without skin Lean cuts of beef, lamb, pork, and veal,
seafood, shellfish Sausages, salami, bacon, spare ribs, hot dogs, organ
meats Dairy food and eggs Skimmed milk and yoghurt Low-fat milk, low-fat cheese
and other milk products, eggs Regular cheese, cream, whole milk and
yoghurt Cooking fat and dressings Vinegar, mustard, fat-free dressings Olive
oil, non-tropical vegetable oils, soft margarines, salad dressing, mayonnaise,
ketchup Trans fats and hard margarines (better to avoid them), palm and coconut
oils, butter, lard, bacon fat Nuts/seeds  All, unsalted (except
coconut) Coconut Cooking procedures Grilling, boiling, steaming Stir-frying,
roasting Frying 

. To be preferred . To be used in moderation . To be chosen occasionally in
limited amounts . Cereals Wholegrains Refined bread, rice, and pasta, biscuits,
corn flakes Pastries, muffins, pies, croissants Vegetables Raw and cooked
vegetables Potatoes Vegetables prepared in butter or cream Legumes Lentils,
beans, fava beans, peas, chickpeas, soybean   Fruit Fresh or frozen fruit Dried
fruit, jelly, jam, canned fruit, sorbets, ice lollies/popsicles, fruit
juice  Sweets and sweeteners Non-caloric sweeteners Sucrose, honey, chocolate,
sweets/candies Cakes, ice creams, fructose, soft drinks Meat and fish Lean and
oily fish, poultry without skin Lean cuts of beef, lamb, pork, and veal,
seafood, shellfish Sausages, salami, bacon, spare ribs, hot dogs, organ
meats Dairy food and eggs Skimmed milk and yoghurt Low-fat milk, low-fat cheese
and other milk products, eggs Regular cheese, cream, whole milk and
yoghurt Cooking fat and dressings Vinegar, mustard, fat-free dressings Olive
oil, non-tropical vegetable oils, soft margarines, salad dressing, mayonnaise,
ketchup Trans fats and hard margarines (better to avoid them), palm and coconut
oils, butter, lard, bacon fat Nuts/seeds  All, unsalted (except
coconut) Coconut Cooking procedures Grilling, boiling, steaming Stir-frying,
roasting Frying 

Open in new tab
Table 9

Food choices to lower low-density lipoprotein cholesterol and improve the
overall lipoprotein profile

. To be preferred . To be used in moderation . To be chosen occasionally in
limited amounts . Cereals Wholegrains Refined bread, rice, and pasta, biscuits,
corn flakes Pastries, muffins, pies, croissants Vegetables Raw and cooked
vegetables Potatoes Vegetables prepared in butter or cream Legumes Lentils,
beans, fava beans, peas, chickpeas, soybean   Fruit Fresh or frozen fruit Dried
fruit, jelly, jam, canned fruit, sorbets, ice lollies/popsicles, fruit
juice  Sweets and sweeteners Non-caloric sweeteners Sucrose, honey, chocolate,
sweets/candies Cakes, ice creams, fructose, soft drinks Meat and fish Lean and
oily fish, poultry without skin Lean cuts of beef, lamb, pork, and veal,
seafood, shellfish Sausages, salami, bacon, spare ribs, hot dogs, organ
meats Dairy food and eggs Skimmed milk and yoghurt Low-fat milk, low-fat cheese
and other milk products, eggs Regular cheese, cream, whole milk and
yoghurt Cooking fat and dressings Vinegar, mustard, fat-free dressings Olive
oil, non-tropical vegetable oils, soft margarines, salad dressing, mayonnaise,
ketchup Trans fats and hard margarines (better to avoid them), palm and coconut
oils, butter, lard, bacon fat Nuts/seeds  All, unsalted (except
coconut) Coconut Cooking procedures Grilling, boiling, steaming Stir-frying,
roasting Frying 

. To be preferred . To be used in moderation . To be chosen occasionally in
limited amounts . Cereals Wholegrains Refined bread, rice, and pasta, biscuits,
corn flakes Pastries, muffins, pies, croissants Vegetables Raw and cooked
vegetables Potatoes Vegetables prepared in butter or cream Legumes Lentils,
beans, fava beans, peas, chickpeas, soybean   Fruit Fresh or frozen fruit Dried
fruit, jelly, jam, canned fruit, sorbets, ice lollies/popsicles, fruit
juice  Sweets and sweeteners Non-caloric sweeteners Sucrose, honey, chocolate,
sweets/candies Cakes, ice creams, fructose, soft drinks Meat and fish Lean and
oily fish, poultry without skin Lean cuts of beef, lamb, pork, and veal,
seafood, shellfish Sausages, salami, bacon, spare ribs, hot dogs, organ
meats Dairy food and eggs Skimmed milk and yoghurt Low-fat milk, low-fat cheese
and other milk products, eggs Regular cheese, cream, whole milk and
yoghurt Cooking fat and dressings Vinegar, mustard, fat-free dressings Olive
oil, non-tropical vegetable oils, soft margarines, salad dressing, mayonnaise,
ketchup Trans fats and hard margarines (better to avoid them), palm and coconut
oils, butter, lard, bacon fat Nuts/seeds  All, unsalted (except
coconut) Coconut Cooking procedures Grilling, boiling, steaming Stir-frying,
roasting Frying 

Open in new tab


7.2 INFLUENCE OF LIFESTYLE ON TRIGLYCERIDE LEVELS

Weight reduction improves insulin sensitivity and decreases TG levels. Regular
physical exercise reduces plasma TG levels over and above the effect of weight
reduction.151,168,169 Alcohol intake has a major impact on TG levels,
particularly in individuals with HTG.153,170 The detrimental effects of a
high-carbohydrate diet on TGs occur mainly when refined carbohydrate-rich foods
are consumed, while they are much less prominent if the diet is based largely on
fibre-rich, low-glycaemic index foods. This applies particularly to people with
DM or MetS.171,172

Habitual consumption of significant amounts (>10% energy) of dietary fructose
contributes to TG elevation, particularly in people with HTG or abdominal
obesity. These effects are dose-dependent; with a habitual fructose consumption
between 15–20% of total energy intake, plasma TG increases by as much as 30–40%.
Sucrose, a disaccharide containing glucose and fructose, represents an important
source of fructose in the diet.159,173,174


7.3 INFLUENCE OF LIFESTYLE ON HIGH-DENSITY LIPOPROTEIN CHOLESTEROL LEVELS

Weight reduction increases HDL-C levels; a 0.01 mmol/L (0.4 mg/dL) increase is
observed for every kilogram decrease in body weight when weight reduction has
stabilized. Aerobic physical activity, such as 25–30 km of brisk walking per
week (or any equivalent activity), may increase HDL-C levels by 0.08–0.15 mmol/L
(3.1–6 mg/dL).169 Smoking cessation may also contribute to HDL-C elevation,
provided that weight gain is prevented.163


7.4 LIFESTYLE RECOMMENDATIONS TO IMPROVE THE PLASMA LIPID PROFILE

LDL-C lowering represents the primary target for reducing CV risk and therefore
deserves special emphasis in the evaluation of lifestyle measures. The diet
recommended to the general population, and particularly to people at increased
CV risk, may also be able to modify plasma TG and HDL-C levels (Table 9). This
section focuses on dietary and other lifestyle factors that may be implemented
to improve the overall lipoprotein profile.

7.4.1 BODY WEIGHT AND PHYSICAL ACTIVITY

Since overweight, obesity, and—in particular—abdominal adiposity often
contribute to dyslipidaemia, caloric intake should be reduced and energy
expenditure increased in those with excessive weight and/or abdominal adiposity.

In the case of excess weight, body weight reduction, even if modest (5–10% of
basal body weight), improves lipid abnormalities and favourably affects the
other CV risk factors often present in dyslipidaemic individuals.148 While the
beneficial effects of weight reduction on metabolic and surrogate markers have
been demonstrated, the benefits of weight loss on mortality and CV outcome are
less clear.175

Weight reduction can be achieved by decreasing the consumption of energy-dense
foods, inducing a caloric deficit of 300–500 kcal/day. The intervention should
combine diet and exercise; this approach also leads to the greatest improvement
in physical performance and quality of life, and mitigates reductions in muscle
and bone mass, particularly in older people.176 It is always appropriate to
advise people with dyslipidaemia to engage in regular physical exercise of
moderate intensity for ≥30 min/day, even if they are not overweight.168

7.4.2 DIETARY FAT

Avoiding any consumption of trans fat is a key measure of the dietary prevention
of CVD. The trans fatty acids produced in the partial hydrogenation of vegetable
oils account for 80% of total intake. Thanks to efforts made in different parts
of the world, the intake of trans fatty acids has decreased substantially over
the past 10–15 years.

As for saturated fat, its consumption should be <10% of the total caloric intake
and should be further reduced (<7% of energy) in the presence of
hypercholesterolaemia. For most individuals, a wide range of total fat intakes
is acceptable, and will depend upon individual preferences and characteristics.
However, fat intakes >35–40% of calories are generally associated with increased
intakes of both saturated fat and calories. Conversely, low intakes of fats and
oils increase the risk of inadequate intakes of vitamin E and of essential fatty
acids, and may contribute to a reduction of HDL-C.164

Fat intake should predominantly come from sources of monounsaturated fatty
acids, including both n-6 and n-3 PUFAs. Not enough data are available to make a
recommendation regarding the optimal n-3:n-6 fatty acid ratio.177,178 The
cholesterol intake in the diet should be reduced (<300 mg/day), particularly in
people with high plasma cholesterol levels.

7.4.3 DIETARY CARBOHYDRATE AND FIBRE

Dietary carbohydrate has a ‘neutral’ effect on LDL-C, although excessive
consumption is represented by untoward effects on plasma TGs and HDL-C
levels.164 Dietary fibre (particularly of the soluble type)—which is present in
legumes, fruits, vegetables, and wholegrain cereals (e.g. oats and barley)—has a
hypocholesterolaemic effect and represents a good dietary substitute for
saturated fat to maximize the effects of the diet on LDL-C levels, and to
minimize the untoward effects of a high-carbohydrate diet on other
lipoproteins.140,179

Carbohydrate intake should range between 45–55% of total energy intake, since
both higher and lower percentages of carbohydrate diets are associated with
increased mortality.180,181 A fat-modified diet that provides 25–40 g per day of
total dietary fibre, including ≥7–13 g of soluble fibre, is well tolerated,
effective, and recommended for plasma lipid control; conversely, there is no
justification for the recommendation of very low-carbohydrate diets.182

Intake of added sugar should not exceed 10% of total energy (in addition to the
amount present in natural foods such as fruits and dairy products); more
restrictive advice concerning sugars may be useful for those needing to lose
weight or with high plasma TG values, MetS, or DM. Soft drinks should be used
with moderation by the general population, and should be drastically limited in
those individuals with elevated TG values or visceral adiposity.158,159,174 The
Prospective Urban Rural Epidemiology (PURE) study was a large, epidemiological
cohort study of 135 335 individuals enrolled in 18 countries with food frequency
questionnaires recorded. Total fat and types of fat were not associated with
CVD, MI, or CVD mortality, whereas saturated fat had an inverse association with
stroke.181 However, a meta-analysis of epidemiological studies including the
PURE study showed a U-shaped relationship between carbohydrate intake and
mortality: diets associated with the highest mortality rate had carbohydrate
intakes >70% and <40% of energy, with minimal risk observed when carbohydrate
intake was between 45–55% of total energy intake.180

7.4.4 ALCOHOL

Moderate alcohol consumption [≤10 g/day (1 unit) for men and women] is
acceptable for those who drink alcoholic beverages, if TG levels are not
elevated.183,184

7.4.5 SMOKING

Smoking cessation has clear benefits regarding overall CV risk, and specifically
on HDL-C levels.163


7.5 DIETARY SUPPLEMENTS AND FUNCTIONAL FOODS FOR THE TREATMENT OF DYSLIPIDAEMIAS

Nutritional evaluation of functional foods includes not only the search for
clinical evidence of beneficial effects relevant to improved health or the
reduction of disease risk, but also the demonstration of good tolerability.
Overall, the available evidence on functional foods so far identified in this
field is incomplete; the major gap is an absence of diet-based intervention
trials of enough duration to be relevant for the natural history of
dyslipidaemia and CVD.

7.5.1 PHYTOSTEROLS

The principal phytosterols are sitosterol, campesterol, and stigmasterol; they
occur naturally in vegetable oils and in smaller amounts in vegetables, fresh
fruits, nuts, grains, and legumes. The dietary intake of plant sterols ranges
between an average of 250 mg/day in Northern Europe to ∼500 mg/day in
Mediterranean countries. Phytosterols compete with cholesterol for intestinal
absorption, thereby modulating TC levels.

Daily consumption of 2 g of phytosterols can effectively lower TC and LDL-C
levels by 7–10% in humans (with a certain degree of heterogeneity among
individuals), while it has little or no effect on HDL-C and TG levels.143
However, to date no studies have been performed on the subsequent effect on CVD.
Based on LDL-C lowering and the absence of adverse signals, functional foods
with plant sterols/stanols (≥2 g/day with the main meal) may be considered: (i)
in individuals with high cholesterol levels at intermediate or low global CV
risk who do not qualify for pharmacotherapy; (ii) as an adjunct to
pharmacological therapy in high- and very-high-risk patients who fail to achieve
LDL-C goals on statins or could not be treated with statins; and (iii) in adults
and children (aged >6 years) with FH, in line with current guidance.142

7.5.2 MONACOLIN AND RED YEAST RICE

Red yeast rice (RYR) is a source of fermented pigment that has been used in
China as a food colorant and flavour enhancer for centuries.
Hypocholesterolaemic effects of RYR are related to a statin-like
mechanism—inhibition of hydroxymethylglutaryl-coenzyme A (HMG-CoA) reductase—of
monacolins, which represent the bioactive ingredient. Different commercial
preparations of RYR have different concentrations of monacolins, and lower TC
and LDL-C levels to variable extents, but the consumer is not able to make that
distinction.144,185 Moreover, the long-term safety of the regular consumption of
these products has not been fully documented and safety issues due to the
possible presence of contaminants in some preparations have been raised. Side
effects like those observed with statins have also been reported.

In the only available RCT in patients with ASCVD, a partially purified extract
of RYR reduced recurrent events by 45%.146 A clinically relevant
hypocholesterolaemic effect (up to a 20% reduction) has been observed with RYR
preparations providing an o.d. [once daily (omni die)] dose of 2.5–10 mg
monacolin K.145 Nutraceuticals containing purified RYR may be considered in
people with elevated plasma cholesterol concentrations who do not qualify for
treatment with statins in view of their global CV risk. However, there is a
clear need for better regulation of RYR supplements. Information regarding the
precise composition of these products, the quantities of their components, and
their purity should be implemented.185

7.5.3 DIETARY FIBRE

Available evidence consistently demonstrates a TC- and LDL-C-lowering effect of
β-glucan, a viscous fibre from oat and barley. Foods enriched with these fibres
or supplements are well tolerated, effective, and recommended for LDL-C
lowering.186 However, the dosage needed to achieve a clinically relevant
reduction in levels of LDL-C of 3–5% varies from 3–10 g per day according to the
specific type of fibre.187

7.5.4 SOY

The cholesterol-lowering effect of soy is generally attributed to its isoflavone
and phytoestrogen content, which decreases progressively with the increasing
degree of soybean processing. Soy protein has also been indicated as being able
to induce a modest LDL-C-lowering effect when replacing animal protein foods.
However, this was not confirmed when changes in other dietary components were
taken into account.187,188

7.5.5 POLICOSANOL AND BERBERINE

Policosanol is a natural mixture of long-chain aliphatic alcohols extracted
primarily from sugarcane wax.189 Studies show that policosanol from sugarcane,
rice or wheat germ has no significant effect on LDL-C, HDL-C, TG, ApoB, Lp(a),
homocysteine, high-sensitivity C-reactive protein, fibrinogen, or blood
coagulation factor levels.190

As for berberine, a recent meta-analysis evaluated its effects on plasma lipids
in humans.191 The comparative evaluation of berberine and lifestyle intervention
or placebo indicated that in the berberine group, LDL-C and plasma TG levels
were more effectively reduced than in the control group. However, due to the
lack of high-quality randomized clinical trials, the efficacy of berberine for
treating dyslipidaemia needs to be further validated. Moreover, the
bioavailability of the different berberine preparations is a matter of
debate.187

7.5.6 N-3 UNSATURATED FATTY ACIDS

Observational evidence indicates that consumption of fish (at least twice a
week) and vegetable foods rich in n-3 fatty acids (α-linoleic acid is present in
walnuts, some vegetables, and some seed oils) is associated with lower risk of
CV death and stroke, but has no major effects on plasma lipoprotein
metabolism.178,192 Pharmacological doses of long-chain n-3 fatty acids (2–3
g/day) reduce TG levels by about 30% and also reduce the post-prandial lipaemic
response, but a higher dosage may increase LDL-C levels. α-Linolenic acid is
less effective at altering TG levels.156,193 Recently, a significantly lower
risk of ischaemic events, including CV death, was observed in patients with
elevated TG levels despite the use of statins treated with 2 g of icosapent
ethyl b.i.d. [twice a day].194

Other features of a healthy diet contributing to CVD prevention are presented in
the Supplementary Data.


8 DRUGS FOR TREATMENT OF DYSLIPIDAEMIAS


8.1 STATINS

8.1.1 MECHANISM OF ACTION

Statins reduce the synthesis of cholesterol in the liver by competitively
inhibiting the enzyme HMG-CoA reductase, the rate-limiting step in cholesterol
biosynthesis. The reduction in intracellular cholesterol promotes increased LDL
receptor (LDLR) expression at the surface of the hepatocytes, which in turn
results in increased uptake of LDL from the blood, and decreased plasma
concentrations of LDL- and other ApoB-containing lipoproteins, including TG-rich
particles.

8.1.2 EFFECTS ON LIPIDS

8.1.2.1 LOW-DENSITY LIPOPROTEIN CHOLESTEROL.

The degree of LDL-C reduction is dose-dependent and varies between the different
statins. A high-intensity regimen is defined as the dose of a statin that, on
average, reduces LDL-C by ≥50%; moderate-intensity therapy is defined as the
dose expected to reduce LDL-C by 30–50%. Notably, there is considerable
interindividual variation in LDL-C reduction with the same dose of drug.31 Poor
responses to statin treatment in clinical studies are to some extent caused by
poor compliance, but may also be explained by genetic backgrounds.195,196
Interindividual variations in statin responses warrant monitoring of responses
on initiation of therapy.

Among patients who cannot tolerate the recommended intensity of a statin because
of adverse effects or those who do not reach their goal, the addition of a
non-statin lipid-modifying agent to a maximally tolerated statin is
recommended.197,198

8.1.2.2 TRIGLYCERIDES.

Statins usually reduce TG levels by 10–20% from baseline values.199 More potent
statins (atorvastatin, rosuvastatin, and pitavastatin) demonstrate robust
lowering of TG levels, especially at high doses and in patients with elevated
TGs (HTG), in whom the absolute risk, and therefore the absolute risk reduction,
is larger.

The mechanism of the TG-lowering effect has not been fully elucidated, but it
seems to be partly independent of the LDLR pathway. It may involve the
upregulation of VLDL uptake by hepatocytes, as well as a reduction of the
production rate of VLDLs; these effects seem to be dependent on pre-treatment
VLDL concentrations.200

8.1.2.3 HIGH-DENSITY LIPOPROTEIN CHOLESTEROL.

In a meta-analysis,201 elevations in HDL-C levels varied with dose among the
respective statins; such elevations ranged from 1–10%. However, given the marked
statin-mediated decrement in atherogenic ApoB-containing lipoproteins, the
extent to which the very modest effect on HDL-C levels might contribute to the
overall observed reductions in CV risk consistently observed in statin
intervention trials cannot reliably be disentangled.

8.1.2.4 LIPOPROTEIN(A).

Statins only marginally affect Lp(a) plasma levels. Previous studies have
reported either no effect on or an increase of Lp(a) levels after statin
treatment.202,203 The mechanisms by which statins raise oxidized phospholipids
on Lp(a) require further investigation.

8.1.3 OTHER EFFECTS OF STATINS

Although reduction of LDL-C levels is the major effect of statins, a number of
other, potentially important effects have been suggested (pleiotropic effects of
statins).204,205 Among such effects that are potentially relevant for the
prevention of CVD are the anti-inflammatory and antioxidant effects of statin
treatment. These effects have been shown in vitro and in experimental systems,
but their clinical relevance remains unproven.18,206

8.1.3.1 EFFECT ON CARDIOVASCULAR MORBIDITY AND MORTALITY.

A large number of meta-analyses have been performed to analyse the effects of
statins in populations and in subgroups.34–36,38,51,207–214 In the Cholesterol
Treatment Trialists (CTT) meta-analysis of individual participant data (IPD)
from >170 000 participants in 26 RCTs of a statin vs. control or a more vs. less
intensive statin regimen,34 for each 1 mmol/L reduction in LDL-C, statin/more
statin reduced major vascular events (MI, CAD death, or any stroke or coronary
revascularization) by ∼22%, major coronary events by 23%, CAD death by 20%,
total stroke by 17%, and total mortality by 10% over 5 years. The proportional
effects (per mmol/L reduction in LDL-C) on major vascular events were similar in
all subgroups examined, so the absolute risk reduction was proportional to the
absolute baseline risk. The relative benefits were half as large in the first
year as compared with subsequent years. There was no increased risk for any
non-CV cause of death, including cancer, in those allocated statins. The
absolute benefit from statin treatment was lower in people in primary
prevention, who are typically at lower risk.36,38,214,215 In the CTT
meta-analysis of treatment in people with a low-risk of vascular disease,36 the
relative risk reduction of major vascular events per mmol/L reduction in LDL-C
was at least as large in low-risk individuals (i.e. in primary prevention). In
those without a history of vascular disease, statin therapy reduced the risk of
all-cause mortality by 9% per mmol/L reduction in LDL cholesterol. Similar
results were reported in a Cochrane review in 2013.213 The West of Scotland
Coronary Prevention Study (WOSCOPS) data were recently reanalysed, and
demonstrated that even people without DM and a 10 year predicted ASCVD risk of
<7.5% benefit from statin treatment. There was also a legacy effect with a
mortality benefit of 18% in all-cause death over 20 years.216 Statins are
effective for the prevention of ASCVD in the elderly, including those aged >75
years.217 Statins are not effective in a few specific groups, notably those with
heart failure (HF) or patients receiving haemodialysis.214,218–222

Current available evidence from meta-analyses suggests that the clinical benefit
of statin treatment is largely a class effect, driven by the absolute LDL-C
reduction; therefore, the type of statin used should reflect the treatment goals
for a given patient.

The following scheme may be proposed.

 * Evaluate the total CV risk of the individual.

 * Determine the treatment goals (depending on current risk).

 * Involve the patient in decisions on CV risk management.

 * Choose a statin regimen and, where necessary, additional treatments (e.g.
   ezetimibe or PCSK9 inhibitors) that can meet the treatment goals (per cent
   and absolute value).

 * Response to statin treatment is variable, therefore uptitration of the statin
   dose may be required before additional LDL-lowering treatments are started.



These are general criteria for the choice of drug. Factors such as the clinical
condition of the patient, concomitant medications, drug tolerability, local
treatment tradition, and drug cost will play major roles in determining the
final choice of drug and dose.

Furthermore, the effects of statins on a number of other clinical conditions
have been evaluated. For cancer, a meta-analysis of IPD from randomized trials
has shown that statins do not have any significant effect on cancer, at least
over a period of ∼5 years.223 Other conditions, such as dementia,224 hepatic
steatosis,225 venous thromboembolism,226 atrial fibrillation,227,228 and
polycystic ovary syndrome229 have also been studied, and no effect of statins on
these conditions has been reliably demonstrated.

The suggested effect on Alzheimer's disease was recently reviewed in a Cochrane
analysis reporting no conclusive effect from statins.230 Furthermore,
neurocognitive functions were extensively investigated in the Evaluating PCSK9
Binding Antibody Influence on Cognitive Health in High Cardiovascular Risk
Subjects (EBBINGHAUS) study231 and no excess risk was observed among patients on
a statin regimen randomized to a PCSK9 mAb.

8.1.4 ADVERSE EFFECTS AND INTERACTIONS OF STATINS

Statins differ in their absorption, bioavailability, plasma protein binding,
excretion, and lipophilicity. Evening administration is usually recommended.
Lovastatin and simvastatin are prodrugs, whereas the other available statins are
administered in their active form. Their bioavailability is relatively low,
owing to a first-pass effect in the liver, and many statins undergo significant
hepatic metabolism via cytochrome P450 (CYP) isoenzymes, except pravastatin,
rosuvastatin, and pitavastatin. These enzymes are expressed mainly in the liver
and gut wall. Although statins are generally very well tolerated, they do have
some specific adverse effects on muscle, glucose haemostasis, and haemorrhagic
stroke. However, there is also widespread misinformation about potential adverse
effects, as reviewed recently.232,233

8.1.4.1 ADVERSE EFFECTS ON MUSCLE.

Myopathy is the most clinically relevant adverse effect of statins. Among the
risk factors for myopathy, it is particularly important that interaction with
concomitant drug therapy is considered (see below). Rhabdomyolysis is the most
severe form of statin-induced muscle damage, characterized by severe muscular
pain, muscle necrosis, and myoglobinuria potentially leading to renal failure
and death. In rhabdomyolysis, creatine kinase (CK) levels are elevated by ≥10
times, and often ≥40 times, the upper limit of normal (ULN).234 The frequency of
rhabdomyolysis has been estimated to represent 1–3 cases/100 000
patient-years.235 Patients taking statin therapy frequently report muscle
symptoms [so-called ‘statin-associated muscle symptoms’ (SAMS)], and in
non-randomized, observational studies, statins are associated with muscular pain
and tenderness (myalgia) without CK elevation or major functional loss, with the
reported frequency of SAMS in such studies varying between 10–15% among
statin-treated individuals.236–238 However, in part because individuals in
observational studies are not blind to the treatment they are receiving, such
studies are unreliable when used to assess the adverse effects of statins.233 In
contrast, in blinded randomized trials of statins vs. placebo there is no, or
only a slightly, increased frequency of muscle symptoms in statin-allocated
groups.239,240 The Anglo-Scandinavian Cardiac Outcomes Trial – Lipid-Lowering
Arm (ASCOT-LLA) study addressed this issue by comparing the incidence of four
different adverse events, including muscle-related symptoms, during both the
blinded, placebo-controlled trial and its open-label extension study.238 They
concluded that a nocebo effect (i.e. one caused by negative expectations) may
partly explain the higher frequency of SAMS in observational studies compared
with in trials. Suggested practical management of muscular symptoms is shown in
Supplementary Figure 6.198,234,241 Several studies have shown a considerable
LDL-C-lowering effect of alternative dosing, such as every other day or twice a
week, with atorvastatin or rosuvastatin.242 Although no clinical endpoint trials
are available, this strategy should be considered in high-risk patients in whom
statin treatment with daily doses is not possible.

8.1.4.2 ADVERSE EFFECTS ON THE LIVER.

The activity of alanine aminotransferase (ALT) in plasma is commonly used to
assess hepatocellular damage. Mild elevation of ALT occurs in 0.5–2.0% of
patients on statin treatment, more commonly with potent statins or high doses.
The common definition of clinically relevant ALT elevation has been an increase
of three times the ULN on two consecutive occasions. Mild elevation of ALT has
not been shown to be associated with true hepatotoxicity or changes in liver
function. Progression to liver failure is exceedingly rare, therefore routine
monitoring of ALT during statin treatment is no longer recommended.243 Patients
with mild ALT elevation due to steatosis have been studied during statin
treatment and there is no indication that statins cause any worsening of liver
disease.244–246

8.1.4.3 INCREASED RISK OF NEW-ONSET DIABETES MELLITUS.

Patients on statin treatment have been shown to exhibit an increased risk of
dysglycaemia and development of type 2 diabetes mellitus (T2DM). Several studies
have shown that this is a consistent, dose-related effect.232 A minor, not
clinically relevant elevation of glycated haemoglobin (HbA1c) has also been
observed. The number needed to cause one case of diabetes has been estimated as
255 over 4 years of statin treatment.247 However, the risk is higher with the
more potent statins at high doses,248 and is also higher in the elderly, and in
the presence of other risk factors for diabetes such as overweight or insulin
resistance.249 Overall, the absolute reduction in the risk of CVD in high-risk
patients clearly outweighs the possible adverse effects of a small increase in
the incidence of diabetes.233 This effect is probably related to the mechanism
of action of statins, as Mendelian randomization studies have confirmed the
increased risk of DM in individuals with HMG-CoA reductase polymorphisms that
reduce cholesterol synthesis.250

8.1.4.4 INCREASED RISK OF HAEMORRHAGIC STROKE.

In observational studies, TC is negatively associated with haemorrhagic stroke,
and in the CTT meta-analysis, there was a 21% [95% confidence interval (CI)
5–41%; P=0.01] relative increase per mmol/L lower LDL cholesterol in
haemorrhagic stroke.34,251,252 However, other meta-analyses have yielded
conflicting findings and there is a need for further exploration of the risk of
haemorrhagic stroke in particular types of patients. Note, however, that the
overall benefit on other stroke subtypes greatly outweighs this small (and
uncertain) hazard.34,36

8.1.4.5 ADVERSE EFFECTS ON KIDNEY FUNCTION.

There is no clear evidence that statins have a clinically significant beneficial
or adverse effect on renal function.253 An increased frequency of proteinuria
has been reported for all statins, but has been analysed in more detail for
rosuvastatin. With a dose of 80 mg, a frequency of 12% was reported. With the
approved doses of <40 mg, the frequency is much lower and in line with the
frequency for other statins. The proteinuria induced by statins is of tubular
origin, usually transitory, and is believed to be due to reduced tubular
reabsorption and not to glomerular dysfunction.254,255 In clinical trials, the
frequency of proteinuria is generally low and, in most cases, is not higher than
for placebo.256

8.1.4.6 INTERACTIONS.

A number of important drug interactions with statins have been described that
may increase the risk of adverse effects. Inhibitors and inducers of enzymatic
pathways involved in statin metabolism are summarized in Table 10. All currently
available statins—except pravastatin, rosuvastatin, and pitavastatin—undergo
major hepatic metabolism via the CYPs. These isoenzymes are mainly expressed in
the liver and intestine. Pravastatin does not undergo metabolism through the CYP
system, but is metabolized by sulfation and conjugation. CYP3A4 isoenzymes are
the most abundant, but other isoenzymes such as CYP2C8, CYP2C9, CYP2C19, and
CYP2D6 are frequently involved in the metabolism of statins. Thus, other
pharmacological substrates of these CYPs may interfere with statin metabolism.
Conversely, statin therapy may interfere with the catabolism of other drugs that
are metabolized by the same enzymatic system.

Table 10

Drugs potentially interacting with statins metabolized by cytochrome P450 3A4
leading to increased risk of myopathy and rhabdomyolysis

Anti-infective agents . Calcium antagonists . Other
. Itraconazole Verapamil Ciclosporin Ketoconazole Diltiazem Danazol Posaconazole Amlodipine Amiodarone Erythromycin  Ranolazine Clarithromycin  Grapefruit
juice Telithromycin  Nefazodone HIV protease inhibitors  Gemfibrozil 

Anti-infective agents . Calcium antagonists . Other
. Itraconazole Verapamil Ciclosporin Ketoconazole Diltiazem Danazol Posaconazole Amlodipine Amiodarone Erythromycin  Ranolazine Clarithromycin  Grapefruit
juice Telithromycin  Nefazodone HIV protease inhibitors  Gemfibrozil 

Adapted from Egan and Colman,257 and Wiklund et al.258

HIV = human immunodeficiency virus.

Open in new tab
Table 10

Drugs potentially interacting with statins metabolized by cytochrome P450 3A4
leading to increased risk of myopathy and rhabdomyolysis

Anti-infective agents . Calcium antagonists . Other
. Itraconazole Verapamil Ciclosporin Ketoconazole Diltiazem Danazol Posaconazole Amlodipine Amiodarone Erythromycin  Ranolazine Clarithromycin  Grapefruit
juice Telithromycin  Nefazodone HIV protease inhibitors  Gemfibrozil 

Anti-infective agents . Calcium antagonists . Other
. Itraconazole Verapamil Ciclosporin Ketoconazole Diltiazem Danazol Posaconazole Amlodipine Amiodarone Erythromycin  Ranolazine Clarithromycin  Grapefruit
juice Telithromycin  Nefazodone HIV protease inhibitors  Gemfibrozil 

Adapted from Egan and Colman,257 and Wiklund et al.258

HIV = human immunodeficiency virus.

Open in new tab

Combination of statins with gemfibrozil enhances the risk of myopathy, and its
association with statins must be avoided. There is no or very little increased
risk for myopathy when combining statins with other fibrates, such as
fenofibrate, bezafibrate, or ciprofibrate.259,260


8.2 CHOLESTEROL ABSORPTION INHIBITORS

8.2.1 MECHANISM OF ACTION

Ezetimibe inhibits intestinal uptake of dietary and biliary cholesterol at the
level of the brush border of the intestine [by interacting with the Niemann-Pick
C1-like protein 1 (NPC1L1)] without affecting the absorption of fat-soluble
nutrients. By inhibiting cholesterol absorption, ezetimibe reduces the amount of
cholesterol delivered to the liver. In response to reduced cholesterol delivery,
the liver reacts by upregulating LDLR expression, which in turn leads to
increased clearance of LDL from the blood.

8.2.2 EFFECTS ON LIPIDS

In clinical studies, ezetimibe in monotherapy at 10 mg/day reduces LDL-C in
hypercholesterolaemic patients by 15–22% with relatively high interindividual
variation.261 A meta-analysis of RCTs that included over 2700 people showed an
18.5% reduction in LDL-C as compared with placebo.262 In addition, there was a
significant 3% increase in HDL-C, a significant 8% reduction in TGs, and a 13%
reduction in TC with ezetimibe as compared with placebo.

Ezetimibe added to ongoing statin therapy reduces LDL-C levels by an additional
21–27% compared with placebo in patients with hypercholesterolaemia with or
without established CHD. In statin-naïve patients, ezetimibe and statin
combination therapy has resulted in around a 15% greater reduction in LDL-C when
compared with the same statins and doses in monotherapy. In other studies, this
combination has also significantly improved reductions in LDL-C levels when
compared with doubling of the statin dose (13–20%), and after switching from
statin monotherapy to ezetimibe and statin combination therapy (11–15%).263

Co-administration of ezetimibe and bile acid sequestrants (colesevelam,
colestipol, or cholestyramine) has been reported to result in an additional
reduction of LDL-C levels by 10–20% when compared with the stable bile acid
sequestrant regimen alone.264 Co-administration of ezetimibe with PCSK9
inhibitors also results in an additional effect.265

8.2.3 EFFECT ON CARDIOVASCULAR MORBIDITY AND MORTALITY

The efficacy of ezetimibe in association with simvastatin has been addressed in
people with aortic stenosis in the Simvastatin and Ezetimibe in Aortic Stenosis
(SEAS) trial,266 and in patients with CKD in the Study of Heart and Renal
Protection (SHARP) trial.222 In both the SEAS and SHARP trials, a reduction in
CV events was demonstrated in the simvastatin–ezetimibe arm vs. placebo.266,267

In the Improved Reduction of Outcomes: Vytorin Efficacy International Trial
(IMPROVE-IT), ezetimibe was added to simvastatin (40 mg) in patients after acute
coronary syndrome (ACS).33 A total of 18 144 patients were randomized to statin
or statin plus ezetimibe, and 5314 patients over 7 years experienced a CV event;
170 fewer events (32.7 vs. 34.7%) were recorded in the group taking simvastatin
plus ezetimibe (P=0.016). The average LDL-C during the study was 1.8 mmol/L (70
mg/dL) in the simvastatin group and 1.4 mmol/L (55 mg/dL) in patients taking
ezetimibe plus simvastatin. Also, ischaemic stroke was reduced by 21% in this
trial (P=0.008). There was no evidence of harm caused by ezetimibe or the
further LDL-C reduction. In this group of patients already treated with statins
to reach goals, the absolute CV benefit from added ezetimibe was small, although
significant and in line with the CTT expectations.268 Therefore, the study
supports the proposition that LDL-C lowering by means other than statins is
beneficial and safe. The beneficial effect of ezetimibe is also supported by
genetic studies of mutations in NPC1L1; naturally occurring mutations that
inactivate the protein were found to be associated with reduced plasma LDL-C and
reduced risk for CAD.55,269,270

Taken together with other studies,271 IMPROVE-IT supports the proposal that
ezetimibe should be used as second-line therapy in association with statins when
the therapeutic goal is not achieved at the maximal tolerated statin dose, or in
cases where a statin cannot be prescribed.272,273

8.2.4 ADVERSE EFFECTS AND INTERACTIONS

Ezetimibe is rapidly absorbed and extensively metabolized to pharmacologically
active ezetimibe glucuronide. The recommended dose of ezetimibe of 10 mg/day can
be administered in the morning or evening irrespective of food intake. There are
no clinically significant effects of age, sex, or race on ezetimibe
pharmacokinetics, and no dosage adjustment is necessary in patients with mild
hepatic impairment or mild-to-severe renal insufficiency. Life-threatening liver
failure with ezetimibe as monotherapy or in combination with statins is
extremely rare. The addition of ezetimibe to statin therapy does not appear to
increase the incidence of elevated CK levels beyond what is noted with statin
treatment alone.261


8.3 BILE ACID SEQUESTRANTS

8.3.1 MECHANISM OF ACTION

Bile acids are synthesized in the liver from cholesterol and are released into
the intestinal lumen, but most of the bile acid is returned to the liver from
the terminal ileum via active absorption. The two older bile acid sequestrants,
cholestyramine and colestipol, are both bile acid-binding exchange resins. The
synthetic drug colesevelam is also available in some countries. As bile acid
sequestrants are not systemically absorbed or altered by digestive enzymes, the
beneficial clinical effects are indirect. By binding the bile acids, the drugs
prevent the reabsorption of both the drug and cholesterol into the blood, and
thereby remove a large portion of the bile acids from the enterohepatic
circulation. The liver, depleted of bile, synthesizes more from hepatic
cholesterol, therefore increasing the hepatic demand for cholesterol and
increasing LDLR expression, which results in a decrease of circulating LDL.

8.3.2 EFFECTS ON LIPIDS

At the top daily dose of 24 g of cholestyramine, 20 g of colestipol, or 4.5 g of
colesevelam, a reduction in LDL-C of 18–25% has been observed. No major effect
on HDL-C has been reported, while TGs may increase in some predisposed
patients.274 Colesevelam can also reduce glucose levels in hyperglycaemic
patients.275

8.3.3 EFFECT ON CARDIOVASCULAR MORBIDITY AND MORTALITY

In clinical trials, bile acid sequestrants have contributed greatly to the
demonstration of the efficacy of LDL-C lowering in reducing CV events in
hypercholesterolaemic people, with a benefit proportional to the degree of LDL-C
lowering. Of note, these studies were performed before many of the modern
treatment options were available.276–278

8.3.4 ADVERSE EFFECTS AND INTERACTIONS

Gastrointestinal (GI) adverse effects (most commonly flatulence, constipation,
dyspepsia, and nausea) are often present with these drugs, even at low doses,
which limits their practical use. These adverse effects can be attenuated by
beginning treatment at low doses and ingesting ample fluid with the drug. The
dose should be increased gradually. Reduced absorption of fat-soluble vitamins
has been reported. Furthermore, these drugs may increase circulating TG levels
in certain patients.

Bile acid sequestrants have major drug interactions with several commonly
prescribed drugs, and must therefore be administered either 4 h before or 1 h
after other drugs. Colesevelam is better tolerated and has fewer interactions
with other drugs, and can be taken together with statins and several other
drugs.279


8.4 PROPROTEIN CONVERTASE SUBTILISIN/KEXIN TYPE 9 INHIBITORS

8.4.1 MECHANISM OF ACTION

Recently, a new class of drugs, PCSK9 inhibitors, has become available that
targets a protein (PCSK9) involved in the control of the LDLR.280 Elevated
concentration or function of this protein in plasma reduces LDLR expression by
promoting, upon binding, LDLR lysosomal catabolism and a subsequent increase in
plasma LDL concentrations, while lower concentration or function of PCSK9 is
related to lower plasma LDL-C levels.281 Therapeutic strategies have been
developed mainly using mAbs; the mechanism of action relates to the reduction of
the plasma level of PCSK9, which in turn is not available to bind the LDLR.
Since this interaction triggers the intracellular degradation of the LDLR, lower
levels of circulating PCSK9 will result in increased expression of LDLRs at the
cell surface and therefore in a reduction of circulating LDL-C levels.281
Currently, the only approved PCSK9 inhibitors are two fully human mAbs,
alirocumab and evolocumab. Statin treatment increases circulating PCSK9 serum
levels,282 and thus the best effect of these mAbs has been demonstrated in
combination with statins.

8.4.2 EFFECTS ON LIPIDS

8.4.2.1 LOW-DENSITY LIPOPROTEIN CHOLESTEROL.

In clinical trials, alirocumab and evolocumab—either alone or in combination
with statins, and/or other lipid-lowering therapies—have been shown to
significantly reduce LDL-C levels on average by 60%, depending on dose. The
efficacy appears to be largely independent of any background therapy. In
combination with high-intensity or maximally tolerated statins, alirocumab and
evolocumab reduced LDL-C by 46–73% more than placebo, and by 30% more than
ezetimibe. Among patients in whom statins cannot be prescribed, PCSK9 inhibition
reduced LDL-C when administered in combination with ezetimibe.283 Both
alirocumab and evolocumab have also been shown to effectively lower LDL-C levels
in patients who are at high CV risk, including those with DM.284

Given the mechanism of action, these drugs are effective at reducing LDL-C in
all patients capable of expressing LDLR in the liver. Therefore, this
pharmacological approach is effective in the vast majority of patients,
including those with HeFH and, albeit to a lower level, those with HoFH with
residual LDLR expression. Receptor-deficient HoFH responds poorly to the
therapy.285

8.4.2.2 TRIGLYCERIDES AND HIGH-DENSITY LIPOPROTEIN CHOLESTEROL.

These highly efficacious LDL-lowering agents also lower TG levels, and increase
those of HDL-C and ApoA-I as a function of the dosing regimen. In phase II
trials, evolocumab lowered TG levels by 26%, and raised HDL-C and ApoA-I by 9
and 4%, respectively; similar findings have been reported for alirocumab.286,287
However, the TG effect must be confirmed in populations with higher starting
plasma TG levels.

8.4.2.3 LIPOPROTEIN(A).

In contrast to statins, inhibiting PCSK9 with mAbs also reduces Lp(a) plasma
levels. Pooled results of phase II trials have shown that treatment leads to an
Lp(a) reduction of about 30–40%.288,289 While recent investigations have
attempted to unravel the mechanism, it remains unclear. However, it appears to
be distinct from that of statins, which also enhance LDLR function but do not
lower circulating Lp(a) levels in humans. The relative contribution of this
effect to the reduction of risk remains to be addressed in appropriately
designed studies.

8.4.3 EFFECT ON CARDIOVASCULAR MORBIDITY AND MORTALITY

Early preliminary data from phase III trials suggests a reduction of CV events
in line with the LDL-C reduction achieved.286,290,291

Recently, two major studies were completed: the Further Cardiovascular Outcomes
Research with PCSK9 Inhibition in Subjects with Elevated Risk (FOURIER) and the
Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During
Treatment With Alirocumab (ODYSSEY Outcomes) trials.119,120 The designs of the
trials were similar with regard to the settings of secondary prevention and
background therapy; however, the populations enrolled had either stable CHD,
peripheral arterial disease (PAD), or stroke; or a recent (median 2.6 months)
ACS, respectively. The relative benefit ranged from 15–20% reductions in the
risk of the primary endpoints. Both studies had relatively short follow-up
periods and the evidence from statin trials indicates that the clinical benefits
of LDL-lowering may only emerge after about 1 year,51 so these trials may have
underestimated the potential impact of longer-term treatment.120,290

In the FOURIER trial,119 27 564 patients with atherosclerotic CVD, and LDL-C
levels of 1.8 mmol/L (70 mg/dL) or higher who were receiving statin therapy,
were randomly assigned to receive evolocumab or placebo. Allocation to
evolocumab reduced median LDL-C from 2.38 mmol/L (92 mg/dL) at baseline to a
mean of 0.78 mmol/L (30 mg/dL) at 48 weeks. After a median follow-up of 2.2
years, evolocumab treatment significantly reduced the risk of the primary
endpoint (composite of CV death, MI, stroke, hospitalization for unstable
angina, or coronary revascularization) by 15% [hazard ratio (HR) 0.85, 95% CI
0.79–0.92]. An analysis of the time to benefit also showed that there was a
lower benefit in the first year than in subsequent years, consistent with the
effects of statins observed within the CTT meta-analysis.268 In the FOURIER
trial, allocation to evolocumab did not reduce the risk of CV mortality (HR
1.05, 95% CI 0.88–1.25) or all-cause mortality.

The ODYSSEY Outcomes trial randomized 18 924 patients after hospitalization for
acute MI or unstable angina, treated with statins, and with LDL-C ≥1.8 mmol/L
(≥70 mg/dL), non-HDL cholesterol ≥2.6 mmol/L (≥100 mg/dL), or ApoB ≥80 mg/dL, to
receive injections of alirocumab or matching placebo. Allocation to alirocumab
reduced the mean baseline LDL-C from 2.38 mmol/L (92 mg/dL) to 1.24 mmol/L (48
mg/dL) at 12 months. There was a 15% relative reduction in the primary outcome
(composite of CHD death, non-fatal MI, ischaemic stroke, or unstable angina
requiring hospitalization) (HR 0.85, 95% CI 0.78–0.93) after a median follow-up
of 2.8 years.120 Although there was a significant reduction in all-cause
mortality in the ODYSSEY trial, this was an exploratory outcome and was not
supported by a significant effect on CV death.

8.4.4 ADVERSE EFFECTS AND INTERACTIONS

Anti-PCSK9 mAbs are injected subcutaneously, every other week or once a month,
at different doses depending on the agent used. The potential for interaction
with orally absorbed drugs is absent, as they will not interfere with
pharmacokinetics or pharmacodynamics. Among the most frequently reported side
effects are itching at the site of injection and flu-like symptoms.292 In some
studies, an increase of patient-reported neurocognitive effects has been
described.293 However, the EBBINGHAUS trial,231 which was specifically designed
to detect neurocognitive function changes, was reassuring, as were the safety
reports in both the FOURIER and ODYSSEY trials. Mendelian randomization studies
have also suggested that PCSK9 inhibition may increase the risk of DM with an
LDL-C-related effect, as apparently occurs for statins.294 To date, no signal
has emerged from RCTs.295–297 Although large long-term trials of PCSK9
inhibitors are needed to rule out these and other potential side effects of
inhibition of PCSK9,298 7 year data from the IMPROVE-IT study have shown that
prolonged low LDL-C concentrations are not associated with any clear adverse
effects.299

A potential problem of long-term antibody treatment is the occurrence of
autoantibodies. Evolocumab and alirocumab are fully human antibodies and,
therefore, theoretically less likely to induce autoantibodies. To date, only
very few cases of antidrug antibodies have been reported, and no reduction of
LDL-C lowering has been observed, but long-term use needs to be monitored.
Indeed, the development programme for a third PCSK9 inhibitor, bococizumab, a
humanized antibody, was discontinued because of an increase of neutralizing
antibodies, which resulted in the attenuation of the LDL-C-lowering effect over
time, as well as a higher rate of injection site reactions.300 However, although
PCSK9 inhibitors are very effective drugs that can reduce LDL-C and CV events on
top of statin and/or ezetimibe treatment, considering the costs of the
treatments and the limited data on long-term safety, these drugs are likely to
be considered cost-effective only in those patients at very high-risk of ASCVD,
and their use may not be possible in some countries with limited healthcare
resources.


8.5 LOMITAPIDE

The microsomal TG transfer protein (MTP) transfers TGs and phospholipids from
the endoplasmic reticulum to ApoB, as a necessary step in the formation of VLDL.
MTP inhibition thus prevents the formation of VLDL in the liver and of
chylomicrons in the intestine.

Lomitapide is an MTP inhibitor designed for o.d. oral treatment of HoFH. In an
open-label, single-arm titration study evaluating lomitapide as adjunct therapy
to statins, with or without apheresis and a low-fat diet,301 LDL-C was reduced
by 50% from baseline at 26 weeks and by 44% at 56 weeks. Lomitapide was also
shown to decrease the frequency of apheresis in HoFH patients. It should be
noted that the drug’s effect on CV outcomes has not yet been determined.

As a consequence of its mechanism of action, lomitapide has been shown to be
associated with increased aminotransferase levels, which most likely reflects
the increased fat in the liver, as well as poor GI tolerability.301,302 The GI
side effects were the most frequent reasons preventing a further increase in the
dose of lomitapide in clinical trials.301 However, it has been noted that the
frequency and intensity of GI side effects generally decrease with time.
Therefore, prescription of lomitapide requires careful patient education and
liver function monitoring during therapy.


8.6 MIPOMERSEN

Mipomersen is an antisense oligonucleotide able to bind the messenger RNA (mRNA)
of ApoB-100, which triggers the selective degradation of mRNA molecules. After
subcutaneous injection, the oligonucleotide is preferentially transported to the
liver, where it binds to a specific mRNA preventing the translation of ApoB
protein and, consequently, reducing the production of atherogenic lipids and
lipoproteins, including LDL and Lp(a).303 An adjunct to lipid-lowering
medications and diet, mipomersen is indicated to reduce LDL-C in patients with
HoFH. Mipomersen is currently approved by the US Food and Drug Administration
(FDA), but not by the European Medicines Agency (EMA).

Reactions at the injection site are the most common adverse effects observed in
patients treated with mipomersen.304 However, the main concerns regarding
mipomersen’s safety are related to liver toxicity. Mipomersen may lead to the
development of steatosis. Treated patients have shown a higher increase of liver
fat from baseline compared with patients randomized to placebo.303 The efficacy
and safety of long-term mipomersen treatment are currently under evaluation in
patients with severe HeFH, and in statin-‘intolerant’ patients.


8.7 FIBRATES

8.7.1 MECHANISM OF ACTION

Fibrates are agonists of peroxisome proliferator-activated receptor-α (PPAR-α),
acting via transcription factors regulating, among other things, various steps
in lipid and lipoprotein metabolism. As a consequence, fibrates have good
efficacy in lowering fasting TG levels, as well as post-prandial TGs and TG-rich
lipoprotein (TRL) remnant particles.

8.7.2 EFFECTS ON LIPIDS

Clinical impacts on lipid profiles vary among members of the fibrate class, but
are estimated to reach a 50% reduction of the TG level, a ≤20% reduction of the
LDL-C level (but a paradoxical small LDL-C increase may be observed with high TG
levels), and an increase of the HDL-C level of ≤20%. The magnitude of effect is
highly dependent on the baseline lipid levels.305 Both the HDL-raising and
TG-lowering effects of fibrates have been reported to be markedly less (∼5 and
∼20%, respectively) in long-term intervention trials in people with T2DM but
without elevated levels of TGs.306,307

8.7.3 EFFECT ON CARDIOVASCULAR MORBIDITY AND MORTALITY

The clinical effects of fibrates have been primarily illustrated by six RCTs:
the Helsinki Heart Study (HHS), Veterans Affairs High Density Lipoprotein
Intervention Trial (VA-HIT), Bezafibrate Infarction Prevention (BIP), Lower
Extremity Arterial Disease Event Reduction (LEADER), Fenofibrate Intervention
and Event Lowering in Diabetes (FIELD), and Action to Control Cardiovascular
Risk in Diabetes (ACCORD) trials; in the latter trial, fenofibrate was added to
statin therapy.306–311 In CV outcome trials of fibrates, the risk reduction
appeared to be proportional to the degree of non-HDL-C lowering.50

Although the HHS reported a significant reduction in CVD outcomes with
gemfibrozil, neither the FIELD nor the ACCORD studies involving fenofibrate
showed a reduction in total CVD outcomes. The LEADER trial included male
participants with lower-extremity arterial disease and failed to show that
bezafibrate could lead to a clinically important reduction in CVD combined
endpoints. Decreases in the rates of non-fatal MI were reported, although often
as a result of post hoc analyses. The effect was most evident in people with
elevated TG/low HDL-C levels. However, the data on other outcome parameters have
remained equivocal. Only one study, ACCORD, has analysed the effect of a fibrate
as an add-on treatment to a statin. No overall benefit was reported in two
recent meta-analyses.312,313 Results from other meta-analyses suggest reduced
major CVD events in patients with high TGs and low HDL-C in fibrate-treated
patients, but no decrease in CVD or total mortality.314–316 Thus, the overall
efficacy of fibrates on CVD outcomes is much less robust than that of statins.
Recently, a new selective PPAR-α modulator (pemafibrate) has been reported to
have marked efficacy in reducing TRLs.317 The study, Pemafibrate to Reduce
Cardiovascular OutcoMes by Reducing Triglycerides IN PatiENts With DiabeTes
(PROMINENT), is an ongoing CVD outcome trial designed to evaluate the efficacy
of pemafibrate in some 10 000 high-risk diabetic patients with high TG and low
HDL-C levels.318 Overall, the potential CV benefits of fibrates require further
confirmation.

8.7.4 ADVERSE EFFECTS AND INTERACTIONS

Fibrates are generally well tolerated with mild adverse effects, GI disturbances
being reported in <5% of patients, and skin rashes in 2%.319 In general,
myopathy, liver enzyme elevations, and cholelithiasis represent the most
well-known adverse effects associated with fibrate therapy.319 The risk of
myopathy has been reported to be 5.5-fold greater with fibrate monotherapy
(mainly with gemfibrozil) compared with a statin, and it varies with different
fibrates and statins used in combination. This is explained by the
pharmacological interactions between the metabolism of different fibrates and
pathways of glucuronidation of statins. Gemfibrozil inhibits the metabolism of
statins via the glucuronidation pathway, which leads to marked increases in
plasma concentrations of statins.320 As fenofibrate does not share the same
pharmacokinetic pathways as gemfibrozil, the risk of myopathy is much less with
this combination therapy.319

As a class, fibrates have been reported to raise both serum creatinine and
homocysteine levels in both short- and long-term studies. The increase of serum
creatinine by fibrate therapy seems to be fully reversible when the drug is
stopped. Data from meta-analyses suggest that a reduction of calculated
glomerular filtration rate (GFR) does not reflect any adverse effects on kidney
function.315 Fibrates are associated with a slightly increased risk of
pancreatitis.321 The increase in homocysteine levels caused by fibrates has been
considered to be relatively neutral with respect to CVD risk. However, a
fibrate-induced increase in homocysteine may blunt elevation of both HDL-C and
ApoA1 levels, and this effect may contribute to the smaller than estimated
benefits of fenofibrate in CV outcome parameters.322


8.8 N-3 FATTY ACIDS

8.8.1 MECHANISM OF ACTION

The n-3 (or omega-3) fatty acids [eicosapentaenoic acid (EPA) and
docosahexaenoic acid (DHA)] can be used at pharmacological doses to lower TGs.
n-3 fatty acids (2–4 g/day) affect serum lipids and lipoproteins, in particular
VLDL concentrations. The underlying mechanism is poorly understood, although it
may be related, at least in part, to their ability to interact with PPARs and to
decreased secretion of ApoB.

8.8.2 EFFECTS ON LIPIDS

n-3 fatty acids reduce TGs, but their effects on other lipoproteins are trivial.
More detailed data on clinical outcomes are needed to justify wide use of
prescription n-3 fatty acids.323 The recommended doses of total EPA and DHA to
lower TGs have varied between 2–4 g/day. Three recent studies in people with
high TGs using EPA reported a significant reduction in serum TG levels of up to
45% in a dose-dependent manner.324–326 The efficacy of omega-3 fatty acids in
lowering serum TGs has also been reported in meta-analyses.157 Recently, the
EpanoVa fOr Lowering Very high triglyceridEs II (EVOLVE II) trial confirmed the
efficacy of omega-3 fatty acids in lowering serum TGs.327

8.8.3 EFFECT ON CARDIOVASCULAR MORBIDITY AND MORTALITY

A Cochrane meta-analysis, including 112 059 people from 79 trials, reported no
overall effect of omega-3 PUFAs on total mortality (relative risk 0.98, 95% CI
0.90–1.03) or CV events (relative risk 0.99, 95% Cl 0.94–1.04), with only a
suggestion that omega-3 fatty acids reduced CHD events (relative risk 0.93, 95%
Cl 0.88–0.97).328 Recently, the A Study of Cardiovascular Events iN Diabetes
(ASCEND) trial,329 which randomly assigned 15 480 patients with DM but without
atherosclerotic CV disease to n-3 fatty acids or placebo, showed no significant
difference in the risk of serious vascular events after a mean follow-up of 7.4
years (relative risk 1.00, 95% Cl 0.91–1.09).

The data remain inconclusive and the clinical efficacy of omega-3 fatty acids
appears to be related to non-lipid effects.330,331 Moreover, studies with
omega-3 fatty acids have suffered from the dose used (1 g/day), which does not
affect plasma lipids to a large extent, as the dose required to decrease plasma
TGs is >2 g/day. The Reduction of Cardiovascular Events with EPA-Intervention
Trial (REDUCE-IT)195 aimed to evaluate the potential benefits of omega-3 oil
(EPA) on ASCVD outcomes in people with elevated serum TGs; the trial enrolled
∼8000 patients on statin therapy, with LDL-C levels between 1.0–2.6 mmol/L
(41–100 mg/dL) and various CV risk factors, including persistent elevated TGs
between 1.7–5.6 mmol/L (150–499 mg/dL), and either established ASCVD or DM, and
at least one other CV risk factor. Use of high doses (2 g b.i.d.) of EPA as
compared with placebo (mineral oil) resulted in a ∼25% relative risk reduction
(P < 0.001) in major adverse CV events (MACE). Another randomized
placebo-controlled trial, Outcomes Study to Assess STatin Residual Risk
Reduction with EpaNova in HiGh CV Risk PatienTs with Hypertriglyceridemia
(STRENGTH),332 which aims to determine whether reduction of TRLs and remnants in
statin-treated patients will provide additional ASCVD risk reduction, is
ongoing. The VITamin D and OmegA-3 TriaL (VITAL), which reported recently, was a
2×2 factorial design study in which healthy participants were randomized in a
1:1 fashion to either vitamin D3 (at a dose of 2000 IU per day) vs. matching
placebo, and n-3 fatty acids (1 g per day as a fish-oil capsule containing 840
mg of n-3 fatty acids, including 460 mg of EPA and 380 mg of DHA) vs. matching
placebo. It showed that supplementation with either n-3 fatty acids at a dose of
1 g/day, or vitamin D3 at a dose of 2000 IU/day, was not effective for primary
prevention of CV or cancer events among healthy middle-aged men and women over 5
years of follow-up.333

8.8.4 SAFETY AND INTERACTIONS

The administration of n-3 fatty acids appears to be safe and devoid of
clinically significant interactions. The most common side effect is GI
disturbance. The antithrombotic effects may increase the propensity for
bleeding, especially when given in addition to aspirin/clopidogrel. Recently,
data from one study have associated a risk of prostate cancer with high dietary
intake of n-3 PUFAs.334


8.9 NICOTINIC ACID

Nicotinic acid has key action sites in both the liver and adipose tissue. In the
liver, nicotinic acid inhibits diacylglycerol acyltransferase-2 resulting in
decreased secretion of VLDL particles, which is also reflected in reductions of
plasma levels of both IDL and LDL particles.335 Nicotinic acid primarily raises
HDL-C and ApoA1 by stimulating ApoA1 production in the liver.335 Two large
randomized trials with nicotinic acid—one with extended-release niacin66 and one
with niacin plus laropiprant67—have shown no beneficial effect and an increased
frequency of serious adverse effects. No medication containing nicotinic acid is
currently approved in Europe.


8.10 CHOLESTERYL ESTER TRANSFER PROTEIN INHIBITORS

To date, the pharmacological approach that has led to the greatest elevations in
HDL-C levels has been direct inhibition of CETP by small-molecule inhibitors,
which may induce an increase in HDL-C by ≥100% on a dose-dependent basis.
Torcetrapib was studied in the Investigation of Lipid Level Management to
Understand its Impact in Atherosclerotic Events (ILLUMINATE) trial, which was
stopped early due to increased mortality.336 Dalcetrapib raises HDL-C levels by
30–40% with no appreciable effect on LDL-C, offering specific insight into pure
HDL-C raising. However, dalcetrapib failed to show any benefit in ACS patients
in the dal-OUTCOMES trial. Evacetrapib, which raises HDL-C levels by 130% and
lowers LDL-C by 37%, was studied in the ACCELERATE trial,63 which was terminated
due to futility. Recently, anacetrapib, which raises HDL-C and ApoA-I levels (by
104 and 36%, respectively), and lowers LDL-C and ApoB (by 17 and 18%,
respectively), was studied in the REVEAL trial. Anacetrapib reduced major
coronary events by 9% over a median of 4.1 years.64 The magnitude of the
relative risk reduction appeared to be consistent with the magnitude of LDL-C-
or non-HDL-C-level lowering.337 This drug has not been submitted for regulatory
approval.


8.11 FUTURE PERSPECTIVES

8.11.1 NEW APPROACHES TO REDUCE LOW-DENSITY LIPOPROTEIN CHOLESTEROL

An alternative approach targeting PCSK9 consists of RNA interference. In a phase
I and a phase II trial, the small interfering RNA (siRNA) molecule
inclisiran—which inhibits the synthesis of PCSK9—reduced LDL-C by up to 50% and
the reduction was dose-dependent. Reductions in PCSK9 and LDL-C levels were
maintained for ≤6 months.338,339 No specific serious adverse events were
observed. HPS4/TIMI65/ORION4, with a planned mean duration of 5 years, is
currently comparing inclisiran vs. placebo among 15 000 patients with a prior MI
or stroke.

Bempedoic acid is a novel, first-in-class, oral small molecule that inhibits
cholesterol synthesis by inhibiting the action of ATP citrate lyase, a cytosolic
enzyme upstream of 3-hydroxy-3-methylglutaryl-coenzyme A reductase.340 So far,
it has been tested in diabetic patients, and patients with or without statin
‘intolerance’. In monotherapy, bempedoic acid reduces LDL-C levels by ∼30% and
by about 50% in combination with ezetimibe. Bempedoic acid is currently being
tested in phase III trials and some trials have been completed.341,342

8.11.2 NEW APPROACHES TO REDUCE TRIGLYCERIDE-RICH LIPOPROTEINS AND THEIR
REMNANTS

As genetic studies indicate that angiopoietin-like protein 3 (ANGPTL3)
deficiency protects against atherosclerotic disease and that this relationship
is causal,343 an ANGPTL3 antibody (evinacumab) is being developed. Evinacumab
has been shown to decrease TGs, LDL-C, and Lp(a) levels in HoFH patients.344
Another approach that is currently being investigated is the inhibition of
ANGPTL3 production by antisense oligonucleotides.345 IONIS-ANGPTL3-LRx, an
antisense oligonucleotide targeting ANGPTL3, another critical protein in the
clearance of TRLs, reduces plasma TGs by about 85%. Thus, the future may yield
tools to improve TRL clearance that will be reflected in the atherogenic load of
the remnant particles.

The rapid development of gene-silencing technology has allowed proteins
(ApoC-III) that are critical in the regulation of TRL clearance processes to be
targeted. A second-generation antisense oligonucleotide targeting ApoC-III mRNA
has been developed.346 Two phase III trials have evaluated the safety and
efficacy of volanesorsen in patients with elevated TG levels.347,348
Volanesorsen reduced plasma TGs by ∼70% and ApoC-III by 80–90%.349 The EMA
recently issued a marketing authorization for Waylivra (volanesorsen) as an
adjunct to diet in adult patients with genetically confirmed familial
chylomicronaemia syndrome (FCS) who are at high-risk for pancreatitis, in whom
response to diet and TG-lowering therapy has been inadequate.

8.11.3 NEW APPROACHES TO INCREASE HIGH-DENSITY LIPOPROTEIN CHOLESTEROL

Although genetic studies suggest that low HDL-C levels are not a cause of ASCVD,
casting doubt on the possibilities of future treatment options to raising HDL-C
levels with attenuation of CVD, major developments in the search for efficacious
agents to raise HDL-C and ApoA1 levels with concomitant benefits on
atherosclerosis and CV events are on the horizon. On the one hand, interest is
focused on ApoA1 mimetic peptides and recombinant forms of HDL possessing
potential for in vivo HDL particle remodelling and enhanced cardioprotective
activity.350 On the other, agents that enhance catabolism of TG-rich
lipoproteins, such as the antisense oligonucleotide to ApoC-III, and which lead
to a concomitant reduction in TGs (∼70%) and a marked elevation in HDL-C (∼40%)
in hypertriglyceridemia, are under development.351 Importantly, however, we
currently lack understanding of the relationship between the modality of raising
HDL/ApoA-I levels and a possible antiatherogenic function of HDL particles.

8.11.4 NEW APPROACHES TO REDUCE LIPOPROTEIN(A) LEVELS

Another approach under study is the selective decrease of Lp(a) concentrations.
RNA-based therapies are now being evaluated in clinical settings. Results from
studies of an antisense oligonucleotide in patients with normal Lp(a) values as
well as in patients with elevated Lp(a) concentrations have shown a reduction of
>90%.352 These approaches are currently being evaluated in phase II–III studies
and an outcome trial is planned to study whether Lp(a) reduction translates into
risk reduction.


8.12 STRATEGIES TO CONTROL PLASMA CHOLESTEROL

Recommendations for pharmacological low-density lipoprotein cholesterol lowering

 

 

ASCVD = atherosclerotic cardiovascular disease; FH = familial
hypercholesterolaemia; LDL-C = low-density lipoprotein cholesterol; PCSK9 =
proprotein convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

c

For definitions see Table 7.

Open in new tab

Recommendations for pharmacological low-density lipoprotein cholesterol lowering

 

 

ASCVD = atherosclerotic cardiovascular disease; FH = familial
hypercholesterolaemia; LDL-C = low-density lipoprotein cholesterol; PCSK9 =
proprotein convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

c

For definitions see Table 7.

Open in new tab

Although LDL-C goals are attained with monotherapy in many patients, a
significant proportion of patients at high-risk or with very high LDL-C levels
need additional treatment. In this case, combination therapy is reasonable. In
patients at very-high risk and with persistent high-risk despite being treated
with a maximally tolerated statin, combination with ezetimibe is recommended
and, if still not at goal, the addition of a PCSK9 inhibitor is recommended (see
Figure 4 and Recommendations for pharmacological low-density lipoprotein
cholesterol lowering). Of note, addition of a PCSK9 inhibitor directly to a
statin is also feasible120,290 (Figure 4).

Figure 3
Open in new tabDownload slide

Expected clinical benefits of low-density lipoprotein cholesterol-lowering
therapies. The expected clinical benefits of treatment to lower low-density
lipoprotein cholesterol for any person can be estimated; it depends on the
intensity of therapy, the baseline low-density lipoprotein cholesterol level,
the expected absolute achieved reduction in low-density lipoprotein cholesterol,
and the baseline estimated risk of atherosclerotic cardiovascular disease. The
intensity of therapy should be selected to achieve the recommended proportional
reduction in low-density lipoprotein cholesterol based on the person’s estimated
risk of atherosclerotic cardiovascular disease. Multiplying the proportional
reduction in low-density lipoprotein cholesterol by a person’s baseline
low-density lipoprotein cholesterol level estimates the expected absolute
reduction in low-density lipoprotein cholesterol that is likely to be achieved
with that therapy. Because each 1.0 mmol/L absolute reduction in low-density
lipoprotein cholesterol is associated with a 20% reduction in the risk of
cardiovascular events, larger absolute reductions in low-density lipoprotein
cholesterol lead to larger proportional reductions in risk. Multiplying the
proportional reduction in risk expected for the achieved absolute reduction in
low-density lipoprotein cholesterol by a person’s estimated baseline risk of
atherosclerotic cardiovascular disease determines the expected absolute risk
reduction for that person. LDL-C = low-density lipoprotein cholesterol; PCSK9 =
proprotein convertase subtilisin/kexin type 9.

Figure 4
Open in new tabDownload slide

(A) Treatment algorithm for pharmacological low-density lipoprotein cholesterol
lowering. (B) Treatment goals for low-density lipoprotein cholesterol across
categories of total cardiovascular disease risk. ASCVD = atherosclerotic
cardiovascular disease; BP = blood pressure; CKD = chronic kidney disease; CV =
cardiovascular; DM = diabetes mellitus; eGFR = estimated glomerular filtration
rate; FH = familial hypercholesterolaemia; LDL-C = low-density lipoprotein
cholesterol; PCSK9 = proprotein convertase subtilisin/kexin type 9; SCORE =
Systematic Coronary Risk Estimation; T1DM = type 1 DM; T2DM = type 2 DM; TC =
total cholesterol.

As shown in Figure 3, the expected clinical benefit of treatment to lower the
LDL-C level of any person can be estimated; it depends on the intensity of
therapy, the baseline LDL-C level, and the baseline estimated risk of ASCVD.
This simple algorithm can be used to help clinicians select the appropriate
therapy and quantify the expected benefits of LDL-C-lowering therapy to help
inform discussions with patients. For ease of reference, Supplementary Table 3
provides a summary of the absolute LDL-C reductions that can be achieved with
various therapeutic approaches at particular baseline levels of LDL-C.


8.13 STRATEGIES TO CONTROL PLASMA TRIGLYCERIDES

Although CVD risk is increased when fasting TGs are >1.7 mmol/L (>150 mg/dL),56
the use of drugs to lower TG levels may only be considered in high-risk patients
when TGs are >2.3 mmol/L (>200 mg/dL) and TGs cannot be lowered by lifestyle
measures. The available pharmacological interventions include statins, fibrates,
PCSK9 inhibitors, and n-3 PUFAs. A meta-analysis of 10 trials included people
treated with various agents that reduce serum TGs (fibrates, niacin, and n-3
PUFAs) and reported a 12% reduction in CV outcomes.354 Recently, the REDUCE-IT
trial194 demonstrated that in statin-treated patients with high CV risk with
fasting TG levels between 135–499 mg/dL (1.52–1.63 mmol/L), high-dose icosapent
ethyl, a highly purified and stable EPA (2 g) taken b.i.d., significantly
reduced the risk of ischaemic events, including CV death, by about one-quarter
over a median follow-up of 4.9 years. In addition, the VITAL trial showed that
n-3 fatty acids at the lower dose of 1 g/day were not effective for primary
prevention of CV or cancer events among healthy middle-aged men and women over 5
years of follow-up.333 Recommendations for the treatment of HTG are shown below.

Recommendations for drug treatment of patients with hypertriglyceridaemia

 

 

CVD = cardiovascular disease; LDL-C = low-density lipoprotein cholesterol; PUFA
= polyunsaturated fatty acids; TG = triglyceride.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for drug treatment of patients with hypertriglyceridaemia

 

 

CVD = cardiovascular disease; LDL-C = low-density lipoprotein cholesterol; PUFA
= polyunsaturated fatty acids; TG = triglyceride.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9 MANAGEMENT OF DYSLIPIDAEMIAS IN DIFFERENT CLINICAL SETTINGS


9.1 FAMILIAL DYSLIPIDAEMIAS

Plasma lipid levels are, to a very large extent, determined by genetic factors.
In its more extreme forms this is manifested as familial dyslipidaemias. A
number of monogenic lipid disorders have been identified; among these, FH is the
most common and is strongly related to CVD (Table 11). In general, in a patient
with dyslipidaemia, the pattern of inheritance commonly does not suggest that
there is a major single gene (monogenic) disorder causing the abnormality;
rather, it stems from the inheritance of more than one gene variant affecting
lipoprotein metabolism that, on its own, might have relatively little effect,
but in combination with another or others has a greater influence on TC, TGs, or
HDL-C. The pattern of inheritance is polygenic.357 It is common to find that
high LDL-C, high TG, or low HDL-C levels affect several family members.

Table 11

Genetic disorders of lipoprotein metabolism

Disorder . Prevalence . Gene(s) . Effect on lipoproteins . HeFH 1 in 200–250 

 * LDLR

 * APO B

 * PCSK9

 ↑LDL-C HoFH 1 in 160 000–320 000 

 * LDLR

 * APO B

 * PCSK9

 ↑↑LDL-C FCH 1 in 100/200 USF1 + modifying genes ↑LDL-C ↑VLDL-C ↑ApoB Familial
dysbetalipoproteinaemia 1 in 5000 APO E ↑↑IDL and chylomicron remnants
(βVLDL) Familial lipoprotein lipase deficiency (familial chylomicron syndrome) 2
in 106 

 * LPL

 * APO C2

 * ApoAV, GPIHBP1

 * LMF1

 ↑↑chylomicrons and VLDL-C Tangier disease (analphalipoproteinaemia) 1 in
106 ABCA1 ↓↓HDL-C Familial LCAT deficiency 1 in 106 LCAT ↓HDL-C 

Disorder . Prevalence . Gene(s) . Effect on lipoproteins . HeFH 1 in 200–250 

 * LDLR

 * APO B

 * PCSK9

 ↑LDL-C HoFH 1 in 160 000–320 000 

 * LDLR

 * APO B

 * PCSK9

 ↑↑LDL-C FCH 1 in 100/200 USF1 + modifying genes ↑LDL-C ↑VLDL-C ↑ApoB Familial
dysbetalipoproteinaemia 1 in 5000 APO E ↑↑IDL and chylomicron remnants
(βVLDL) Familial lipoprotein lipase deficiency (familial chylomicron syndrome) 2
in 106 

 * LPL

 * APO C2

 * ApoAV, GPIHBP1

 * LMF1

 ↑↑chylomicrons and VLDL-C Tangier disease (analphalipoproteinaemia) 1 in
106 ABCA1 ↓↓HDL-C Familial LCAT deficiency 1 in 106 LCAT ↓HDL-C 

Apo = apolipoprotein; FCH = familial combined hyperlipidaemia; HDL-C =
high-density lipoprotein cholesterol; HeFH = heterozygous familial
hypercholesterolaemia; HoFH = homozygous familial hypercholesterolaemia; IDL =
intermediate-density lipoprotein; LCAT = lecithin cholesterol acyltransferase;
LDL-C = low-density lipoprotein cholesterol; VLDL = very low-density lipoprotein
cholesterol.

Open in new tab
Table 11

Genetic disorders of lipoprotein metabolism

Disorder . Prevalence . Gene(s) . Effect on lipoproteins . HeFH 1 in 200–250 

 * LDLR

 * APO B

 * PCSK9

 ↑LDL-C HoFH 1 in 160 000–320 000 

 * LDLR

 * APO B

 * PCSK9

 ↑↑LDL-C FCH 1 in 100/200 USF1 + modifying genes ↑LDL-C ↑VLDL-C ↑ApoB Familial
dysbetalipoproteinaemia 1 in 5000 APO E ↑↑IDL and chylomicron remnants
(βVLDL) Familial lipoprotein lipase deficiency (familial chylomicron syndrome) 2
in 106 

 * LPL

 * APO C2

 * ApoAV, GPIHBP1

 * LMF1

 ↑↑chylomicrons and VLDL-C Tangier disease (analphalipoproteinaemia) 1 in
106 ABCA1 ↓↓HDL-C Familial LCAT deficiency 1 in 106 LCAT ↓HDL-C 

Disorder . Prevalence . Gene(s) . Effect on lipoproteins . HeFH 1 in 200–250 

 * LDLR

 * APO B

 * PCSK9

 ↑LDL-C HoFH 1 in 160 000–320 000 

 * LDLR

 * APO B

 * PCSK9

 ↑↑LDL-C FCH 1 in 100/200 USF1 + modifying genes ↑LDL-C ↑VLDL-C ↑ApoB Familial
dysbetalipoproteinaemia 1 in 5000 APO E ↑↑IDL and chylomicron remnants
(βVLDL) Familial lipoprotein lipase deficiency (familial chylomicron syndrome) 2
in 106 

 * LPL

 * APO C2

 * ApoAV, GPIHBP1

 * LMF1

 ↑↑chylomicrons and VLDL-C Tangier disease (analphalipoproteinaemia) 1 in
106 ABCA1 ↓↓HDL-C Familial LCAT deficiency 1 in 106 LCAT ↓HDL-C 

Apo = apolipoprotein; FCH = familial combined hyperlipidaemia; HDL-C =
high-density lipoprotein cholesterol; HeFH = heterozygous familial
hypercholesterolaemia; HoFH = homozygous familial hypercholesterolaemia; IDL =
intermediate-density lipoprotein; LCAT = lecithin cholesterol acyltransferase;
LDL-C = low-density lipoprotein cholesterol; VLDL = very low-density lipoprotein
cholesterol.

Open in new tab

9.1.1 FAMILIAL COMBINED HYPERLIPIDAEMIA

Familial combined hyperlipidaemia (FCH) is a highly prevalent mixed
dyslipidaemia (1:100–200) characterized by elevated levels of LDL-C, TGs, or
both, and is an important cause of premature CAD. FCH is a complex disease, and
the phenotype is determined by the interaction of multiple susceptibility genes
and the environment. It has considerable overlap with the dyslipidaemic
phenotypes of T2DM and MetS. Even within a family, the phenotype shows high
inter- and intrapersonal variability based on lipid values (TGs, LDL-C, HDL-C,
and ApoB). FCH has no monogenic component and is not linked to a single genetic
cause, but the phenotype is high LDL-C and/or high TGs.358,359 Therefore, the
diagnosis is commonly missed in clinical practice; the combination of ApoB >120
mg/dL and TGs >1.5 mmol/L (>133 mg/dL) with a family history of premature CVD
can be used to identify people who most probably have FCH.360

The concept of mixed dyslipidaemia is also valuable clinically in assessing CV
risk. It emphasizes both the importance of considering family history in
deciding how rigorously to treat dyslipidaemia and that elevated LDL-C levels
portend a higher risk when HTG is also present. Statin treatment decreases CV
risk by the same relative amount in people with HTG as in those without. Because
the absolute risk is often greater in those with HTG, they may therefore benefit
greatly from LDL-lowering therapy.

9.1.2 FAMILIAL HYPERCHOLESTEROLAEMIA

9.1.2.1 HETEROZYGOUS FAMILIAL HYPERCHOLESTEROLAEMIA.

FH is a common codominant monogenic dyslipidaemia causing premature CVD due to
lifelong elevation of plasma levels of LDL-C. If left untreated, men and women
with HeFH typically develop early CAD before the ages of 55 and 60 years
respectively. The risk of CHD among individuals with definite or probable HeFH
is estimated to be increased at least 10-fold. However, early diagnosis and
appropriate treatment can dramatically reduce the risk for CAD.

The prevalence of HeFH in the population is estimated to be 1/200–250,361
translating to a total number of cases between 14–34 million worldwide.362,363
Only a minor fraction of these cases is identified and properly treated.

FH is a monogenic disease caused by loss-of-function mutations in the LDLR or
apoB genes, or a gain-of-function mutation in the PCSK9 gene; around 95% of FH
cases are caused by mutations in LDLR. More than 1000 different mutations that
cause FH have been identified in LDLR. The different mutations cause reduced
function or complete loss-of-function, the latter being associated with more
severe hypercholesterolaemia and CVD.

The diagnosis of FH is usually based on clinical presentation. The commonly used
criteria from the Dutch Lipid Clinic Network are shown in Table 12. Other
criteria are the Simon Broome register or the WHO criteria.364,365

Table 12

Dutch Lipid Clinic Network diagnostic criteria for familial
hypercholesterolaemia

Criteria . Points . 1) Family history First-degree relative with known premature
(men aged <55 years; women <60 years) coronary or vascular disease, or
first-degree relative with known LDL-C above the 95th percentile 1 First-degree
relative with tendinous xanthomata and/or arcus cornealis, or children aged <18
years with LDL-C above the 95th percentile 2 2) Clinical history Patient with
premature (men aged <55 years; women <60 years) CAD 2 Patient with premature
(men aged <55 years; women <60 years) cerebral or peripheral vascular
disease 1 3) Physical examinationa Tendinous xanthomata 6 Arcus cornealis before
age 45 years 4 4) LDL-C levels (without treatment) LDL-C ≥8.5 mmol/L (≥325
mg/dL) 8 LDL-C 6.5–8.4 mmol/L (251–325 mg/dL) 5 LDL-C 5.0–6.4 mmol/L (191–250
mg/dL) 3 LDL-C 4.0–4.9 mmol/L (155–190 mg/dL) 1 5) DNA analysis Functional
mutation in the LDLR, apoB, or PCSK9 genes 8 Choose only one score per group,
the highest applicable; diagnosis is based on the total number of points
obtained A ‘definite’ FH diagnosis requires >8 points A ‘probable’ FH diagnosis
requires 6–8 points A ‘possible’ FH diagnosis requires 3–5 points 

Criteria . Points . 1) Family history First-degree relative with known premature
(men aged <55 years; women <60 years) coronary or vascular disease, or
first-degree relative with known LDL-C above the 95th percentile 1 First-degree
relative with tendinous xanthomata and/or arcus cornealis, or children aged <18
years with LDL-C above the 95th percentile 2 2) Clinical history Patient with
premature (men aged <55 years; women <60 years) CAD 2 Patient with premature
(men aged <55 years; women <60 years) cerebral or peripheral vascular
disease 1 3) Physical examinationa Tendinous xanthomata 6 Arcus cornealis before
age 45 years 4 4) LDL-C levels (without treatment) LDL-C ≥8.5 mmol/L (≥325
mg/dL) 8 LDL-C 6.5–8.4 mmol/L (251–325 mg/dL) 5 LDL-C 5.0–6.4 mmol/L (191–250
mg/dL) 3 LDL-C 4.0–4.9 mmol/L (155–190 mg/dL) 1 5) DNA analysis Functional
mutation in the LDLR, apoB, or PCSK9 genes 8 Choose only one score per group,
the highest applicable; diagnosis is based on the total number of points
obtained A ‘definite’ FH diagnosis requires >8 points A ‘probable’ FH diagnosis
requires 6–8 points A ‘possible’ FH diagnosis requires 3–5 points 

CAD = coronary artery disease; FH = familial hypercholesterolaemia; LDL-C =
low-density lipoprotein cholesterol; PCSK9 = proprotein convertase
subtilisin/kexin type 9.

a

Exclusive of each other (i.e. maximum 6 points if both are present).

Open in new tab
Table 12

Dutch Lipid Clinic Network diagnostic criteria for familial
hypercholesterolaemia

Criteria . Points . 1) Family history First-degree relative with known premature
(men aged <55 years; women <60 years) coronary or vascular disease, or
first-degree relative with known LDL-C above the 95th percentile 1 First-degree
relative with tendinous xanthomata and/or arcus cornealis, or children aged <18
years with LDL-C above the 95th percentile 2 2) Clinical history Patient with
premature (men aged <55 years; women <60 years) CAD 2 Patient with premature
(men aged <55 years; women <60 years) cerebral or peripheral vascular
disease 1 3) Physical examinationa Tendinous xanthomata 6 Arcus cornealis before
age 45 years 4 4) LDL-C levels (without treatment) LDL-C ≥8.5 mmol/L (≥325
mg/dL) 8 LDL-C 6.5–8.4 mmol/L (251–325 mg/dL) 5 LDL-C 5.0–6.4 mmol/L (191–250
mg/dL) 3 LDL-C 4.0–4.9 mmol/L (155–190 mg/dL) 1 5) DNA analysis Functional
mutation in the LDLR, apoB, or PCSK9 genes 8 Choose only one score per group,
the highest applicable; diagnosis is based on the total number of points
obtained A ‘definite’ FH diagnosis requires >8 points A ‘probable’ FH diagnosis
requires 6–8 points A ‘possible’ FH diagnosis requires 3–5 points 

Criteria . Points . 1) Family history First-degree relative with known premature
(men aged <55 years; women <60 years) coronary or vascular disease, or
first-degree relative with known LDL-C above the 95th percentile 1 First-degree
relative with tendinous xanthomata and/or arcus cornealis, or children aged <18
years with LDL-C above the 95th percentile 2 2) Clinical history Patient with
premature (men aged <55 years; women <60 years) CAD 2 Patient with premature
(men aged <55 years; women <60 years) cerebral or peripheral vascular
disease 1 3) Physical examinationa Tendinous xanthomata 6 Arcus cornealis before
age 45 years 4 4) LDL-C levels (without treatment) LDL-C ≥8.5 mmol/L (≥325
mg/dL) 8 LDL-C 6.5–8.4 mmol/L (251–325 mg/dL) 5 LDL-C 5.0–6.4 mmol/L (191–250
mg/dL) 3 LDL-C 4.0–4.9 mmol/L (155–190 mg/dL) 1 5) DNA analysis Functional
mutation in the LDLR, apoB, or PCSK9 genes 8 Choose only one score per group,
the highest applicable; diagnosis is based on the total number of points
obtained A ‘definite’ FH diagnosis requires >8 points A ‘probable’ FH diagnosis
requires 6–8 points A ‘possible’ FH diagnosis requires 3–5 points 

CAD = coronary artery disease; FH = familial hypercholesterolaemia; LDL-C =
low-density lipoprotein cholesterol; PCSK9 = proprotein convertase
subtilisin/kexin type 9.

a

Exclusive of each other (i.e. maximum 6 points if both are present).

Open in new tab

The diagnosis can be verified by showing causative mutations in the pathogenic
genes. However, in most studies, the frequency of detectable mutations in
patients with a clinically definite or probable HeFH is between 60–80%. This
suggests that a considerable proportion of patients with FH have either a
polygenic cause of the disease or that other genes, yet to be identified, are
involved.

Genetic testing and cascade screening. Probands (index cases) should be
identified according to the following criteria:

 * TC ≥8 mmol/L (≥310 mg/dL) without treatment in an adult or adult family
   member (or >95th percentile by age and gender for country);

 * Premature CHD in the patient or a family member;

 * Tendon xanthomas in the patient or a family member; or

 * Sudden premature cardiac death in a family member.



Cascade screening of family members of a known index case allows for the
efficient identification of new cases. Cascade screening is best performed by a
lipid clinic. In most families, the cases may be identified with TC or LDL-C
analysis; however, genetic testing is recommended when the causative mutation is
known.

Cholesterol-lowering treatment should be initiated as soon as possible after a
diagnosis has been made. To improve risk assessment, the use of imaging
techniques to detect asymptomatic atherosclerosis is recommended. The concept of
cumulative cholesterol burden illustrates the importance of early treatment (for
children, see below). Treatment should be initiated with high-intensity statin
therapy, in most cases in combination with ezetimibe. In FH patients at
very-high risk of ASCVD due to a prior history of ASCVD or another major risk
factor, LDL-C goals are a ≥50% reduction of LDL-C from baseline and an LDL-C
<1.4 mmol/L (<55 mg/dL). In the absence of ASCVD or another major risk factor,
patients with FH are categorized as high-risk, and LDL-C goals are a ≥50%
reduction of LDL-C from baseline and an LDL-C <1.8 mmol/L (<70 mg/dL).

PCSK9 inhibitors lower LDL-C levels by up to 60% on top of statins. Two RCTs
have reported a beneficial effect on clinical endpoints in ASCVD patients
without FH.119,120 PCSK9 inhibitors are recommended in very-high-risk patients
with FH if the treatment goal is not achieved on maximal tolerated statin plus
ezetimibe. PCSK9 inhibitors are also recommended in FH patients who cannot
tolerate statins.366,367

Recommendations for the detection and treatment of patients with HeFH are shown
below.

Recommendations for the detection and treatment of patients with heterozygous
familial hypercholesterolaemia

 

 

ASCVD = atherosclerotic cardiovascular disease; CHD = coronary heart disease;
CVD = cardiovascular disease; FH = familial hypercholesterolaemia; HoFH =
homozygous FH; LDL-C = low-density lipoprotein cholesterol; PCSK9 = proprotein
convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for the detection and treatment of patients with heterozygous
familial hypercholesterolaemia

 

 

ASCVD = atherosclerotic cardiovascular disease; CHD = coronary heart disease;
CVD = cardiovascular disease; FH = familial hypercholesterolaemia; HoFH =
homozygous FH; LDL-C = low-density lipoprotein cholesterol; PCSK9 = proprotein
convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

9.1.2.2 HOMOZYGOUS FAMILIAL HYPERCHOLESTEROLAEMIA.

HoFH is a rare and life-threatening disease. The clinical picture is
characterized by extensive xanthomas, marked premature and progressive CVD, and
TC >13 mmol/L (>500 mg/dL). Most patients develop CAD and aortic stenosis before
the age of 20 years and die before 30 years of age. The frequency of HoFH is
estimated to be 1/160 000–1/320 000. The early identification of these children
and prompt referral to a specialized clinic is crucial. The patients should be
treated with intensive LDL-lowering drug therapy and, when available, with
lipoprotein apheresis. This treatment (every 1–2 weeks) can decrease plasma
LDL-C levels by 55–70%. The procedure frequency may be adjusted for each patient
as lipid levels, symptoms, and other disease-related parameters change.
Maximally tolerated pharmacological therapy must be maintained.368 For a more
detailed discussion on HoFH, see the EAS consensus statements.366,368

9.1.2.3 FAMILIAL HYPERCHOLESTEROLAEMIA IN CHILDREN.

FH is diagnosed in children based on phenotypic criteria including elevated
LDL-C plus a family history of elevated LDL-C, premature CAD, and/or positive
genetic testing.369 Testing during childhood is optimal to discriminate between
FH and non-FH using LDL-C. In children with a family history of high cholesterol
or premature CHD, an accepted cut-off is ≥4.0 mmol/L (≥160 mg/dL). If a parent
has a known genetic defect, the diagnostic level for the child is ≥3.5 mmol/L
(≥130 mg/dL). If possible, genetic testing of the child is suggested.

Although there have been no placebo-controlled trials in children, observational
studies have suggested that early treatment can reduce LDL-C burden, improve
endothelial function, substantially attenuate the development of
atherosclerosis, and improve coronary outcomes.369–371 Treatment of children
with FH includes a healthy lifestyle and statin treatment. A heart-healthy diet
should be adopted early in life and statin treatment should be considered at
6–10 years of age. Statin treatment should be started with low doses and the
dose should be increased to reach goals.372 The goal in children >10 years of
age is an LDL-C <3.5 mmol/L (<135 mg/dL) and at younger ages a ≥50% reduction of
LDL-C.

9.1.3 FAMILIAL DYSBETALIPOPROTEINAEMIA

Familial dysbetalipoproteinaemia (i.e. type III hyperlipoproteinaemia; remnant
removal disease) is rare and is generally inherited as an autosomal recessive
disorder with variable penetrance. Familial dysbetalipoproteinaemia produces a
characteristic clinical syndrome in which both TC and TGs are elevated before
treatment, usually both in the range of 7–10 mmol/L. In severe cases, patients
develop tuberoeruptive xanthomas, particularly over the elbows and knees, and
palmar xanthomata in the skin creases of the hands and wrists. The risk of CAD
is very high, and accelerated atherosclerosis of the femoral and tibial arteries
is also prevalent. The syndrome is usually not expressed at a young age or in
women before menopause. The majority of cases are homozygous for the E2 isoform
of ApoE. ApoE is important for the hepatic clearance of chylomicron remnants and
IDL. ApoE2 binds less readily than the E3 and E4 isoforms to hepatic receptors.
However, without some coincidental cause of dyslipidaemia such as dyslipidaemia
associated with HTG, DM, obesity, or hypothyroidism,373–375 ApoE2 homozygosity
does not generally cause familial dysbetalipoproteinaemia.

The detection of ApoE2 homozygosity in a dyslipidaemic patient is diagnostic and
analysis of ApoE isoforms is now available in most clinical laboratories. The
presence of cholesterol remnants characteristic of familial
dysbetalipoproteinaemia can be reliably predicted on the basis of plasma levels
of cholesterol, TGs, and ApoB.376 If suspicion is confirmed, ApoE genotyping can
be performed. In older patients with xanthomata resembling those of familial
dysbetalipoproteinaemia who prove not to be homozygous for ApoE2, a paraprotein
should be sought. The treatment of familial dysbetalipoproteinaemia should be
undertaken in a specialist clinic. Most cases respond well to treatment with a
statin or, if dominated by high TGs, a fibrate; often a combination of a statin
and a fibrate may be needed.

9.1.4 GENETIC CAUSES OF HYPERTRIGLYCERIDAEMIA

Although the genetic aetiology for HTG seems to be very complex, recent data
have extended our genetic understanding of HTG, in particular that of
chylomicronaemia.37,226,377 Moderate elevation of TG levels (between 2.0–10.0
mmol/L) is caused by the polygenic effect of multiple genes influencing both
VLDL production and removal. Monogenic severe HTG causes chylomicronaemia,
pancreatitis, and lipid deposits. Thus far, mutations in six genes (LPL, apoC2,
apoA5, LMF1, GPIHBP1, and GPD1) with monogenic effects have been recognized to
lead to severe elevation of serum TGs due to disruption of the chylomicron
removal pathways. These mutations are inherited as autosomal recessive traits
and are rare. The profound defect in the catabolism of chylomicrons and VLDL
results in chylomicronaemia and TG levels >11.2 mmol/L (>1000 mg/dL), with
turbid and milky serum. Severe HTG is seen in patients who are homozygous or
compound heterozygous for mutations of the enzyme LPL, and in other genes linked
to the catabolism of TG-rich lipoproteins. Heterozygous carriers of these same
gene mutations commonly express moderate elevations of serum TG levels that
expose them to increased CVD risk.378 Recently, gene therapy for LPL deficiency
has been developed and tested in clinical trials,379 and the alipogene
tiparvovec was approved by the EMA in 2013. However, this therapy is no longer
available. A gain-of-function mutation in apoC3 that leads to high ApoC-III
levels can also cause severe HTG by inhibiting the activity of LPL, whereas
loss-of-function mutations are associated with a favourable lipid profile with
low TG levels.380 These findings have raised the possibility of ApoC-III being a
novel lipid drug target.

9.1.4.1 ACTION TO PREVENT ACUTE PANCREATITIS IN SEVERE HYPERTRIGLYCERIDAEMIA.

The risk of pancreatitis is clinically significant if TGs are >10 mmol/L (880
mg/dL), particularly when occurring in association with familial
chylomicronaemia, and actions to prevent acute pancreatitis are
mandatory.381,382 Notably, HTG is the cause of ∼10% of all cases with
pancreatitis, and patients can develop pancreatitis even when their TG
concentration is 5–10 mmol/L (440–880 mg/dL). Recent data from a prospective
cohort study reported that the risk of acute pancreatitis increased
significantly over the quartiles of serum TGs, highlighting the fact that, as a
risk factor, serum TGs may have been underestimated.383 Any factor that
increases VLDL production can aggravate the risk of pancreatitis, with alcohol
consumption being the most common contributing factor. Either a patient should
be admitted to hospital if symptomatic, or careful and close follow-up of the
patient’s TG values should be undertaken. Restriction of calories and fat
content (10–15% recommended) in the diet, and alcohol abstinence are obligatory.
Fibrate therapy (fenofibrate) should be initiated, with n-3 fatty acids (2–4
g/day) as adjunct therapy. Lomitapide may also be considered in severe cases.37
In patients with DM, insulin therapy should be initiated to achieve good
glycaemic control. In general, a sharp decrease of TG values is seen within 2–5
days. In the acute setting, plasmapheresis is able to rapidly lower TG
levels.384 Volanesorsen has been recently approved by the EMA as an adjunct to
diet in adult patients with genetically confirmed FCS who are at high-risk for
pancreatitis.

9.1.5 OTHER GENETIC DISORDERS OF LIPOPROTEIN METABOLISM

Sometimes patients are encountered with extremely low levels of LDL-C or HDL-C.
The most common form of genetic hypolipidaemia is hypobetalipoproteinaemia,
which is dominantly inherited and often due to truncation of ApoB. Serum LDL-C
is typically between 0.5–1.5 mmol/L (20–60 mg/dL). A more profound deficiency of
ApoB occurs in abetalipoproteinaemia when steatorrhoea, and neurological or
other complications require specialist treatment. Almost absent levels of HDL-C
occur in Tangier disease (analphalipoproteinaemia) and very low levels of HDL-C
occur in lecithin cholesterol acyltransferase (LCAT) deficiency. Both these
conditions are associated with distinct clinical syndromes and require
specialist investigation. Very high levels of HDL-C are detected in patients
with CETP deficiency. In the heterozygous form, levels of 2.0–2.3 mmol/L (80–90
mg/dL) are typically observed, and levels ≥5 mmol/L (≥200 mg/dL) are observed in
homozygotes. This is not associated with atherosclerotic disease and may be
associated with reduced risk.

Lysosomal acid lipase deficiency or cholesterol ester storage disease (in
children with Wolman disease) is a rare cause (recessive transmission) of
elevated LDL-C and low HDL-C, accompanied by hepatomegaly and microvesicular
hepatosteatosis. Statin treatment does decrease LDL-C levels and could therefore
prevent ASCVD in these patients, but it cannot stop the progression of liver
damage. Treatment with a PCSK9 inhibitor may lead to an even greater overload of
lysosomes.385 Enzyme replacement therapy with sebelipase alfa might offer a
treatment solution in the near future.386


9.2 WOMEN

Few randomized trials of statin therapy have reported independently significant
CV benefits in women,387,389 chiefly because women have not been adequately
represented in statin trials.

9.2.1 EFFECTS OF STATINS IN PRIMARY AND SECONDARY PREVENTION

There has previously been controversy over whether statins are effective for
primary prevention in women. Using published data, a 2013 Cochrane analysis
showed that statin therapy reduced all-cause mortality, vascular events, and
revascularizations in primary prevention, and the proportional effects in women
were similar to those in men.213 The CTT collaboration has provided a more
complete assessment of the evidence through a comprehensive analysis of IPD from
22 trials of statins vs. control and five trials of more- vs. less-intensive
statin therapy.35 Overall, 46 675 (27%) of 174 149 participants were women, and
after adjustment for non-gender differences, the proportional reductions per
mmol/L reduction in LDL-C in major vascular events, major coronary events,
coronary revascularization, and stroke were similar in women and men.35

9.2.2 NON-STATIN LIPID-LOWERING DRUGS

Definitive evidence of the cardioprotective effects of non-statin drugs that
lower LDL-C is now available, and the beneficial effects are similar in both
women and men. In the IMPROVE-IT study,33 the relative benefit of adding
ezetimibe to simvastatin was similar in women and men.33 In the ACCORD lipid
study, there was no evidence that fenofibrate added to the effects of
simvastatin in patients with T2DM,306 but an analysis of the FIELD study showed
consistent CV event reduction in both women and men.389 Several outcome trials
assessing the effects of adding a PCSK9 inhibitor to high-intensity statin
therapy have now been reported, with similar proportional reductions in major
vascular events in women and men.120,286,290

9.2.3 HORMONE THERAPY

Currently prescribed third-generation, low-dose oestrogen–progestin oral
contraceptives do not appear to increase adverse coronary events390 and can be
used, after baseline lipid profile assessment, in women with acceptable TC
levels. In contrast, alternative contraceptive measures should be recommended in
women with hypercholesterolaemia [LDL-C >4 mmol/L (>160 mg/dL)] or with multiple
risk factors, and in those at high-risk of thrombotic events.391 Oestrogen
replacement therapy, despite some favourable effects on lipid profiles, has not
been demonstrated to reduce CV risk and cannot be recommended for CVD prevention
in women.392 No lipid-lowering drugs should be administered during pregnancy and
the period of breastfeeding because data on possible adverse effects are
lacking. However, bile acid sequestrants may be considered.

Box 6 lists the main measures in the management of dyslipidaemia in women.

Box 6

Management of dyslipidaemia in women

Statin treatment is recommended for primary prevention of ASCVD in high-risk
women.34,35 Statins are recommended for secondary prevention in women with the
same indications and goals as in men.34,35 Lipid-lowering drugs should not be
given when pregnancy is planned, during pregnancy, or during the breastfeeding
period. However, for severe FH patients, bile acid sequestrants (which are not
absorbed) and/or LDL apheresis may be considered. 

Statin treatment is recommended for primary prevention of ASCVD in high-risk
women.34,35 Statins are recommended for secondary prevention in women with the
same indications and goals as in men.34,35 Lipid-lowering drugs should not be
given when pregnancy is planned, during pregnancy, or during the breastfeeding
period. However, for severe FH patients, bile acid sequestrants (which are not
absorbed) and/or LDL apheresis may be considered. 

ASCVD = atherosclerotic cardiovascular disease; FH = familial
hypercholesterolaemia; LDL = low-density lipoprotein.

Open in new tab
Box 6

Management of dyslipidaemia in women

Statin treatment is recommended for primary prevention of ASCVD in high-risk
women.34,35 Statins are recommended for secondary prevention in women with the
same indications and goals as in men.34,35 Lipid-lowering drugs should not be
given when pregnancy is planned, during pregnancy, or during the breastfeeding
period. However, for severe FH patients, bile acid sequestrants (which are not
absorbed) and/or LDL apheresis may be considered. 

Statin treatment is recommended for primary prevention of ASCVD in high-risk
women.34,35 Statins are recommended for secondary prevention in women with the
same indications and goals as in men.34,35 Lipid-lowering drugs should not be
given when pregnancy is planned, during pregnancy, or during the breastfeeding
period. However, for severe FH patients, bile acid sequestrants (which are not
absorbed) and/or LDL apheresis may be considered. 

ASCVD = atherosclerotic cardiovascular disease; FH = familial
hypercholesterolaemia; LDL = low-density lipoprotein.

Open in new tab


9.3 OLDER PEOPLE

The proportion of older people (defined herein as those aged >65 years) in
society is increasing and, as a consequence, >80% of individuals who die from
CVD are >65 years of age. The proportion of patients with MI >85 years of age
has increased several-fold.393

A meta-analysis of observational studies has shown that higher TC is associated
with increased CAD mortality at all ages.62,394 However, since the absolute risk
of CAD is higher in older persons, the associated absolute increase in risk for
a given increment in TC is larger with increasing age.217

9.3.1 EFFECTS OF STATINS IN PRIMARY AND SECONDARY PREVENTION

The use of statin therapy declines with increasing age, reflecting differences
in both prescription and compliance.395,396 This trend is even more prominent
among older patients who do not have evidence of occlusive vascular disease.396
One explanation for this pattern may be uncertainty about the effects of statins
in older people due to the relatively small number of people aged >75 years who
have been included in statin trials.233,397,398 The CTT collaboration recently
provided a comprehensive assessment of the randomized evidence on the effects of
statin therapy at different ages.217 Among 186 854 participants in 28 trials, 14
483 (8%) were aged >75 years at randomization. Overall, statin therapy produced
a 21% relative reduction in major vascular events (relative risk 0.79, 95% CI
0.77–0.81) per 1.0 mmol/L reduction in LDL-C, and there was direct evidence of
benefit among those aged >75 years. The relative reduction in major vascular
events was similar, irrespective of age, among patients with pre-existing
vascular disease, but appeared smaller among older individuals not known to have
vascular disease. Therefore, the available evidence from trials indicates that
statin therapy produces significant reductions in major vascular events
irrespective of age. However, there is less direct evidence of benefit among
patients aged >75 years who do not already have evidence of occlusive vascular
disease, and this limitation is currently being addressed by the STAtin therapy
for Reducing Events in the Elderly (STAREE) trial in Australia.

9.3.2 ADVERSE EFFECTS, INTERACTIONS, AND ADHERENCE

The safety and adverse effects of statins are a matter of special concern in
older adults because they often have comorbidities, take multiple medications,
and have altered pharmacokinetics and pharmacodynamics. Statin–drug interactions
are a concern, primarily because of their potential to increase muscle-related
statin-associated adverse effects such as myalgia without CK elevation, myopathy
with CK elevation, and the rare but serious rhabdomyolysis. It is recommended
that a statin is started at a low dose if there is significant renal impairment
and/or the potential for drug interactions, and then titrated upwards to achieve
LDL-C treatment goals.

The recommendations for the treatment of dyslipidaemias in older people are
shown below.

Recommendations for the treatment of dyslipidaemias in older people (aged >65
years)

 

 

ASCVD = atherosclerotic cardiovascular disease; LDL-C = low-density lipoprotein
cholesterol.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for the treatment of dyslipidaemias in older people (aged >65
years)

 

 

ASCVD = atherosclerotic cardiovascular disease; LDL-C = low-density lipoprotein
cholesterol.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9.4 DIABETES AND METABOLIC SYNDROME

The number of people with DM will increase from ∼415 million today up to 550
million by 2030, but the situation may get even worse.399 Despite significant
advantages in the management strategies that lessen atherosclerotic CVD risk
factors, CVD has remained the leading cause of morbidity and mortality in
patients with T2DM. The good news is that fatal CVD outcomes have declined
significantly in both T1DM and T2DM between 1998 and 2014.400 DM itself is an
independent risk factor for CVD and is associated with a higher risk of CVD,
even more so in women. The difference in CVD risk between individuals with and
without DM has narrowed substantially over the last few decades,401 and there
are strong associations between DM and vascular outcomes.402,403 Recent data
indicate that DM per se increases CVD risk about two-fold on average, but the
risk is subject to wide variation depending on the population and current
aggressive prophylactic therapy.401,404 Importantly, those with DM and CAD are
at substantially higher CVD risk for future events. In T2DM, the risk of ASCVD
is strongly determined by the presence of target organ damage—including
nephropathy (microalbuminuria), neuropathy, or retinopathy—with the risks
increasing in relation to the number of conditions present.405 Hypertension,
dyslipidaemia, abdominal obesity, and non-alcoholic fatty liver disease (NAFLD)
commonly coexist with T2DM and further aggravate the risk, which is highest in
people with T2DM and multiple cardiometabolic risk factors.406–408 Importantly,
DM confers excess mortality risk following ACS despite modern therapies,
highlighting the poor prognosis of coronary patients with T2DM and the need for
intensive therapy.409

How to capture the extra risk beyond the traditional risk factors in clinical
practice is a debated issue. A practical approach is that if one component is
identified, a systematic search should be made for the others.410

9.4.1 SPECIFIC FEATURES OF DYSLIPIDAEMIA IN INSULIN RESISTANCE AND TYPE 2
DIABETES MELLITUS

Diabetic dyslipidaemia is a cluster of plasma lipid and lipoprotein
abnormalities that are metabolically interrelated. The increase in large VLDL
particles in T2DM initiates a sequence of events that generates atherogenic
remnants, small dense LDL, and small TG-rich dense HDL particles.411 These
components are not isolated abnormalities but are closely linked to each other.
Both LDL and HDL particles show variable compositional changes that are
reflected in their functions. Notably, ApoC-III levels are increased in people
with T2DM.412 High ApoC-III concentrations prevent the clearance of both TRLs
and remnants, resulting in prolonged residence times of these particles in the
circulation.413,414 In fact, the defective catabolism of TRLs seems to be a more
important contributor to the elevation of plasma TGs than the increased
production rate leading to an excess of remnant particles. Together, TRL
remnants, small dense LDL, and small dense HDL comprise the atherogenic lipid
profile, which is also characterized by an increase in ApoB concentration due to
an increased number of ApoB-containing particles. Importantly, TRLs—including
chylomicrons, VLDL, and their remnants—carry a single ApoB molecule, also like
LDL particles. Therefore, the malignant nature of diabetic dyslipidaemia is not
always revealed by the lipid measures used in clinical practice, as LDL-C levels
may remain within the normal range. It may be better revealed by non-HDL-C
levels.415 Elevation of TGs or low HDL-C levels in the fasting or post-prandial
state is seen in about one-half of all people with T2DM,416,417 and is also
often present in people with abdominal adiposity, insulin resistance or impaired
glucose tolerance.413

Box 7 summarizes dyslipidaemia in MetS and T2DM.

Box 7

Summary of dyslipidaemia in metabolic syndrome and type 2 diabetes mellitus

Dyslipidaemia represents a cluster of lipid and lipoprotein abnormalities,
including elevation of both fasting and post-prandial TG, ApoB, and small dense
LDL, and low HDL-C and ApoA1 levels. Non-HDL-C or ApoB are good markers of TRLs
and remnants, and are a secondary objective of therapy. Non-HDL-C <2.6 mmol/L
(<100 mg/dL) and ApoB <80 mg/dL are desirable in those at high-risk, and
non-HDL-C <2.2 mmol/L (<85 mg/dL) and ApoB <65 mg/dL in those at very high-risk.
For those at very high-risk with recurrent ASCVD events, a goal of non-HDL-C
<1.8 mmol/L (<70 mg/dL) and ApoB <55 mg/dL may be considered. Atherogenic
dyslipidaemia is one of the major risk factors for CVD in people with type 2
diabetes, and in people with abdominal obesity and insulin resistance or
impaired glucose tolerance. 

Dyslipidaemia represents a cluster of lipid and lipoprotein abnormalities,
including elevation of both fasting and post-prandial TG, ApoB, and small dense
LDL, and low HDL-C and ApoA1 levels. Non-HDL-C or ApoB are good markers of TRLs
and remnants, and are a secondary objective of therapy. Non-HDL-C <2.6 mmol/L
(<100 mg/dL) and ApoB <80 mg/dL are desirable in those at high-risk, and
non-HDL-C <2.2 mmol/L (<85 mg/dL) and ApoB <65 mg/dL in those at very high-risk.
For those at very high-risk with recurrent ASCVD events, a goal of non-HDL-C
<1.8 mmol/L (<70 mg/dL) and ApoB <55 mg/dL may be considered. Atherogenic
dyslipidaemia is one of the major risk factors for CVD in people with type 2
diabetes, and in people with abdominal obesity and insulin resistance or
impaired glucose tolerance. 

Apo = apolipoprotein; ASCVD = atherosclerotic cardiovascular disease; CVD =
cardiovascular disease; HDL-C = high-density lipoprotein cholesterol; LDL-C =
low-density lipoprotein cholesterol; TG = triglyceride; TRLs = triglyceride-rich
lipoproteins.

Open in new tab
Box 7

Summary of dyslipidaemia in metabolic syndrome and type 2 diabetes mellitus

Dyslipidaemia represents a cluster of lipid and lipoprotein abnormalities,
including elevation of both fasting and post-prandial TG, ApoB, and small dense
LDL, and low HDL-C and ApoA1 levels. Non-HDL-C or ApoB are good markers of TRLs
and remnants, and are a secondary objective of therapy. Non-HDL-C <2.6 mmol/L
(<100 mg/dL) and ApoB <80 mg/dL are desirable in those at high-risk, and
non-HDL-C <2.2 mmol/L (<85 mg/dL) and ApoB <65 mg/dL in those at very high-risk.
For those at very high-risk with recurrent ASCVD events, a goal of non-HDL-C
<1.8 mmol/L (<70 mg/dL) and ApoB <55 mg/dL may be considered. Atherogenic
dyslipidaemia is one of the major risk factors for CVD in people with type 2
diabetes, and in people with abdominal obesity and insulin resistance or
impaired glucose tolerance. 

Dyslipidaemia represents a cluster of lipid and lipoprotein abnormalities,
including elevation of both fasting and post-prandial TG, ApoB, and small dense
LDL, and low HDL-C and ApoA1 levels. Non-HDL-C or ApoB are good markers of TRLs
and remnants, and are a secondary objective of therapy. Non-HDL-C <2.6 mmol/L
(<100 mg/dL) and ApoB <80 mg/dL are desirable in those at high-risk, and
non-HDL-C <2.2 mmol/L (<85 mg/dL) and ApoB <65 mg/dL in those at very high-risk.
For those at very high-risk with recurrent ASCVD events, a goal of non-HDL-C
<1.8 mmol/L (<70 mg/dL) and ApoB <55 mg/dL may be considered. Atherogenic
dyslipidaemia is one of the major risk factors for CVD in people with type 2
diabetes, and in people with abdominal obesity and insulin resistance or
impaired glucose tolerance. 

Apo = apolipoprotein; ASCVD = atherosclerotic cardiovascular disease; CVD =
cardiovascular disease; HDL-C = high-density lipoprotein cholesterol; LDL-C =
low-density lipoprotein cholesterol; TG = triglyceride; TRLs = triglyceride-rich
lipoproteins.

Open in new tab

9.4.2 EVIDENCE FOR LIPID-LOWERING THERAPY

9.4.2.1 LOW-DENSITY LIPOPROTEIN CHOLESTEROL.

LDL-C is the primary target of lipid-lowering therapy in patients with DM.
Trials specifically performed in people with T2DM, as well as subsets of
individuals with DM in major statin trials, have consistently demonstrated
significant benefits of statin therapy on CVD events in people with T2DM.418
Statin therapy reduces the 5 year incidence of major CVD events by 23% per 1
mmol/L reduction in LDL-C, regardless of the initial LDL-C level or other
baseline characteristics based on meta-analysis.418 The CTT meta-analysis
further indicates that people with T2DM will have a relative risk reduction that
is comparable to that seen in non-diabetic patients; however, being at higher
absolute risk, the absolute benefit will be greater, resulting in a lower number
needed to treat (NNT). Thus, statin therapy is the first-line treatment for
LDL-C lowering and for the reduction of CVD burden.419

Ezetimibe lowers LDL-C by ∼24% and, when added to statin therapy, decreases the
risk of major vascular events.33 The relative risk reduction in major vascular
events is proportional to the absolute degree of LDL-C lowering and consistent
with the relationship seen for statins. The subset of patients with DM in
IMPROVE-IT had, as expected, a higher rate of major vascular events than
patients without DM (46 vs. 31% 7 year Kaplan–Meier rate in the placebo arm).
Ezetimibe appeared particularly efficacious in patients with DM, with a relative
risk reduction of 15% (95% CI 6–22%) and an absolute risk reduction of 5.5%.299

The mAb PCSK9 inhibitors evolocumab and alirocumab lower LDL-C levels by ∼60%
and, when added to statin therapy, decrease the risk of major vascular
events.119 In the FOURIER study, the relative risk reduction for major vascular
events was similar in patients with and without DM; however, given the higher
baseline risk in patients with DM, the absolute risk reductions tended to be
greater in patients with DM (2.7% absolute decrease in major vascular events
over 3 years).297 Of note, the achieved LDL-C in the evolocumab arm was 0.8
mmol/L. The same benefits were also recently demonstrated for diabetic patients
after ACS in the ODYSSEY trial.420

Recent studies have suggested an increased incidence of DM in patients treated
with statins.247 These observations have been seen in Mendelian randomization
studies and in clinical trials, although the effect appears greatest in patients
already at high risk for DM (e.g. those with pre-diabetes). These observations
should not lessen our attention to the treatment of patients, as the overall
benefits in CV event reduction remain and greatly outweigh the increased
incidence of DM. In RCTs, neither ezetimibe nor the PCSK9 inhibitors have been
reported to increase the risk of DM.297

9.4.2.2 TRIGLYCERIDES AND HIGH-DENSITY LIPOPROTEIN CHOLESTEROL.

Lifestyle modification provides the first option to improve atherogenic
dyslipidaemia due to its multifaceted effects. Weight loss is, in most cases,
the most effective measure since it is associated with very pronounced effects
on plasma TG and HDL levels, together with a modest decrease in TC and LDL-C
levels. Moderate-to-heavy aerobic exercise is also associated with improvement
of the plasma lipid profile by reducing TG levels and increasing HDL-C
concentrations. In relation to diet composition, besides the need to eliminate
trans fat, the available evidence supports the reduction of saturated fat intake
and its substitution with unsaturated fat, as well as the replacement of a major
proportion of refined starchy foods and simple sugars with fibre-rich foods like
fruits, vegetables, and wholegrains.179

The clinical benefits achieved by the treatment of high TG and low HDL-C levels
(frequently seen with DM) are still a matter of debate, as the effects of
fenofibrate therapy on the major outcome (MACE) remained negative in both the
FIELD and the ACCORD studies performed in T2DM cohorts.306,307 In a post hoc
analysis of the FIELD study, fenofibrate reduced CVD events by 27% in those with
elevated TGs [∼2.3 mmol/L (200 mg/dL)] and increased HDL-C levels (NNT = 23).416
The ACCORD trial confirmed the following: patients who had both TG levels in the
higher third [∼2.3 mmol/L (200 mg/dL)] and an HDL-C level in the lower third
[≤0.4 mmol/L (≤34 mg/dL)], representing 17% of all participants, appeared to
benefit from the addition of fenofibrate to simvastatin.306

Recently, post-trial follow-up of the ACCORD lipid trial participants reported
the beneficial effect of fenofibrate in people with HTG and low HDL-C levels at
baseline.421 Consistent with these findings, a meta-analysis of fibrates in the
prevention of CVD in 11 590 people with T2DM showed that fibrates significantly
reduced the risk of non-fatal MI by 21%, but had no effect on the risk of
overall mortality or coronary mortality.422 In CV outcome trials of fibrates,
the risk reduction has appeared to simply be proportional to the degree of
non-HDL-C lowering.50

Overall, available data indicate that diabetic patients with atherogenic
dyslipidaemia may derive clinical benefits from TG-lowering therapy as an add-on
to statin treatment.354 The ongoing PROMINENT trial is exploring the efficacy of
pemafibrate, a new selective PPAR-α modulator, in reducing CVD outcomes in ∼10
000 diabetic patients with atherogenic dyslipidaemia on a statin.317,423

There are limited data on the impacts on CVD of adding omega-3 fatty acids to
statin therapy in patients with high plasma TG levels who are treated with
statins. The REDUCE-IT trial examined the effects of icosapent ethyl 2 g b.i.d.
on CV events in 8179 high-risk patients with HTG who were taking a statin. Over
a median of 4.9 years, there was a significant (P < 0.001) 25% reduction in the
composite primary outcome of CV death, non-fatal MI, non-fatal stroke, coronary
revascularization, or unstable angina, corresponding with an absolute reduction
of 4.8%, which was offset by a 1% increased absolute risk of hospitalization for
atrial fibrillation or flutter.194 The STRENGTH trial is investigating the
effect of omega-3 fatty acids, in addition to a statin, in individuals with HTG
and low HDL-C levels who are at high-risk for CVD. The ASCEND trial was a
randomized 2×2 factorial design study of aspirin and omega-3 fatty acid
supplements for the primary prevention of CV events in people with DM, but not
specifically with HTG. Among 15 480 people randomized to omega-3 fatty acid
supplements vs. placebo over a mean follow-up of 7.4 years, there was no
significant effect (HR 0.97, 95% CI 0.87–1.08) on serious vascular events
[non-fatal MI, non-fatal stroke, transient ischaemic attack (TIA), or vascular
death].329,424–426

9.4.3 TYPE 1 DIABETES MELLITUS

T1DM is associated with high CVD risk, in particular in patients with
microalbuminuria and renal disease.427 Conclusive evidence supports the
proposition that hyperglycaemia accelerates atherosclerosis. Emerging evidence
highlights the frequent coexistence of MetS with T1DM, resulting in the
so-called double diabetes increasing CVD risk.428

The lipid profile in T1DM patients with good glycaemic control is ‘supernormal’,
and is characterized by subnormal TG and LDL-C levels, whereas HDL-C levels are
usually within the upper normal range or slightly elevated. This is explained by
subcutaneous administration of insulin that increases LPL activity in adipose
tissue and skeletal muscle, and consequently the turnover rate of VLDL
particles.429 However, there are potentially atherogenic changes in the
compositions of both HDL and LDL particles.

Consistent data have demonstrated the efficacy of statins in preventing CV
events and reducing CV mortality in patients with DM, with no evidence of sex
differences.430,431 A meta-analysis including 18 686 patients with DM
demonstrated that a statin-induced reduction of LDL-C yielded a 9% reduction in
all-cause mortality and a 21% reduction in the incidence of major CV events per
1.0 mmol/L (40mg/dL) lower LDL cholesterol.418 Similar benefits were seen in
patients with T1DM and T2DM. In diabetic patients with ACS, intensive statin
treatment led to a reduction in all-cause mortality and CV death, and
contributed to a reduction in atheroma progression.432

9.4.4 MANAGEMENT OF DYSLIPIDAEMIA FOR PREGNANT WOMEN WITH DIABETES

In both T1DM and young-onset T2DM patients, there is a paucity of evidence to
indicate the age at which statin therapy should be initiated. To guide an
approach, statins are not indicated in pregnancy,433 and should be avoided in
both T1DM and T2DM individuals who are planning pregnancy. If diabetic
individuals aged ≤30 years have no evidence of vascular damage and, in
particular, microalbuminuria, it seems reasonable to delay statin therapy in
asymptomatic patients until the age of 30. Below this age, statin therapy should
be managed on a case-by-case basis, taking into account the presence of
microalbuminuria, end organ damage, and ambient LDL-C levels.

Recommendations for the treatment of dyslipidaemias in DM are shown in the table
below.

Recommendations for the treatment of dyslipidaemias in diabetes mellitus

 

 

LDL-C = low-density lipoprotein cholesterol; T1DM = type 1 diabetes mellitus;
T2DM = type 2 diabetes mellitus.

a

Class of recommendation.

b

Level of evidence.

c

See Table 6.

Open in new tab

Recommendations for the treatment of dyslipidaemias in diabetes mellitus

 

 

LDL-C = low-density lipoprotein cholesterol; T1DM = type 1 diabetes mellitus;
T2DM = type 2 diabetes mellitus.

a

Class of recommendation.

b

Level of evidence.

c

See Table 6.

Open in new tab


9.5 PATIENTS WITH ACUTE CORONARY SYNDROMES AND PATIENTS UNDERGOING PERCUTANEOUS
CORONARY INTERVENTION

Patients who present with ACS are at increased risk of experiencing recurrent CV
events. For these patients, lipid management should be undertaken in the context
of a comprehensive global risk reduction strategy including lifestyle
adaptations, risk factor management, and the implementation of cardioprotective
drug strategies. Ideally, patients should be signed up to cardiac rehabilitation
programmes to enhance the control of lipid levels434 and improve overall
survival following ACS.435 Despite the acknowledged clinical benefits of
lowering LDL-C in patients with ACS,436 attainment of LDL-C target values
remains suboptimal in this very high-risk setting.437

9.5.1 LIPID-LOWERING THERAPY IN PATIENTS WITH ACUTE CORONARY SYNDROMES

LDL-C levels tend to decrease during the first days of ACS and therefore a lipid
profile should be obtained as soon as possible after admission for ACS. Patients
do not have to be fasting as this has little impact on LDL-C levels.100
Lipid-lowering treatment should be initiated as early as possible to increase
patient adherence after discharge. Lipid levels should be re-evaluated 4–6 weeks
after ACS to determine whether treatment goals have been achieved and to check
for any safety issues; the therapeutic regimen can then be adapted accordingly.

9.5.1.1 STATINS.

Data from RCTs and meta-analyses indicate that routine early use of
high-intensity statin therapy is associated with rapid and sustained clinical
benefits.438–442 We recommend the initiation of high-intensity statin therapy in
all statin-naïve ACS patients with no contraindication, regardless of initial
LDL-C values; the treatment goal is to reach a 50% LDL-C reduction from baseline
and an LDL-C goal of <1.4 mmol/L (<55 mg/dL). In those with recurrent events
within 2 years while taking maximally tolerated statin therapy, a goal of <1.0
mmol/L (<40 mg/dL) for LDL-C should be considered. The intensity of statin
therapy should be increased in those patients receiving low- or
moderate-intensity statin treatment at presentation, unless there is a definite
history of intolerance to high-intensity statin therapy. The use of
lower-intensity statin therapy should be considered in patients at increased
risk of adverse effects with high-intensity statin therapy, such as in the
elderly, patients diagnosed with hepatic or renal impairment, or in the case of
a potential risk of drug–drug interactions with other essential concomitant
therapies.

Regarding the timing of statin treatment initiation, the Statins Evaluation in
Coronary Procedures and Revascularization (SECURE-PCI) randomized,
placebo-controlled trial recently assessed the impact of peri-procedural loading
with atorvastatin [two loading doses of 80 mg, before and 24 h after the planned
percutaneous coronary intervention (PCI)] on MACE at 30 days in 4191 patients
with ACS and planned invasive management.443 All patients received atorvastatin
40 mg per day starting 24 h after the second loading dose. The authors found no
significant treatment benefit in the overall study population. In a
pre-specified analysis, a significant 28% relative risk reduction in MACE was
observed among patients who underwent PCI (65% of all patients). The benefit was
even more pronounced (46% relative risk reduction) in a post hoc analysis
including 865 ST-elevation MI (STEMI) patients undergoing reperfusion by primary
PCI.443 Based on current evidence, we recommend the initiation of high-intensity
statin therapy during the first 1–4 days of hospitalization for the index
ACS.438–442 Moreover, pre-treatment (or loading dose for patients already on a
statin) with a high-intensity statin should be considered in ACS patients with
planned invasive management.443

9.5.1.2 EZETIMIBE.

In the IMPROVE-IT trial, the addition of ezetimibe to simvastatin therapy
provided an additional benefit (6.4% relative risk reduction in the composite
clinical endpoint) to post-ACS patients.33 The clinical benefit of adding
ezetimibe was consistent across patient subgroups299,444 and also led to a
reduction of total CV events,445 stroke,446 and rehospitalizations.447 Patients
at higher atherothrombotic risk [as assessed by the TIMI (Thrombolysis In
Myocardial Infarction) risk score for secondary prevention] benefitted the most
from the addition of ezetimibe.448 In another randomized, open-label trial
including 1734 patients with ACS, the addition of ezetimibe to
moderate-intensity statin (pitavastatin 2 mg) therapy failed to improve outcomes
overall, but did reduce the composite primary endpoint (death, MI, stroke,
unstable angina, and ischaemia-driven revascularization) during 3.9-year
follow-up in patients with increased intestinal absorption of cholesterol (as
assessed by elevated levels of sitosterol)449; however, this finding requires
further confirmation.

9.5.1.3 PROPROTEIN CONVERTASE SUBTILISIN/KEXIN TYPE 9 INHIBITORS.

In the FOURIER trial, which included 27 564 patients with atherosclerotic CV
disease, the addition of evolocumab to statin therapy (69% high-intensity
therapy) resulted in a 15% relative risk reduction of the composite primary
endpoint throughout a 2.2 year follow-up. Results were consistent in the
subgroup of patients with a history of MI (81% of all patients).119,450 A
subanalysis of the FOURIER trial showed that patients who achieved the lowest
LDL-C values under PCSK9 treatment also had the lowest risk of future MACE.451
In the ODYSSEY Outcomes trial, which included 18 924 patients with recent ACS
(1–12 months prior to enrolment, median 2.6 months), alirocumab added to statin
therapy (89% high-intensity therapy) also resulted in a 15% relative risk
reduction in the primary composite endpoint and was associated with a 15%
relative reduction in all-cause mortality throughout a 2.8 year follow-up.120 No
serious side effects or safety concerns were reported in these two large trials.
The optimal timing of initiating PCSK9 inhibition after ACS and its impact on
clinical outcomes remain to be determined. Regarding the timing of PCSK9
inhibitor treatment initiation, post hoc analyses from the FOURIER trial have
shown that the closer to the event this is done, the better. Treatment
initiation with PCSK9 inhibitors during the acute phase of ACS is under
investigation in the EVOlocumab for Early Reduction of LDL-cholesterol Levels in
Patients With Acute Coronary Syndromes (EVOPACS) trial.452 Based on current
evidence, we recommend the initiation of treatment with PCSK9 inhibitors in
patients with ACS who do not reach their respective LDL-C goals (as outlined in
Table 7) after 4–6 weeks of maximum tolerated statin and ezetimibe therapy. In
patients who present with an ACS and whose LDL-C levels are not at goal, despite
already taking a maximally tolerated statin dose and ezetimibe prior to the
event, the addition of a PCSK9 inhibitor early after the event (during the
hospitalization for the ACS event if possible) should be considered.

9.5.1.4 N-3 POLYUNSATURATED FATTY ACIDS.

Oral supplementation with highly purified n-3 PUFAs reduced mortality in
survivors of MI in one study [Gruppo Italiano per lo Studio della Sopravvivenza
nell'Infarto Miocardico-Prevenzione (GISSI-P)] but failed to affect clinical
outcomes in subsequent trials using contemporary secondary prevention therapies.
A recent meta-analysis of available RCTs showed no reduction in mortality, MI,
or major vascular events associated with n-3 PUFAs, including the subgroup of
patients with known CAD.453 Therefore, routine treatment with n-3 PUFAs cannot
be recommended.

9.5.1.5 CHOLESTERYL ESTER TRANSFER PROTEIN INHIBITORS.

In 2007, a large prospective study using the CETP inhibitor torcetrapib failed
to show any clinical benefit in more than 15 000 high-risk patients, and was
potentially harmful.336 The CETP inhibitors dalcetrapib (in >30 000 patients
with recent ACS65) and evacetrapib (in >12 000 high-risk patients63) were
investigated in 2012 and 2017, respectively. Neither clinical study was able to
show any clinical benefit associated with CETP inhibitors.65 More recently, the
REVEAL study investigated anacetrapib in >30 000 patients with atherosclerotic
vascular disease and resulted in a lower incidence of MACE compared with placebo
after 4 years, with no safety concerns.64 However, this compound was not filed
for marketing authorization.

9.5.2 LIPID-LOWERING THERAPY IN PATIENTS UNDERGOING PERCUTANEOUS CORONARY
INTERVENTION

In a meta-analysis of 13 randomized studies including 3341 patients who were
planned to undergo PCI, pre-treatment with a high-dose statin (statin-naïve
patients, 11 studies) or a high-dose statin loading dose reduced the risk of
MACE (death, MI, or target vessel revascularization) by 44% both for
peri-procedural MI and MACE at 30 days.454 In all but one study, PCI was
performed in the setting of stable angina or in a non-emergency setting in
non-ST elevation ACS (NSTE-ACS). One of the studies that was included in the
meta-analysis showed an improvement in coronary flow when primary PCI was used
for the treatment of STEMI.455 A routine strategy of either short pre-treatment
or loading (on the background of pre-existing therapy) with a high-dose statin
before PCI should be considered in elective PCI or NSTE-ACS.454,456,457

In addition, pre-treatment with a statin has also been shown to reduce the risk
of contrast-induced acute kidney injury after coronary angiography or
intervention.458

Recommendations for lipid-lowering therapy in patients with ACS and patients
undergoing PCI are summarized below.

Recommendations for lipid-lowering therapy in very-high-risk patients with acute
coronary syndromes

 

 

ACS = acute coronary syndrome; LDL-C = low-density lipoprotein cholesterol;
PCSK9 = proprotein convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for lipid-lowering therapy in very-high-risk patients with acute
coronary syndromes

 

 

ACS = acute coronary syndrome; LDL-C = low-density lipoprotein cholesterol;
PCSK9 = proprotein convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9.6 STROKE

Stroke has a heterogeneous aetiology, including cardiac thromboembolism [often
associated with atrial fibrillation, but also of uncertain source (embolic
stroke of undetermined source)], carotid artery and proximal aortic
atherosclerosis and thromboembolism, small-vessel CVD, and intracranial
haemorrhage (including intracerebral and subarachnoid haemorrhage).
Dyslipidaemia may play a variable role in the pathogenesis of stroke according
to the particular aetiology. The relationship between dyslipidaemia and
atherothrombotic events, including ischaemic stroke and TIA, is well recognized,
while the association of dyslipidaemia with other types of stroke is uncertain.
Notwithstanding, concomitant control of other aetiological factors, such as
hypertension, is of paramount importance.

Following ischaemic stroke or TIA, patients are at risk not only of recurrent
cerebrovascular events, but also of other major CV events, including MI.
Secondary prevention therapy with statins reduces the risk of recurrent stroke
(by 12% per mmol/L reduction in LDL cholesterol), MI, and vascular death.459,460
Statin pre-treatment at TIA onset was associated with reduced recurrent early
stroke risk in patients with carotid stenosis in a pooled data analysis,
supporting as-early-as-possible initiation of statins after stroke.460–462
Statin therapy may yield a small increase in the risk of haemorrhagic stroke,
but the evidence regarding this risk is uncertain.34,36,251,252

Recommendations for lipid-lowering therapy in very-high-risk patients undergoing
percutaneous coronary intervention

 

 

ACS = acute coronary syndrome; PCI = percutaneous coronary intervention.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for lipid-lowering therapy in very-high-risk patients undergoing
percutaneous coronary intervention

 

 

ACS = acute coronary syndrome; PCI = percutaneous coronary intervention.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for lipid-lowering therapy for the prevention of atherosclerotic
cardiovascular disease events in patients with prior ischaemic stroke

 

 

ASCVD = atherosclerotic cardiovascular disease; LDL-C = low-density lipoprotein
cholesterol; TIA = transient ischaemic attack.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for lipid-lowering therapy for the prevention of atherosclerotic
cardiovascular disease events in patients with prior ischaemic stroke

 

 

ASCVD = atherosclerotic cardiovascular disease; LDL-C = low-density lipoprotein
cholesterol; TIA = transient ischaemic attack.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9.7 HEART FAILURE AND VALVULAR DISEASES

9.7.1 PREVENTION OF INCIDENT HEART FAILURE IN CORONARY ARTERY DISEASE PATIENTS

Cholesterol lowering with statins reduces the incidence of HF in patients with
CAD (stable CAD or a history of ACS) without previous HF; this has been shown
consistently in RCTs that have compared statin vs. no statin treatment463,464 as
well as more-intensive vs. less-intensive statin therapy.465–468 A large-scale
meta-analysis of primary and secondary prevention RCTs with statins showed a
modest (10%) reduction in first non-fatal HF hospitalizations with statin
treatment, with no effect on HF death within the limited RCT period.469 There is
no evidence that statins can prevent HF of non-ischaemic origin.

9.7.2 CHRONIC HEART FAILURE

Two large RCTs466,470 (mainly including patients with systolic HF), as well as a
meta-analysis of 24 RCTs, have shown no benefit of statin treatment on CV
mortality or stroke;471 a reduction in HF hospitalizations,218,471 as well as a
small reduction in MI, was observed in a pooled analysis of the Controlled
Rosuvastatin Multinational Trial in Heart Failure (CORONA) and GISSI-HF
trials.472 Based on current evidence, routine administration of statins in
patients with HF without other indications for their use (e.g. CAD) is not
recommended. Because there is no evidence of harm in patients on statin
treatment after the occurrence of HF, there is no need for statin
discontinuation for patients already on treatment.

There is no evidence regarding the effect of PCSK9 inhibition in patients with
chronic HF. In the recent PCSK9 clinical outcomes trials, FOURIER119 and ODYSSEY
Outcomes,120 PCSK9 inhibition in patients with atherosclerotic CVD or after an
ACS did not reduce the risk of HF hospitalization. In the BIOlogy Study to
TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) study of 2174 patients
with worsening HF, multivariable analysis revealed a positive linear association
between PCSK9 levels and the risk of mortality, and the composite of mortality
and unplanned HF hospitalization.473 Similarly, there was a negative association
between LDLR levels and mortality, indicating a potential relationship between
the PCSK9–LDLR axis and outcomes among patients with HF that requires further
investigation.473,474

Treatment with n-3 PUFAs 1 g o.d. may confer a small benefit in patients with
chronic HF, as shown by a significant 9% relative risk reduction for mortality
in the GISSI-HF RCT.475

9.7.3 VALVULAR HEART DISEASES

Aortic stenosis increases the risk of CV events and mortality, and frequently
coexists with atherosclerotic CVD. Life-long high levels of LDL-C476 and
Lp(a)477 have been associated with incident aortic valve stenosis and aortic
valve calcification in genetic Mendelian randomization studies. Observational
studies have suggested possible beneficial effects of intensive lipid lowering
in slowing the progression of native valve aortic stenosis.478 However, this has
not been confirmed in RCTs,266,479–481 or in meta-analyses of observational and
randomized trials.482,483 Three modestly sized trials479–481 and one large
randomized trial (SEAS, which included 1873 patients treated with simvastatin 40
mg plus ezetimibe 10 mg or placebo)266 failed to show a reduction in the
clinical progression of aortic stenosis in patients with mild-to-moderate native
valve aortic stenosis. In a post hoc analysis of the SEAS trial, the efficacy of
lipid-lowering therapy in impeding the progression of aortic stenosis increased
with higher pre-treatment LDL-C levels and lower peak aortic jet velocity (i.e.
milder stenosis at baseline).484 Similarly, a post hoc analysis of three RCTs,
including patients without known aortic valve stenosis at baseline [Treating to
New Targets (TNT), Incremental Decrease In End-points Through Aggressive
Lipid-lowering (IDEAL), and Stroke Prevention by Aggressive Reduction in
Cholesterol Levels (SPARCL)] showed no impact of high-dose vs. usual-dose statin
therapy on the incidence of aortic valve stenosis.485 In patients who underwent
transcatheter aortic valve replacement, statin therapy was associated with
improved outcomes in a small observational study.486

Aortic valve sclerosis (calcification of the aortic leaflets without significant
transvalvular pressure gradient) is associated with an increased risk of CAD
even in the absence of increased risk profiles. Whether or not statins may be
useful both for aortic valve disease and CAD progression in such patients
warrants further investigation.487

Recommendations for lipid-lowering therapy in patients with HF and valvular
diseases are shown below.

Recommendations for the treatment of dyslipidaemias in chronic heart failure or
valvular heart diseases

 

 

CAD = coronary artery disease; HF = heart failure.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for the treatment of dyslipidaemias in chronic heart failure or
valvular heart diseases

 

 

CAD = coronary artery disease; HF = heart failure.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9.8 CHRONIC KIDNEY DISEASE

CKD is defined as abnormalities of kidney structure or function, present for >3
months, with implications for health. CKD is classified on the basis of the
cause, GFR category, and category of albuminuria.488 In the adult population,
decreasing GFR is associated with increased CVD risk, independent of other CV
risk factors.489–492 There is an increased risk of both atherosclerotic vascular
disease and structural heart disease.492 Patients with CKD and established CVD
have a much higher mortality rate compared with patients with CVD and normal
renal function.493 Therefore, patients with CKD are considered to be at high
(stage 3 CKD) or very-high risk (stage 4–5 CKD or on dialysis) of CVD, and there
is no need to use risk estimation models in these patients.

9.8.1 LIPOPROTEIN PROFILE IN CHRONIC KIDNEY DISEASE

In the initial stages of CKD, TG levels are specifically elevated and HDL-C
levels are lowered. LDL subclasses display a shift to an excess of small dense
LDL particles. Studies suggest that the kidney has a role in Lp(a) catabolism
and that Lp(a) levels are increased in association with kidney disease. Such
acquired abnormalities can be reversed by kidney transplantation or remission of
nephrosis.

9.8.2 EVIDENCE FOR RISK REDUCTION THROUGH STATIN-BASED THERAPY IN PATIENTS WITH
CHRONIC KIDNEY DISEASE

In the Die Deutsche Diabetes Dialyse Studie (4D) trial, which involved 1200
patients with diabetes on haemodialysis, atorvastatin had no significant effect
on risk of CVD.220 Similar results were obtained in the AURORA (A study to
evaluate the Use of Rosuvastatin in subjects On Regular haemodialysis: an
Assessment of survival and cardiovascular events) trial, which involved 2776
patients on haemodialysis.221

In the SHARP study,222 simvastatin and ezetimibe combination therapy reduced the
risk for major atherosclerotic events (coronary death, MI, non-haemorrhagic
stroke, or any revascularization) compared with placebo in persons with CKD
stage 3A–5. The trial did not have sufficient power to separately assess the
effects on the primary outcome in dialysis and non-dialysis patients. Although
statin-based therapy is clearly effective in mild-to-moderate CKD, a major
controversy that remained after the publication of the 4D, AURORA, and SHARP
studies was whether statin therapy is effective in more advanced CKD,
particularly dialysis patients. By combining data from the three CKD trials with
other trials in the existing database, the CTT investigators found that, even
after adjusting for the smaller LDL-C reductions achieved among patients with
more advanced CKD and for differences in outcome definitions between dialysis
trials, there was a trend towards smaller relative reductions per mmol/L
reduction in LDL-C in major atherosclerotic events as estimated GFR (eGFR)
declines (with little evidence of benefit among dialysis patients).214 This
diminution in relative risk reduction as GFR declines implies that, at least in
non-dialysis patients, more intensive LDL-lowering regimens are required to
achieve the same benefit.

9.8.3 SAFETY OF LIPID MANAGEMENT IN PATIENTS WITH CHRONIC KIDNEY DISEASE

Safety issues and dose adjustments are important in advanced stages of CKD
(stages 3–5), as adverse events are commonly dose-related and due to increased
blood concentrations of compounds. Although it has been suggested that
preference should be given to regimens and doses that have been shown to be
beneficial in RCTs conducted specifically in such patients,494 the CTT
meta-analysis makes clear that the goal—as in patients without CKD—should be to
achieve the largest possible absolute reduction in LDL-C safely. Although there
were no specific safety concerns raised by the 4D, AURORA, or SHARP trials,
statins metabolized via CYP3A4 may result in adverse effects due to drug–drug
interactions and caution is required.

Based on the evidence for lipid management in patients with CKD, the Kidney
Disease: Improving Global Outcomes (KDIGO) organization has developed an updated
clinical practice guideline for lipid management in CKD.494 In line with this,
but with a focus on those patients at high or very-high risk for developing CVD,
recommendations are summarized below.

Recommendations for lipid management in patients with moderate-to-severe (Kidney
Disease Outcomes Quality Initiative stages 3–5) chronic kidney disease

 

 

ASCVD = atherosclerotic cardiovascular disease; CKD = chronic kidney disease;
eGFR = estimated glomerular filtration rate.

a

Class of recommendation.

b

Level of evidence.

c

Defined as eGFR < 60ml/min/1.73m2 on two measurements more than 3 months apart.

Open in new tab

Recommendations for lipid management in patients with moderate-to-severe (Kidney
Disease Outcomes Quality Initiative stages 3–5) chronic kidney disease

 

 

ASCVD = atherosclerotic cardiovascular disease; CKD = chronic kidney disease;
eGFR = estimated glomerular filtration rate.

a

Class of recommendation.

b

Level of evidence.

c

Defined as eGFR < 60ml/min/1.73m2 on two measurements more than 3 months apart.

Open in new tab


9.9 TRANSPLANTATION

Dyslipidaemias are very common in patients who have undergone heart, lung,
liver, kidney, or allogenic haematopoietic stem cell transplantation, and
predispose such patients to an increased risk of developing ASCVD and transplant
arterial vasculopathy.497–501 In patients with CKD undergoing renal
transplantation, the risk of ASCVD may be determined, at least in part, by the
increased risk resulting from CKD itself.

Immunosuppressive drug regimens may have adverse effects on lipid metabolism
leading to increases in TC, VLDL, and TGs, and in the size and density of LDL
particles. These effects vary with different immunosuppressive
drugs.497,498,502–506

The management of dyslipidaemias in transplant recipients is comparable to what
is recommended for patients at high or very high ASCVD risk, although more
attention is needed regarding the causes of the lipid disturbances and possible
side effects due to drug–drug interactions (see Recommendations for low-density
lipoprotein in solid organ transplant patients below).

The clinical effectiveness of statins in renal transplant patients is uncertain
owing to a lack of randomized trials in this population. A systematic review of
the benefits and harms of statins in patients with a functioning kidney
transplant included 3465 patients, free of CHD, from 22 studies. Although the
authors concluded that statins may reduce CV events, they also suggested a need
for additional studies.253 However, in patients with a functioning renal
transplant at increased risk of CVD, it may be appropriate to extrapolate from
the clear evidence of benefit from statin therapy, without safety concerns, in
people with moderate reductions in GFR.214

Several potential drug interactions must also be considered, especially with
ciclosporin, which is metabolized through CYP3A4, and may increase systemic
statin exposure and the risk of myopathy. Ciclosporin increases the blood levels
of all statins.

Fluvastatin, pravastatin, pitavastatin, and rosuvastatin are metabolized through
different CYP enzymes than the others and have less potential for
interaction.507

Tacrolimus is also metabolized by CYP3A4, but appears to have less potential for
harmful interaction with statins than ciclosporin. Other drugs that influence
CYP3A4 activity should be avoided if possible, and used with extreme caution in
patients receiving both calcineurin inhibitors and statins.

For transplant patients with dyslipidaemia, ezetimibe could be considered as an
alternative for patients unable to take a statin or added to the highest
tolerated statin dose.507–509 No outcome data are available for this drug, which
should generally be reserved for second-line use. Ciclosporin can induce a
2–12-fold increase in the ezetimibe level.

Care is required with the use of fibrates, as they can decrease ciclosporin
levels and have the potential to cause myopathy. Extreme caution is required if
fibrate therapy is planned in combination with a statin. Cholestyramine is not
effective as monotherapy in heart transplant patients and has the potential to
reduce absorption of immunosuppressants; this potential is minimized by separate
administration.

Recommendations for low-density lipoprotein lowering in solid organ transplant
patients

 

 

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for low-density lipoprotein lowering in solid organ transplant
patients

 

 

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9.10 PERIPHERAL ARTERIAL DISEASE

PAD encompasses all vascular sites, including carotid, vertebral, upper
extremity, mesenteric, renal, and lower extremity arteries. The aorta is often
included in the term.510 PAD is a common manifestation of atherosclerosis and
such patients are at elevated risk of coronary events, with PAD representing an
independent risk factor for MI and CV death.510,511 Patients with PAD are at
very-high risk and should be managed according to the recommendations in
Table 7. Elevated CV risk has led to the inclusion of PAD among the list of
‘risk equivalent’ conditions, and therapeutic strategies of secondary prevention
should be implemented [see Recommendations for lipid-lowering drugs in patients
with peripheral arterial disease (including carotid artery disease) below]. Yet,
despite the high CV morbidity and mortality risk, PAD patients are usually
inadequately managed compared with CAD patients.511

9.10.1 LOWER EXTREMITY ARTERIAL DISEASE

A low ABI (0.90) is diagnostic for lower extremity arterial disease (LEAD).
Either a low (0.90) or high (1.40, related to stiffened arteries) ABI is
predictive of CV morbidity and mortality. Lowering LDL-C levels reduces the risk
of ischaemic CV events and worsening of claudication, while it also improves
walking performance. As for cardiac events, a systematic review of 18 trials
including 10 000 patients, with cholesterol levels ranging from normal to
elevated, reported that lipid-lowering therapy in people affected by
atherosclerosis of the lower limbs was associated with a 20% reduction in total
CV events, together with a non-significant 14% reduction of all-cause
mortality.512 In the Heart Protection Study, the need for non-coronary
revascularization was reduced by 16% with statin therapy.513

In addition to statins, PSCK9 inhibitors have also been shown to reduce CV
events in PAD patients. In a pre-specified subgroup analysis of the FOURIER
trial, evolocumab significantly reduced the primary endpoint in patients with
PAD.514 PAD had larger absolute risk reductions for the primary endpoint (3.5%
with PAD and 1.6% without PAD). Evolocumab also reduced the risk of major
adverse limb events by 42% in patients, with consistent effects in those with
and without known PAD. In the FIELD trial, fenofibrate reduced the risk of
amputations, particularly minor amputations without known large-vessel disease,
probably through non-lipid mechanisms.515

9.10.2 CAROTID ARTERY DISEASE

While there are currently no randomized studies that have assessed whether
lipid-lowering treatments reduce the incidence of CV events in patients enrolled
on the basis of carotid atherosclerotic disease and without previous CV events,
lipid-lowering therapy had reduced stroke in numerous studies. In a
meta-analysis of RCTs enrolling >90 000 patients, statin therapy did lead to a
21% reduction in the incidence of all strokes in different populations; this
effect was mainly driven by the extent of LDL-C reduction.460

9.10.3 RETINAL VASCULAR DISEASE

Atherosclerotic changes of retinal arteries correlate with TC, LDL-C, TG, and
apoB levels and also with CAD.516 Fenofibrate reduces the progression of
diabetic retinopathy.517,518

9.10.4 SECONDARY PREVENTION IN PATIENTS WITH ABDOMINAL AORTIC ANEURYSM

The presence of an abdominal aortic aneurysm represents a risk-equivalent
condition for CAD and is associated with age, male gender, personal history of
atherosclerotic CVD, smoking, hypertension, and dyslipidaemia;519 in contrast,
diabetic patients are at decreased risk.

There are currently no available clinical trials on the reduction of CV risk
with lipid-lowering therapy in patients affected by this condition. Systematic
reviews,520 mostly based on retrospective non-randomized studies, have reported
that there is still inconclusive evidence that statin therapy reduces
peri-operative CV morbidity and mortality. In an RCT comparing atorvastatin 20
mg with placebo, the composite endpoint of cardiac death, MI, stroke, and
unstable angina was significantly reduced in 100 patients undergoing vascular
non-cardiac surgery, including abdominal aortic aneurysm repair.521 In another
double-blind, placebo-controlled trial in 497 patients undergoing vascular
surgery, peri-operative fluvastatin therapy (80 mg/day) was associated with an
improvement in post-operative cardiac outcome.522

9.10.5 RENOVASCULAR ATHEROSCLEROSIS

Lipid-lowering therapy has never been tested in an RCT in patients affected by
renovascular atherosclerosis; however, a recent non-randomized population-based
study showed that in patients older than 65 years of age with atherosclerotic
renovascular disease raised the hypothesis that such treatment may yield
cardiorenal benefits; the risk of a major cardiorenal composite endpoint (MI,
stroke, HF, acute renal failure, dialysis, and death) was significantly lower in
statin users than in non-users.523

Recommendations for lipid-lowering drugs in patients with peripheral arterial
disease (including carotid artery disease)

 

 

ASCVD = atherosclerotic cardiovascular disease; PAD = peripheral arterial
disease; PCSK9 = proprotein convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

Recommendations for lipid-lowering drugs in patients with peripheral arterial
disease (including carotid artery disease)

 

 

ASCVD = atherosclerotic cardiovascular disease; PAD = peripheral arterial
disease; PCSK9 = proprotein convertase subtilisin/kexin type 9.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


9.11 OTHER SPECIAL POPULATIONS AT RISK OF ATHEROSCLEROTIC CARDIOVASCULAR DISEASE

In general, the effects of lowering LDL-C are determined by the absolute risk of
ASCVD and the achieved reduction in LDL-C, so it is important to identify and
treat all those at increased risk of ASCVD. There are a few specific groups of
patients in whom an underlying disease confers such increased risk, and in
addition in whom the standard treatments may themselves cause dyslipidaemia that
may contribute to the risk of ASCVD. These include: (i) chronic immune-mediated
inflammatory disease, (ii) patients with human immunodeficiency virus (HIV), and
(iii) patients with severe mental illness. The management principles are the
same in these patient groups, but their management may need to address specific
issues related to individual dyslipidaemias and drug safety. Details are
provided in the Supplementary Data document.


10 INFLAMMATION

Recent advances in basic science have established a fundamental role for
low-degree chronic inflammation in mediating all stages of atherosclerosis, from
initiation through progression and, ultimately, to the rupture of plaque and
ensuing thrombotic complications of atherosclerosis. The cellular and molecular
interactions involved during atherogenesis are fundamentally not different from
those in chronic inflammatory–fibroproliferative diseases, such as rheumatoid
arthritis (RA), glomerulosclerosis, or pulmonary fibrosis.525 Almost all cell
types of the immuno-inflammatory system, such as macrophages, and T- and
B-cells, as well as many pro- and anti-inflammatory cytokines and chemokines,
have been identified during the process of atherosclerosis.526

Interestingly, cholesterol accumulation in cells triggers the inflammasome
response and results in the production of inflammatory mediators such as
interleukin (IL)-1β. Numerous animal studies, using the knockout model, have
demonstrated that inflammation and the immune system both play crucial roles
during atherogenesis.527

During inflammatory processes, large numbers of acute-phase proteins have been
identified, and several clinical studies have reported C-reactive protein528 to
be the most useful serum marker of inflammation, even though it has poor
specificity for any particular inflammation process, including atherosclerosis.
The high-sensitivity C-reactive protein diagnostic test was developed to detect
very low levels of C-reactive protein, and thereby enable a more accurate and
precise measure of chronic inflammation compared with standard C-reactive
protein.529 This diagnostic tool differs only in the range of C-reactive protein
levels that it can detect. Several studies have found that elevated levels of
high-sensitivity C-reactive protein in the blood are associated with an
increased risk of CV events and could be used to predict clinical outcomes
independently of cholesterol levels.530,531 Other studies have not been able to
show any relationship between low-grade chronic inflammation, as indicated by
high-sensitivity C-reactive protein levels, and increased risk of CV.532–535
Finally, genetic studies of large population cohorts have not demonstrated that
chronic elevated high-sensitivity C-reactive protein increases the risk of
atherosclerotic events.536 Nevertheless, in some guidelines, high-sensitivity
C-reactive protein has been added to traditional risk factors for prognostic
information, especially for patients at intermediate risk.537,538

Statins have been shown to reduce C-reactive protein secretion by
hepatocytes,539 and a series of clinical trials and post hoc analyses have found
that beneficial outcomes after statin therapy relate both to a reduction in
cholesterol levels and reduced inflammation.540–544 The Justification for the
Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin
(JUPITER) trial542 demonstrated that in primary prevention for individuals with
chronically elevated C-reactive protein (>2 mg/L), statin treatment markedly
reduced CV events.545 It is of note that other lipid-lowering agents, such as
ezetimibe and more recently the anti-PCSK9 mAbs, do not influence
high-sensitivity C-reactive protein levels,546,547 but lead to further
significant reductions in CV events when added to statin therapy.

Specific anti-inflammatory treatment was tested in the Canakinumab
Antiinflammatory Thrombosis Outcome Study (CANTOS) trial.548 In patients with
previous MI and chronic elevated high-sensitivity C-reactive protein levels, all
on optimal medical treatment, including statins, the anti-IL-1β mAb canakinumab
dose-dependently reduced high-sensitivity C-reactive protein and significantly
lowered the rate of recurrent CV events compared with placebo, independently of
the level of lipid lowering. Not surprisingly, there was a slight increase in
the risk of severe and fatal infections associated with canakinumab. This study
was the first to highlight the positive correlation between high-sensitivity
C-reactive protein and CV events, where lower achieved high-sensitivity
C-reactive protein values were directly correlated with a lower risk of future
CV events.548 Nevertheless, the FDA declined to approve canakinumab for CV risk
reduction on the strength of data from the CANTOS study. As canakinumab
treatment has not been tested against anti-PCSK9 mAb and/or ezetimibe added to
statin therapy, the question of residual risk remains for patients with elevated
high-sensitivity C-reactive protein despite achieving very low (below goal)
LDL-C values, and whether patients with very low LDL-C would benefit from
anti-IL-1β treatment or other anti-inflammatory agents. In addition, all
currently recommended lipid-lowering drugs, including anti-PCSK9 mAbs, have
demonstrated beneficial effects on atherosclerotic plaque composition as well as
plaque volume regression; such results are still missing for anti-inflammatory
treatment. Another anti-inflammatory approach using methotrexate was tested in
the Cardiovascular Inflammation Reduction Trial (CIRT).549 Very low-dose
methotrexate (10 mg weekly), a proven anti-inflammatory regimen that reduces
tumour necrosis factor (TNF), IL-6, and C-reactive protein levels and is widely
used in the treatment of RA, was allocated vs. placebo to 7000 stable CAD
patients. This study was stopped prematurely due to futility. Interestingly,
this regimen of methotrexate had no effect on either IL-6 or high-sensitivity
C-reactive protein blood levels in this population, which could explain the
neutral results of this trial.550 Based on the current level of evidence, no
further recommendations on the use of anti-inflammatory agents can be made.551


11 MONITORING OF LIPIDS AND ENZYMES IN PATIENTS ON LIPID-LOWERING THERAPY

Evidence concerning which tests should be carried out to monitor lipids in
patients on treatment is limited. Similar limited evidence applies to tests of
possible toxicity, such as ALT and CK. Recommendations stem from consensus
rather than evidence-based medicine.

Response to therapy can be assessed at 6–8 weeks from initiation of therapy, but
response to lifestyle may take longer. Standard practice for subsequent
follow-up monitoring is 6–12 months, but such monitoring intervals are
arbitrary. As a minimum, LDL-C should be assessed whenever available, but better
management decisions will probably occur if a full lipid profile is performed,
including HDL-C and TGs. Non-HDL-C or ApoB should also be analysed, and used as
a secondary treatment target. A separate issue is the impact of regular lipid
monitoring in promoting patient adherence to lifestyle changes or drug regimens
that impact positively on their health, as found in a range of studies. It is
unclear whether only the process of monitoring is critical in achieving this or
whether a combination of education, regular contact, and adherence assessment is
required.

Where pharmacological lipid-lowering therapy is implemented, safety blood tests
are advised, including ALT and CK at baseline, to identify the limited number of
patients where treatment is contraindicated. CK should be checked in patients at
high-risk for myopathy, such as the very elderly with comorbidities, patients
with antecedents of muscle symptoms, or patients receiving interacting drugs. A
mild and typically transient elevation of ALT is seen in about 2% of patients
and normalization is seen with continuing therapy.240,244,552 Recent reviews are
encouraging regarding the safety of long-term statin therapy and statin-induced
liver injury is reported to be very uncommon.243,244,553–555 ALT is recommended
before the start of statin therapy; routine control of ALT during treatment is
not recommended but should be performed, if indicated, based on clinical
observations. During fibrate therapy, regular ALT control is still recommended.
In patients whose liver function tests increase to above three times the ULN,
explanations such as alcohol ingestion or NAFLD should be sought, and the levels
monitored. If levels remain elevated then lipid-lowering therapy should be
stopped, but may be cautiously reintroduced under monitoring after levels have
returned to normal.

There is no predictive value of routine repeat CK testing for rhabdomyolysis
since the level can increase for many reasons, including muscle injury or excess
muscular exercise. However, CK must be assessed immediately in patients who
present with muscle pain and weakness, and especially in the elderly, and
treatment stopped if CK rises to >10 times the ULN. Strategies to handle CK
elevations are given in Table 13.

Due to the increased frequency of DM during statin treatment,247,249,556,557
regular checks of HbA1c should be considered in patients at high-risk of
developing DM and under high-dose statin treatment. Groups to be considered for
glucose control are the elderly or those with MetS, obesity, or signs of insulin
resistance.

Table 13

Summary of recommendations for monitoring lipids and enzymes in patients, before
and on lipid-lowering therapy

Testing lipids How often should lipids be tested?

 * Before starting lipid-lowering drug treatment, at least two measurements
   should be made, with an interval of 1–12 weeks, with the exception of
   conditions where prompt drug treatment is suggested, such as ACS and very
   high-risk patients.

 How often should a patient’s lipids be tested after starting lipid-lowering
treatment?

 * After starting treatment: 8 (±4) weeks.

 * After adjustment of treatment: 8 (±4) weeks until the goal is achieved.

 How often should lipids be tested once a patient has achieved the target or
optimal lipid level?

 * Annually (unless there are adherence problems or other specific reasons for
   more frequent reviews).

 Monitoring liver and muscle enzymes How often should liver enzymes (ALT) be
routinely measured in patients on lipid-lowering drugs?

 * Before treatment.

 * Once, 8–12 weeks after starting a drug treatment or after dose increase.

 * Routine control of ALT thereafter is not recommended during statin treatment,
   unless symptoms suggesting liver disease evolve. During treatment with
   fibrates, control of ALT is still recommended.

 What if liver enzymes become elevated in a person taking lipid-lowering drugs?
If ALT <3× ULN:

 * Continue therapy.

 * Recheck liver enzymes in 4–6 weeks.

If ALT rises to ≥3× ULN

 * Stop lipid-lowering therapy or reduce dose and recheck liver enzymes within
   4–6 weeks.

 * Cautious reintroduction of therapy may be considered after ALT has returned
   to normal.

 * If ALT remains elevated check for the other reasons.

 How often should CK be measured in patients taking lipid-lowering drugs?

 *   Pre-treatment
   
   * Before starting therapy.
   
   * If baseline CK is >4× ULN, do not start drug therapy; recheck.
   
   

 *   Monitoring:
   
   * Routine monitoring of CK is not necessary.
   
   * Check CK if patient develops myalgia.
   
   

 Be alert regarding myopathy and CK elevation in patients at risk, such as:
elderly patients, those on concomitant interfering therapy, multiple
medications, liver or renal disease, or athletes. What if CK becomes elevated in
a person taking lipid-lowering drugs? Re-evaluate indication for statin
treatment. If ≥4× ULN:

 * If CK >10× ULN: stop treatment, check renal function, and monitor CK every 2
   weeks.

 * If CK <10× ULN: if no symptoms, continue lipid-lowering therapy while
   monitoring CK between 2 and 6 weeks.

 * If CK <10× ULN: if symptoms present, stop statin and monitor normalization of
   CK, before rechallenge with a lower statin dose.

 * Consider the possibility of transient CK elevation for other reasons such as
   exertion.

 * Consider myopathy if CK remains elevated.

 * Consider combination therapy or an alternative drug.

 If <4× ULN:

 * If no muscle symptoms, continue statin (patient should be alerted to report
   symptoms; check CK).

 * If muscle symptoms, monitor symptoms and CK regularly.

 * If symptoms persist, stop statin and re-evaluate symptoms after 6 weeks;
   re-evaluate indication for statin treatment.

 * Consider rechallenge with the same or another statin.

 * Consider low-dose statin, alternate day or once/twice weekly dosing regimen,
   or combination therapy.

 For details on CK elevation and treatment of muscular symptoms during statin
treatment see algorithm in Supplementary Figure 4.     In which patients should
HbA1c or blood glucose be checked?

 * Regular checks of HbA1c or glucose should be considered in patients at
   high-risk of developing diabetes, and on high-dose statin treatment.

 * Groups to be considered for glucose control are the elderly and patients with
   metabolic syndrome, obesity, or other signs of insulin resistance.

 

Testing lipids How often should lipids be tested?

 * Before starting lipid-lowering drug treatment, at least two measurements
   should be made, with an interval of 1–12 weeks, with the exception of
   conditions where prompt drug treatment is suggested, such as ACS and very
   high-risk patients.

 How often should a patient’s lipids be tested after starting lipid-lowering
treatment?

 * After starting treatment: 8 (±4) weeks.

 * After adjustment of treatment: 8 (±4) weeks until the goal is achieved.

 How often should lipids be tested once a patient has achieved the target or
optimal lipid level?

 * Annually (unless there are adherence problems or other specific reasons for
   more frequent reviews).

 Monitoring liver and muscle enzymes How often should liver enzymes (ALT) be
routinely measured in patients on lipid-lowering drugs?

 * Before treatment.

 * Once, 8–12 weeks after starting a drug treatment or after dose increase.

 * Routine control of ALT thereafter is not recommended during statin treatment,
   unless symptoms suggesting liver disease evolve. During treatment with
   fibrates, control of ALT is still recommended.

 What if liver enzymes become elevated in a person taking lipid-lowering drugs?
If ALT <3× ULN:

 * Continue therapy.

 * Recheck liver enzymes in 4–6 weeks.

If ALT rises to ≥3× ULN

 * Stop lipid-lowering therapy or reduce dose and recheck liver enzymes within
   4–6 weeks.

 * Cautious reintroduction of therapy may be considered after ALT has returned
   to normal.

 * If ALT remains elevated check for the other reasons.

 How often should CK be measured in patients taking lipid-lowering drugs?

 *   Pre-treatment
   
   * Before starting therapy.
   
   * If baseline CK is >4× ULN, do not start drug therapy; recheck.
   
   

 *   Monitoring:
   
   * Routine monitoring of CK is not necessary.
   
   * Check CK if patient develops myalgia.
   
   

 Be alert regarding myopathy and CK elevation in patients at risk, such as:
elderly patients, those on concomitant interfering therapy, multiple
medications, liver or renal disease, or athletes. What if CK becomes elevated in
a person taking lipid-lowering drugs? Re-evaluate indication for statin
treatment. If ≥4× ULN:

 * If CK >10× ULN: stop treatment, check renal function, and monitor CK every 2
   weeks.

 * If CK <10× ULN: if no symptoms, continue lipid-lowering therapy while
   monitoring CK between 2 and 6 weeks.

 * If CK <10× ULN: if symptoms present, stop statin and monitor normalization of
   CK, before rechallenge with a lower statin dose.

 * Consider the possibility of transient CK elevation for other reasons such as
   exertion.

 * Consider myopathy if CK remains elevated.

 * Consider combination therapy or an alternative drug.

 If <4× ULN:

 * If no muscle symptoms, continue statin (patient should be alerted to report
   symptoms; check CK).

 * If muscle symptoms, monitor symptoms and CK regularly.

 * If symptoms persist, stop statin and re-evaluate symptoms after 6 weeks;
   re-evaluate indication for statin treatment.

 * Consider rechallenge with the same or another statin.

 * Consider low-dose statin, alternate day or once/twice weekly dosing regimen,
   or combination therapy.

 For details on CK elevation and treatment of muscular symptoms during statin
treatment see algorithm in Supplementary Figure 4.     In which patients should
HbA1c or blood glucose be checked?

 * Regular checks of HbA1c or glucose should be considered in patients at
   high-risk of developing diabetes, and on high-dose statin treatment.

 * Groups to be considered for glucose control are the elderly and patients with
   metabolic syndrome, obesity, or other signs of insulin resistance.

 

ACS = acute coronary syndrome; ALT = alanine aminotransferase; CK = creatine
kinase; ULN = upper limit of normal.

Open in new tab
Table 13

Summary of recommendations for monitoring lipids and enzymes in patients, before
and on lipid-lowering therapy

Testing lipids How often should lipids be tested?

 * Before starting lipid-lowering drug treatment, at least two measurements
   should be made, with an interval of 1–12 weeks, with the exception of
   conditions where prompt drug treatment is suggested, such as ACS and very
   high-risk patients.

 How often should a patient’s lipids be tested after starting lipid-lowering
treatment?

 * After starting treatment: 8 (±4) weeks.

 * After adjustment of treatment: 8 (±4) weeks until the goal is achieved.

 How often should lipids be tested once a patient has achieved the target or
optimal lipid level?

 * Annually (unless there are adherence problems or other specific reasons for
   more frequent reviews).

 Monitoring liver and muscle enzymes How often should liver enzymes (ALT) be
routinely measured in patients on lipid-lowering drugs?

 * Before treatment.

 * Once, 8–12 weeks after starting a drug treatment or after dose increase.

 * Routine control of ALT thereafter is not recommended during statin treatment,
   unless symptoms suggesting liver disease evolve. During treatment with
   fibrates, control of ALT is still recommended.

 What if liver enzymes become elevated in a person taking lipid-lowering drugs?
If ALT <3× ULN:

 * Continue therapy.

 * Recheck liver enzymes in 4–6 weeks.

If ALT rises to ≥3× ULN

 * Stop lipid-lowering therapy or reduce dose and recheck liver enzymes within
   4–6 weeks.

 * Cautious reintroduction of therapy may be considered after ALT has returned
   to normal.

 * If ALT remains elevated check for the other reasons.

 How often should CK be measured in patients taking lipid-lowering drugs?

 *   Pre-treatment
   
   * Before starting therapy.
   
   * If baseline CK is >4× ULN, do not start drug therapy; recheck.
   
   

 *   Monitoring:
   
   * Routine monitoring of CK is not necessary.
   
   * Check CK if patient develops myalgia.
   
   

 Be alert regarding myopathy and CK elevation in patients at risk, such as:
elderly patients, those on concomitant interfering therapy, multiple
medications, liver or renal disease, or athletes. What if CK becomes elevated in
a person taking lipid-lowering drugs? Re-evaluate indication for statin
treatment. If ≥4× ULN:

 * If CK >10× ULN: stop treatment, check renal function, and monitor CK every 2
   weeks.

 * If CK <10× ULN: if no symptoms, continue lipid-lowering therapy while
   monitoring CK between 2 and 6 weeks.

 * If CK <10× ULN: if symptoms present, stop statin and monitor normalization of
   CK, before rechallenge with a lower statin dose.

 * Consider the possibility of transient CK elevation for other reasons such as
   exertion.

 * Consider myopathy if CK remains elevated.

 * Consider combination therapy or an alternative drug.

 If <4× ULN:

 * If no muscle symptoms, continue statin (patient should be alerted to report
   symptoms; check CK).

 * If muscle symptoms, monitor symptoms and CK regularly.

 * If symptoms persist, stop statin and re-evaluate symptoms after 6 weeks;
   re-evaluate indication for statin treatment.

 * Consider rechallenge with the same or another statin.

 * Consider low-dose statin, alternate day or once/twice weekly dosing regimen,
   or combination therapy.

 For details on CK elevation and treatment of muscular symptoms during statin
treatment see algorithm in Supplementary Figure 4.     In which patients should
HbA1c or blood glucose be checked?

 * Regular checks of HbA1c or glucose should be considered in patients at
   high-risk of developing diabetes, and on high-dose statin treatment.

 * Groups to be considered for glucose control are the elderly and patients with
   metabolic syndrome, obesity, or other signs of insulin resistance.

 

Testing lipids How often should lipids be tested?

 * Before starting lipid-lowering drug treatment, at least two measurements
   should be made, with an interval of 1–12 weeks, with the exception of
   conditions where prompt drug treatment is suggested, such as ACS and very
   high-risk patients.

 How often should a patient’s lipids be tested after starting lipid-lowering
treatment?

 * After starting treatment: 8 (±4) weeks.

 * After adjustment of treatment: 8 (±4) weeks until the goal is achieved.

 How often should lipids be tested once a patient has achieved the target or
optimal lipid level?

 * Annually (unless there are adherence problems or other specific reasons for
   more frequent reviews).

 Monitoring liver and muscle enzymes How often should liver enzymes (ALT) be
routinely measured in patients on lipid-lowering drugs?

 * Before treatment.

 * Once, 8–12 weeks after starting a drug treatment or after dose increase.

 * Routine control of ALT thereafter is not recommended during statin treatment,
   unless symptoms suggesting liver disease evolve. During treatment with
   fibrates, control of ALT is still recommended.

 What if liver enzymes become elevated in a person taking lipid-lowering drugs?
If ALT <3× ULN:

 * Continue therapy.

 * Recheck liver enzymes in 4–6 weeks.

If ALT rises to ≥3× ULN

 * Stop lipid-lowering therapy or reduce dose and recheck liver enzymes within
   4–6 weeks.

 * Cautious reintroduction of therapy may be considered after ALT has returned
   to normal.

 * If ALT remains elevated check for the other reasons.

 How often should CK be measured in patients taking lipid-lowering drugs?

 *   Pre-treatment
   
   * Before starting therapy.
   
   * If baseline CK is >4× ULN, do not start drug therapy; recheck.
   
   

 *   Monitoring:
   
   * Routine monitoring of CK is not necessary.
   
   * Check CK if patient develops myalgia.
   
   

 Be alert regarding myopathy and CK elevation in patients at risk, such as:
elderly patients, those on concomitant interfering therapy, multiple
medications, liver or renal disease, or athletes. What if CK becomes elevated in
a person taking lipid-lowering drugs? Re-evaluate indication for statin
treatment. If ≥4× ULN:

 * If CK >10× ULN: stop treatment, check renal function, and monitor CK every 2
   weeks.

 * If CK <10× ULN: if no symptoms, continue lipid-lowering therapy while
   monitoring CK between 2 and 6 weeks.

 * If CK <10× ULN: if symptoms present, stop statin and monitor normalization of
   CK, before rechallenge with a lower statin dose.

 * Consider the possibility of transient CK elevation for other reasons such as
   exertion.

 * Consider myopathy if CK remains elevated.

 * Consider combination therapy or an alternative drug.

 If <4× ULN:

 * If no muscle symptoms, continue statin (patient should be alerted to report
   symptoms; check CK).

 * If muscle symptoms, monitor symptoms and CK regularly.

 * If symptoms persist, stop statin and re-evaluate symptoms after 6 weeks;
   re-evaluate indication for statin treatment.

 * Consider rechallenge with the same or another statin.

 * Consider low-dose statin, alternate day or once/twice weekly dosing regimen,
   or combination therapy.

 For details on CK elevation and treatment of muscular symptoms during statin
treatment see algorithm in Supplementary Figure 4.     In which patients should
HbA1c or blood glucose be checked?

 * Regular checks of HbA1c or glucose should be considered in patients at
   high-risk of developing diabetes, and on high-dose statin treatment.

 * Groups to be considered for glucose control are the elderly and patients with
   metabolic syndrome, obesity, or other signs of insulin resistance.

 

ACS = acute coronary syndrome; ALT = alanine aminotransferase; CK = creatine
kinase; ULN = upper limit of normal.

Open in new tab


12 COST-EFFECTIVENESS OF CARDIOVASCULAR DISEASE PREVENTION BY LIPID MODIFICATION

In 2015, there were >85 million people in Europe living with CVD.558 Aging
populations,559 unhealthy diets, smoking, sedentary lifestyles, increasing
obesity, and diabetes560–563 are the main contributors. CVD cost the European
Union about €210 billion in 2015, one-half of which was in healthcare costs (∼8%
of total healthcare expenditure), and the other half in productivity losses and
informal care.558

In these Guidelines, the Joint Task Force recommends a range of actions to
reduce CVD by targeting plasma lipids, ranging from population-wide initiatives
to promote healthy lifestyles to individual-level interventions to reduce CVD
risk factors, such as unhealthy diets and high lipid levels. Cost-effectiveness
analysis can help target resources for interventions where the net health gain
is greatest in relation to the net resources, and is increasingly required
across Europe.564 However, cost-effectiveness depends on available resources,
the costs of services, and disease risk in the population, and results obtained
in one country might not be valid in another.565 In addition, to fully capture
the long-term effects of interventions, cost-effectiveness studies combining
evidence from RCTs with modelling and limitations in both could affect the
reliability of findings. Here, the evidence for the cost-effectiveness of ASCVD
preventive interventions with respect to lipid modification is summarized;
further scrutiny in view of local circumstances is recommended.

The health impact pyramid summarizes the evidence on the relative effort in
relation to health impact (Figure 5), with interventions with the broadest
impact on populations at the base and interventions requiring considerable
individual effort at the top.566 There is consensus that all the levels of the
pyramid should be targeted but that emphasis should be placed on the lower
levels. This would address the persistent socio-economic divide in CV health
despite major improvements in ASCVD treatment.558

Figure 5
Open in new tabDownload slide

Health impact pyramid.

More than one-half of the reduction in CV mortality over the last three decades
has been attributed to population-level changes in CV risk factors, primarily
reductions in plasma cholesterol, BP levels, and smoking.560–563,567 Lifestyle
changes at the population level may be more cost-effective than lifestyle and
drug interventions at the individual level, particularly when targeted to
populations at increased risk. Awareness and knowledge of how lifestyle risk
factors lead to CVD has increased in recent decades. Moreover, legislation
promoting a healthy lifestyle, such as reduced salt intake and smoking bans, has
been reported to be cost-effective in preventing CVD,568–573 and initiatives to
improve infrastructure and promote physical activity have shown promise.574,575
A number of structural strategies at international, national, and regional
levels combined can substantially reduce CVD morbidity and mortality.576,577
Individual-level interventions to improve diet,578,579 increase physical
activity,580 and stop smoking581 could also be cost-effective.582 However,
suboptimal adherence limits benefits,583,584 and interventions to improve
adherence, such as electronic device reminders to reinforce favourable health
behaviours, are increasingly being investigated.585

All statin regimens and ezetimibe are now generically available across Europe.
There is strong evidence that lowering blood cholesterol levels using low-cost
statins is widely cost-effective586–590 in many categories of patients. For
secondary prevention of CVD, the evidence suggests that statin treatments are
highly cost-effective,586,590,591 and adding low-cost ezetimibe to
high-intensity statin therapy further reduces LDL-C and CVD risk
cost-effectively.592 In primary ASCVD prevention, the evidence indicates that
generic statin-based treatments are cost-effective for people at least down to
1% annual total CVD risk and could be cost-effective at even lower risk,589 with
the highest tolerated statin dose likely the most cost-effective.591,593,594
Importantly, many patients on statin treatment fail to take their medications
adequately and/or to reach their therapeutic goals,595 with clinical and
economic consequences.596,597 Reinforcing measures aimed at improving adherence
to treatment is cost-effective.598–600

Studies have shown that at mid-2018 prices PCSK9 inhibitors were largely not
cost-effective.601–604 Their cost-effectiveness is improved in selected
high-risk patients, such as those with clinical CVD or FH, other comorbidities,
and high LDL-C levels.605,606 However, at lower prices, PCSK9 inhibitors would
become cost-effective in a wider range of high-risk patients; recent price
reductions may therefore lead to increased use.607 Cost-effectiveness evidence
for other lipid-modifying therapies is lacking.

Effective interventions to prevent ASCVD, including statins, typically exhibit
similar relative risk reductions across categories of patients, including by
ASCVD risk; therefore, health benefits and cost-effectiveness are greater among
people at higher ASCVD risk (Figure 6).36,233 Consequently, increased efforts
and higher-intensity interventions should be aimed at individuals and
populations at higher ASCVD risk.

Figure 6
Open in new tabDownload slide

Absolute reductions in major vascular events with statin therapy.233 LDL =
low-density lipoprotein. Reproduced from The Lancet, 388/10059, Collins et al.,
‘Interpretation of the evidence for the efficacy and safety of statin therapy’,
2532-2561, 2016, with permission from Elsevier.

Box 8 lists the key messages regarding the cost-effectiveness of CVD prevention
by lipid modification, and Box 9 highlights gaps in the evidence.

Box 8

Key messages

Prevention of CVD by lifestyle changes, medication, or both is cost-effective in
many scenarios, including population-based approaches and actions directed at
individuals at increased CVD risk. Cost-effectiveness depends on several
factors, including baseline CVD risk and LDL levels, cost of treatment, and
uptake of preventive strategies. Interventions to prevent CVD are more
cost-effective among individuals and populations at higher CVD
risk. Cost-effectiveness analyses are importantly informed by assumptions about
long-term disease prognosis and treatment effects. Strengthening of the evidence
to inform these assumptions is encouraged. 

Prevention of CVD by lifestyle changes, medication, or both is cost-effective in
many scenarios, including population-based approaches and actions directed at
individuals at increased CVD risk. Cost-effectiveness depends on several
factors, including baseline CVD risk and LDL levels, cost of treatment, and
uptake of preventive strategies. Interventions to prevent CVD are more
cost-effective among individuals and populations at higher CVD
risk. Cost-effectiveness analyses are importantly informed by assumptions about
long-term disease prognosis and treatment effects. Strengthening of the evidence
to inform these assumptions is encouraged. 

CVD = cardiovascular disease; LDL = low-density lipoprotein.

Open in new tab
Box 8

Key messages

Prevention of CVD by lifestyle changes, medication, or both is cost-effective in
many scenarios, including population-based approaches and actions directed at
individuals at increased CVD risk. Cost-effectiveness depends on several
factors, including baseline CVD risk and LDL levels, cost of treatment, and
uptake of preventive strategies. Interventions to prevent CVD are more
cost-effective among individuals and populations at higher CVD
risk. Cost-effectiveness analyses are importantly informed by assumptions about
long-term disease prognosis and treatment effects. Strengthening of the evidence
to inform these assumptions is encouraged. 

Prevention of CVD by lifestyle changes, medication, or both is cost-effective in
many scenarios, including population-based approaches and actions directed at
individuals at increased CVD risk. Cost-effectiveness depends on several
factors, including baseline CVD risk and LDL levels, cost of treatment, and
uptake of preventive strategies. Interventions to prevent CVD are more
cost-effective among individuals and populations at higher CVD
risk. Cost-effectiveness analyses are importantly informed by assumptions about
long-term disease prognosis and treatment effects. Strengthening of the evidence
to inform these assumptions is encouraged. 

CVD = cardiovascular disease; LDL = low-density lipoprotein.

Open in new tab
Box 9

Gaps in the evidence

Cost-effectiveness requires evidence for effects of interventions on health and
healthcare over a long time period; modelling techniques fill gaps. More data
are needed from RCTs and observational studies. Direct evidence of effects of
lipid-modifying treatments on overall mortality, particularly among people at
low-to-moderate CVD risk, older people, and for newer interventions, is lacking.
Long-term post-trial follow-up in RCTs should be encouraged. The
cost-effectiveness of using lifetime CVD risk and more precise CVD risk scores
to target interventions needs further investigation. 

Cost-effectiveness requires evidence for effects of interventions on health and
healthcare over a long time period; modelling techniques fill gaps. More data
are needed from RCTs and observational studies. Direct evidence of effects of
lipid-modifying treatments on overall mortality, particularly among people at
low-to-moderate CVD risk, older people, and for newer interventions, is lacking.
Long-term post-trial follow-up in RCTs should be encouraged. The
cost-effectiveness of using lifetime CVD risk and more precise CVD risk scores
to target interventions needs further investigation. 

CVD = cardiovascular disease; RCT = randomized controlled trial.

Open in new tab
Box 9

Gaps in the evidence

Cost-effectiveness requires evidence for effects of interventions on health and
healthcare over a long time period; modelling techniques fill gaps. More data
are needed from RCTs and observational studies. Direct evidence of effects of
lipid-modifying treatments on overall mortality, particularly among people at
low-to-moderate CVD risk, older people, and for newer interventions, is lacking.
Long-term post-trial follow-up in RCTs should be encouraged. The
cost-effectiveness of using lifetime CVD risk and more precise CVD risk scores
to target interventions needs further investigation. 

Cost-effectiveness requires evidence for effects of interventions on health and
healthcare over a long time period; modelling techniques fill gaps. More data
are needed from RCTs and observational studies. Direct evidence of effects of
lipid-modifying treatments on overall mortality, particularly among people at
low-to-moderate CVD risk, older people, and for newer interventions, is lacking.
Long-term post-trial follow-up in RCTs should be encouraged. The
cost-effectiveness of using lifetime CVD risk and more precise CVD risk scores
to target interventions needs further investigation. 

CVD = cardiovascular disease; RCT = randomized controlled trial.

Open in new tab


13 STRATEGIES TO ENCOURAGE ADOPTION OF HEALTHY LIFESTYLE CHANGES AND ADHERENCE
TO LIPID-MODIFYING THERAPIES

Helping patients to change to healthier lifestyle habits is most effectively
achieved through formal programmes of preventive care, possibly because of the
intensive follow-up and multidisciplinary expertise they provide.608 However, in
everyday care, adherence to both healthy lifestyle changes and medication
regimens is a challenge to patients and professionals.

A comprehensive patient- and family-centred approach located in one healthcare
setting is recommended rather than addressing single risk factors with more than
one intervention in different locations. Box 10 includes some useful techniques
when counselling patients for behavioural change.

A comprehensive approach to improving adherence to medication is described in
the Supplementary Data document.

Box 10

Methods for enhancing adherence to lifestyle changes

1. Explore motivation and identify ambivalence. Weigh pros and cons for change,
assess and build self-efficacy and confidence, and avoid circular discussion. 2.
Offer support, and establish an alliance with the patient and his/her family. 3.
Involve the partner, other household members, or caregiver who may be
influential in the lifestyle of the patient. 4. Use the OARS method (Open-ended
questions, Affirmation, Reflective listening, Summarising when discussing
behaviour changes
(www.smartrecovery.org/wp-content/uploads/2017/03/UsingMIinSR.pdf). 5. Tailor
advice to an individual patient’s culture, habits, and situation. 6. Use SMART
goal setting (negotiate goals for change that are Specific, Measurable,
Achievable, Realistic, and Timely). Follow-up on goals and record progress on a
shared record. 

1. Explore motivation and identify ambivalence. Weigh pros and cons for change,
assess and build self-efficacy and confidence, and avoid circular discussion. 2.
Offer support, and establish an alliance with the patient and his/her family. 3.
Involve the partner, other household members, or caregiver who may be
influential in the lifestyle of the patient. 4. Use the OARS method (Open-ended
questions, Affirmation, Reflective listening, Summarising when discussing
behaviour changes
(www.smartrecovery.org/wp-content/uploads/2017/03/UsingMIinSR.pdf). 5. Tailor
advice to an individual patient’s culture, habits, and situation. 6. Use SMART
goal setting (negotiate goals for change that are Specific, Measurable,
Achievable, Realistic, and Timely). Follow-up on goals and record progress on a
shared record. 

Open in new tab
Box 10

Methods for enhancing adherence to lifestyle changes

1. Explore motivation and identify ambivalence. Weigh pros and cons for change,
assess and build self-efficacy and confidence, and avoid circular discussion. 2.
Offer support, and establish an alliance with the patient and his/her family. 3.
Involve the partner, other household members, or caregiver who may be
influential in the lifestyle of the patient. 4. Use the OARS method (Open-ended
questions, Affirmation, Reflective listening, Summarising when discussing
behaviour changes
(www.smartrecovery.org/wp-content/uploads/2017/03/UsingMIinSR.pdf). 5. Tailor
advice to an individual patient’s culture, habits, and situation. 6. Use SMART
goal setting (negotiate goals for change that are Specific, Measurable,
Achievable, Realistic, and Timely). Follow-up on goals and record progress on a
shared record. 

1. Explore motivation and identify ambivalence. Weigh pros and cons for change,
assess and build self-efficacy and confidence, and avoid circular discussion. 2.
Offer support, and establish an alliance with the patient and his/her family. 3.
Involve the partner, other household members, or caregiver who may be
influential in the lifestyle of the patient. 4. Use the OARS method (Open-ended
questions, Affirmation, Reflective listening, Summarising when discussing
behaviour changes
(www.smartrecovery.org/wp-content/uploads/2017/03/UsingMIinSR.pdf). 5. Tailor
advice to an individual patient’s culture, habits, and situation. 6. Use SMART
goal setting (negotiate goals for change that are Specific, Measurable,
Achievable, Realistic, and Timely). Follow-up on goals and record progress on a
shared record. 

Open in new tab


14 KEY MESSAGES



 1.  Cholesterol and risk. Prospective studies, randomized trials, and Mendelian
     randomization studies have all shown that raised LDL-C is a cause of ASCVD.
     Throughout the range of LDL-C levels, ‘lower is better’ with no lower
     threshold, at least down to ∼1 mmol/L. Lowering LDL-C may yield worthwhile
     benefits in patients with average or below average LDL-C who are already
     receiving LDL-C-lowering treatment. The proportional reduction in ASCVD
     risk achieved by lowering LDL-C (e.g. with a statin, ezetimibe, or
     PCSK9-inhibitor) depends on the absolute reduction in LDL-C, with each 1
     mmol/L reduction corresponding to a reduction of about one-fifth in ASCVD.

 2.  PCSK-9 inhibitors. Large trials have shown that PCSK9 inhibitors further
     reduce ASCVD risk when given on top of statin-based therapy and their use
     may need to be restricted to those at the highest risk for ASCVD.

 3.  Use of cardiac imaging for risk stratification. CAC score assessment with
     CT may be helpful in reaching decisions about treatment in people who are
     at moderate risk of ASCVD. Obtaining such a score may assist in discussions
     about treatment strategies in patients where the LDL-C goal is not achieved
     with lifestyle intervention alone and there is a question of whether to
     institute LDL-C-lowering treatment. Assessment of arterial (carotid or
     femoral) plaque burden on ultrasonography may also be informative in these
     circumstances.

 4.  Use of ApoB in risk stratification. ApoB may be a better measure of an
     individual’s exposure to pro atherogenic lipoproteins, and hence its use
     may be particularly helpful for risk assessment in people where measurement
     of LDL-C underestimates this burden, such as those with high TG, DM,
     obesity, or very low LDL-C.

 5.  Use of Lp(a) in risk stratification. A one-off measurement of Lp(a) may
     help to identify people with very high inherited Lp(a) levels who may have
     a substantial lifetime risk of ASCVD. A high Lp(a) plasma level may also be
     helpful in further risk stratification of patients at high risk of ASCVD,
     in patients with a family history of premature CVD, and to determine
     treatment strategies in people whose estimated risk is on the border of
     risk categories.

 6.  Intensification of treatment goals. It is important to ensure that
     treatment of the highest-risk patients achieves the largest LDL-C reduction
     possible. These Guidelines aim to support this by setting both a minimum
     percentage LDL-C reduction (50%) and an absolute LDL-C treatment goal of
     <1.4 mmol/L (<55 mg/dL) for very-high-risk patients, and <1.8 mmol/L (<70
     mg/dL) for high-risk patients. It is recommended that FH patients with
     ASCVD or who have another major risk factor are treated as very-high-risk,
     and those with no prior ASCVD or other risk factors as high-risk.

 7.  Treatment of patients with recent ACS. New randomized trials support a
     strategy of intensification of LDL-C-lowering therapy in very-high-risk
     patients with ACS (MI or unstable angina). If the specified LDL-C treatment
     goal is not achieved after 4–6 weeks with the highest tolerated statin dose
     and ezetimibe, it is appropriate to add a PCSK9 inhibitor.

 8.  Safety of low LDL cholesterol concentrations. To date there are no known
     adverse effects of very low LDL-C concentrations [e.g. <1 mmol/L (40
     mg/dL)].

 9.  Management of statin ‘intolerance’. While statins rarely cause serious
     muscle damage (myopathy, or rhabdomyolysis in the most severe cases), there
     is much public concern that statins may commonly cause less serious muscle
     symptoms. Such statin ‘intolerance’ is frequently encountered by
     practitioners and may be difficult to manage. However, placebo-controlled
     randomized trials have shown very clearly that true statin intolerance is
     rare, and that it is generally possible to institute some form of statin
     therapy (e.g. by changing the statin or reducing the dose) in the
     overwhelming majority of patients at risk of ASCVD.

 10. Statin treatment for older people. A meta-analysis of randomized trials has
     shown that the effects of statin therapy are determined by the absolute
     reduction in LDL-C as well as the baseline ASCVD risk, and are independent
     of all known risk factors, including age. Statin therapy in older people
     should therefore be considered according to the estimated level of risk and
     baseline LDL-C, albeit with due regard to an individual’s underlying health
     status and the risk of drug interactions. There is less certainty about the
     effects of statins in individuals aged >75 years, particularly in primary
     prevention. Statin therapy should be started at a low dose if there is
     significant renal impairment and/or the potential for drug interactions,
     and then titrated upwards to achieve LDL-C treatment goals.




15 GAPS IN THE EVIDENCE

 * Prospective studies are needed to investigate the incremental value of
   reclassifying total CV risk and defining eligibility for lipid-lowering
   therapy based on CAC scores in individuals at moderate or high-risk.

 * Outcome-based comparisons of CAC scores vs. assessment of arterial (carotid
   or femoral) plaque burden by ultrasonography for CV risk reclassification in
   people at moderate or high-risk are needed.

 * Although calibrated country-specific versions of the SCORE system are
   available for many European countries, risk charts based on country-specific
   cohort data are missing for most countries. Regional total event charts (vs.
   mortality-only charts) are needed.

 * Total CV risk estimation by means of the SCORE system and, accordingly,
   recommendations on eligibility for statins as well as treatment goals are
   based on TC, whereas LDL-C is the primary lipid analysis method for
   screening, diagnosis, and management.

 * There are no outcome-based comparisons of LDL-C vs. ApoB as primary
   measurement methods for screening, diagnosis, and management.

 * Against a background of genetic and randomized clinical trial evidence
   showing no significant effect of increasing HDL levels on the risk of CVD
   events, the clinical impact of therapies altering the function of HDL
   particles is unknown. More evidence is needed regarding the apparently
   adverse association of extremely high levels of HDL-C with clinical outcomes.

 * Dedicated studies assessing outcomes with specific Lp(a)-lowering therapies
   are warranted.

 * More evidence is needed for PCSK9 inhibitors in specific populations,
   including patients with severe CKD and on dialysis, patients with HIV
   infection, in children and adolescents with FH, after heart transplantation,
   and during pregnancy.

 * The effects of PCSK9 inhibition on specific body compartments (as with siRNA
   or antisense) or only within plasma (as with monoclonal antibodies) remain to
   be established.

 * How early should a PCSK9 inhibitor be initiated in patients with ACS or
   stroke? In view of evidence of sustained clinical benefit associated with the
   early initiation of statin treatment in the acute phase of ACS or stroke, the
   optimal timing of PCSK9 inhibitor treatment in ACS and stroke patients
   remains to be addressed in outcome studies.

 * Whether very low LDL-C levels achieved with the combination of statin,
   ezetimibe, and PCSK9 inhibitor reduce the need for further PCI remains to be
   addressed in outcome studies.

 * In patients with chronic HF, a small benefit of n-3 PUFAs has been shown in
   one RCT and merits further investigation.

 * What is the optimal screening programme for detecting FH?

 * In view of limited access to genetic testing in several environments, more
   evidence is needed regarding outcomes with only clinical vs. genetic
   screening and diagnosis of FH.

 * More RCT evidence is required to support the use of statin-based treatment in
   older people (aged ≥75 years, but particularly in those aged ≥80 years).

 * More RCT evidence is needed for statin treatment in kidney transplant
   recipients.

 * There are no data on the effects of statins, ezetimibe, or fibrates on CV
   events in dyslipidaemic HIV-infected patients.

 * More evidence is needed regarding attainment of recommended LDL goals among
   very high-risk patients in real-world practice in the era of increasingly
   prescribed combination therapies for LDL lowering.

 

 * Prospective studies are needed to investigate the incremental value of
   reclassifying total CV risk and defining eligibility for lipid-lowering
   therapy based on CAC scores in individuals at moderate or high-risk.

 * Outcome-based comparisons of CAC scores vs. assessment of arterial (carotid
   or femoral) plaque burden by ultrasonography for CV risk reclassification in
   people at moderate or high-risk are needed.

 * Although calibrated country-specific versions of the SCORE system are
   available for many European countries, risk charts based on country-specific
   cohort data are missing for most countries. Regional total event charts (vs.
   mortality-only charts) are needed.

 * Total CV risk estimation by means of the SCORE system and, accordingly,
   recommendations on eligibility for statins as well as treatment goals are
   based on TC, whereas LDL-C is the primary lipid analysis method for
   screening, diagnosis, and management.

 * There are no outcome-based comparisons of LDL-C vs. ApoB as primary
   measurement methods for screening, diagnosis, and management.

 * Against a background of genetic and randomized clinical trial evidence
   showing no significant effect of increasing HDL levels on the risk of CVD
   events, the clinical impact of therapies altering the function of HDL
   particles is unknown. More evidence is needed regarding the apparently
   adverse association of extremely high levels of HDL-C with clinical outcomes.

 * Dedicated studies assessing outcomes with specific Lp(a)-lowering therapies
   are warranted.

 * More evidence is needed for PCSK9 inhibitors in specific populations,
   including patients with severe CKD and on dialysis, patients with HIV
   infection, in children and adolescents with FH, after heart transplantation,
   and during pregnancy.

 * The effects of PCSK9 inhibition on specific body compartments (as with siRNA
   or antisense) or only within plasma (as with monoclonal antibodies) remain to
   be established.

 * How early should a PCSK9 inhibitor be initiated in patients with ACS or
   stroke? In view of evidence of sustained clinical benefit associated with the
   early initiation of statin treatment in the acute phase of ACS or stroke, the
   optimal timing of PCSK9 inhibitor treatment in ACS and stroke patients
   remains to be addressed in outcome studies.

 * Whether very low LDL-C levels achieved with the combination of statin,
   ezetimibe, and PCSK9 inhibitor reduce the need for further PCI remains to be
   addressed in outcome studies.

 * In patients with chronic HF, a small benefit of n-3 PUFAs has been shown in
   one RCT and merits further investigation.

 * What is the optimal screening programme for detecting FH?

 * In view of limited access to genetic testing in several environments, more
   evidence is needed regarding outcomes with only clinical vs. genetic
   screening and diagnosis of FH.

 * More RCT evidence is required to support the use of statin-based treatment in
   older people (aged ≥75 years, but particularly in those aged ≥80 years).

 * More RCT evidence is needed for statin treatment in kidney transplant
   recipients.

 * There are no data on the effects of statins, ezetimibe, or fibrates on CV
   events in dyslipidaemic HIV-infected patients.

 * More evidence is needed regarding attainment of recommended LDL goals among
   very high-risk patients in real-world practice in the era of increasingly
   prescribed combination therapies for LDL lowering.

 

Open in new tab

 * Prospective studies are needed to investigate the incremental value of
   reclassifying total CV risk and defining eligibility for lipid-lowering
   therapy based on CAC scores in individuals at moderate or high-risk.

 * Outcome-based comparisons of CAC scores vs. assessment of arterial (carotid
   or femoral) plaque burden by ultrasonography for CV risk reclassification in
   people at moderate or high-risk are needed.

 * Although calibrated country-specific versions of the SCORE system are
   available for many European countries, risk charts based on country-specific
   cohort data are missing for most countries. Regional total event charts (vs.
   mortality-only charts) are needed.

 * Total CV risk estimation by means of the SCORE system and, accordingly,
   recommendations on eligibility for statins as well as treatment goals are
   based on TC, whereas LDL-C is the primary lipid analysis method for
   screening, diagnosis, and management.

 * There are no outcome-based comparisons of LDL-C vs. ApoB as primary
   measurement methods for screening, diagnosis, and management.

 * Against a background of genetic and randomized clinical trial evidence
   showing no significant effect of increasing HDL levels on the risk of CVD
   events, the clinical impact of therapies altering the function of HDL
   particles is unknown. More evidence is needed regarding the apparently
   adverse association of extremely high levels of HDL-C with clinical outcomes.

 * Dedicated studies assessing outcomes with specific Lp(a)-lowering therapies
   are warranted.

 * More evidence is needed for PCSK9 inhibitors in specific populations,
   including patients with severe CKD and on dialysis, patients with HIV
   infection, in children and adolescents with FH, after heart transplantation,
   and during pregnancy.

 * The effects of PCSK9 inhibition on specific body compartments (as with siRNA
   or antisense) or only within plasma (as with monoclonal antibodies) remain to
   be established.

 * How early should a PCSK9 inhibitor be initiated in patients with ACS or
   stroke? In view of evidence of sustained clinical benefit associated with the
   early initiation of statin treatment in the acute phase of ACS or stroke, the
   optimal timing of PCSK9 inhibitor treatment in ACS and stroke patients
   remains to be addressed in outcome studies.

 * Whether very low LDL-C levels achieved with the combination of statin,
   ezetimibe, and PCSK9 inhibitor reduce the need for further PCI remains to be
   addressed in outcome studies.

 * In patients with chronic HF, a small benefit of n-3 PUFAs has been shown in
   one RCT and merits further investigation.

 * What is the optimal screening programme for detecting FH?

 * In view of limited access to genetic testing in several environments, more
   evidence is needed regarding outcomes with only clinical vs. genetic
   screening and diagnosis of FH.

 * More RCT evidence is required to support the use of statin-based treatment in
   older people (aged ≥75 years, but particularly in those aged ≥80 years).

 * More RCT evidence is needed for statin treatment in kidney transplant
   recipients.

 * There are no data on the effects of statins, ezetimibe, or fibrates on CV
   events in dyslipidaemic HIV-infected patients.

 * More evidence is needed regarding attainment of recommended LDL goals among
   very high-risk patients in real-world practice in the era of increasingly
   prescribed combination therapies for LDL lowering.

 

 * Prospective studies are needed to investigate the incremental value of
   reclassifying total CV risk and defining eligibility for lipid-lowering
   therapy based on CAC scores in individuals at moderate or high-risk.

 * Outcome-based comparisons of CAC scores vs. assessment of arterial (carotid
   or femoral) plaque burden by ultrasonography for CV risk reclassification in
   people at moderate or high-risk are needed.

 * Although calibrated country-specific versions of the SCORE system are
   available for many European countries, risk charts based on country-specific
   cohort data are missing for most countries. Regional total event charts (vs.
   mortality-only charts) are needed.

 * Total CV risk estimation by means of the SCORE system and, accordingly,
   recommendations on eligibility for statins as well as treatment goals are
   based on TC, whereas LDL-C is the primary lipid analysis method for
   screening, diagnosis, and management.

 * There are no outcome-based comparisons of LDL-C vs. ApoB as primary
   measurement methods for screening, diagnosis, and management.

 * Against a background of genetic and randomized clinical trial evidence
   showing no significant effect of increasing HDL levels on the risk of CVD
   events, the clinical impact of therapies altering the function of HDL
   particles is unknown. More evidence is needed regarding the apparently
   adverse association of extremely high levels of HDL-C with clinical outcomes.

 * Dedicated studies assessing outcomes with specific Lp(a)-lowering therapies
   are warranted.

 * More evidence is needed for PCSK9 inhibitors in specific populations,
   including patients with severe CKD and on dialysis, patients with HIV
   infection, in children and adolescents with FH, after heart transplantation,
   and during pregnancy.

 * The effects of PCSK9 inhibition on specific body compartments (as with siRNA
   or antisense) or only within plasma (as with monoclonal antibodies) remain to
   be established.

 * How early should a PCSK9 inhibitor be initiated in patients with ACS or
   stroke? In view of evidence of sustained clinical benefit associated with the
   early initiation of statin treatment in the acute phase of ACS or stroke, the
   optimal timing of PCSK9 inhibitor treatment in ACS and stroke patients
   remains to be addressed in outcome studies.

 * Whether very low LDL-C levels achieved with the combination of statin,
   ezetimibe, and PCSK9 inhibitor reduce the need for further PCI remains to be
   addressed in outcome studies.

 * In patients with chronic HF, a small benefit of n-3 PUFAs has been shown in
   one RCT and merits further investigation.

 * What is the optimal screening programme for detecting FH?

 * In view of limited access to genetic testing in several environments, more
   evidence is needed regarding outcomes with only clinical vs. genetic
   screening and diagnosis of FH.

 * More RCT evidence is required to support the use of statin-based treatment in
   older people (aged ≥75 years, but particularly in those aged ≥80 years).

 * More RCT evidence is needed for statin treatment in kidney transplant
   recipients.

 * There are no data on the effects of statins, ezetimibe, or fibrates on CV
   events in dyslipidaemic HIV-infected patients.

 * More evidence is needed regarding attainment of recommended LDL goals among
   very high-risk patients in real-world practice in the era of increasingly
   prescribed combination therapies for LDL lowering.

 

Open in new tab


16 ‘WHAT TO DO’ AND ‘WHAT NOT TO DO’ MESSAGES FROM THE GUIDELINES

  

  

ACS = acute coronary syndrome(s); Apo = apolipoprotein; ASCVD = atherosclerotic
cardiovascular disease; CAD = coronary artery disease; CHD = coronary heart
disease; CIID = chronic immune-mediated inflammatory diseases; CKD = chronic
kidney disease; CV = cardiovascular; CVD = cardiovascular disease; DM = diabetes
mellitus; FH = familial hypercholesterolaemia; HDL-C = high-density lipoprotein
cholesterol; HeFH = heterozygous FH; HF = heart failure; HoFH = homozygous FH;
HTG = hypertriglyceridaemia; LDL-C = low-density lipoprotein cholesterol; MetS =
metabolic syndrome; PAD = peripheral arterial disease; PCSK9 = proprotein
convertase subtilisin/kexin type 9; SCORE = Systematic Coronary Risk Estimation;
SMI = severe mental illness; TC = total cholesterol; TG = triglycerides; TIA =
transient ischaemic event; T1DM = type 1 DM; T2DM = type 2 DM.

a

Class of recommendation.

b

Level of evidence.

Open in new tab

  

  

ACS = acute coronary syndrome(s); Apo = apolipoprotein; ASCVD = atherosclerotic
cardiovascular disease; CAD = coronary artery disease; CHD = coronary heart
disease; CIID = chronic immune-mediated inflammatory diseases; CKD = chronic
kidney disease; CV = cardiovascular; CVD = cardiovascular disease; DM = diabetes
mellitus; FH = familial hypercholesterolaemia; HDL-C = high-density lipoprotein
cholesterol; HeFH = heterozygous FH; HF = heart failure; HoFH = homozygous FH;
HTG = hypertriglyceridaemia; LDL-C = low-density lipoprotein cholesterol; MetS =
metabolic syndrome; PAD = peripheral arterial disease; PCSK9 = proprotein
convertase subtilisin/kexin type 9; SCORE = Systematic Coronary Risk Estimation;
SMI = severe mental illness; TC = total cholesterol; TG = triglycerides; TIA =
transient ischaemic event; T1DM = type 1 DM; T2DM = type 2 DM.

a

Class of recommendation.

b

Level of evidence.

Open in new tab


17 SUPPLEMENTARY DATA

Supplementary Data with additional Supplementary Tables, Boxes, and text
complementing the full text—as well as sections on other features of a healthy
diet contributing to cardiovascular disease prevention, chronic immune-mediated
inflammatory diseases, HIV patients, severe mental illness, and adhering to
medications along with the related references—are available on the European
Heart Journal website and via the ESC website at www.escardio.org/guidelines.


18 APPENDIX

Author/Task Force Member Affiliations:

Konstantinos C. Koskinas, Cardiology, Bern University Hospital (Inselspital),
Bern, Switzerland; Manuela Casula, Epidemiology and Preventive Pharmacology
Service (SEFAP), Department of Pharmacological and Biomolecular Sciences
(DiSFeB), University of Milan, Milan, Italy and IRCCS MultiMedica, Sesto S.
Giovanni (Milan), Italy; Lina Badimon, Cardiovascular Program-ICCC and CiberCV,
IR-Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; M. John Chapman,
National Institute for Health and Medical Research (INSERM), Paris, France;
Sorbonne University, Paris, France; and Division of Endocrinology- Metabolism,
Pitie-Salpetriere University Hospital, Paris, France; Guy G. De Backer, Public
Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent
University, Ghent, Belgium; Victoria Delgado, Cardiology, Leiden University
Medical Center, Leiden, Netherlands; Brian A. Ference, Centre for Naturally
Randomized Trials, Department of Public Health and Primary Care, University of
Cambridge, Cambridge, United Kingdom; Ian M. Graham, Cardiology, Trinity
College, Dublin, Ireland; Alison Halliday, Nuffield Department of Surgery,
University of Oxford, Oxford, United Kingdom and NIHR Oxford Biomedical Research
Centre, Oxford, United Kingdom; Ulf Landmesser, Department of Cardiology,
Charite Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health
(BIH), Berlin, Germany; and German Center of Cardiovascular Research (DZHK),
Berlin, Germany; Borislava Mihaylova, Nuffield Department of Population Health
and NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, United
Kingdom and Barts and The London School of Medicine and Dentistry, Queen Mary
University of London, London, United Kingdom; Terje R. Pedersen, Preventive
Cardiology, Oslo University Hospital, Aker, Oslo, Norway; Gabriele Riccardi,
Clinical Medicine and Surgery, Federico II University, Naples, Italy; Dimitrios
J. Richter, Cardiac Department, Euroclinic, Athens, Greece; Marc S. Sabatine,
TIMI Study Group, Division of Cardiovascular Medicine, Brigham and Women’s
Hospital and Harvard Medical School, Boston, MA, United States of America;
Marja-Riitta Taskinen, Research Program for Clinical and Molecular Metabolism,
University of Helsinki, Helsinki, Finland; Lale Tokgozoglu, Cardiology,
Hacettepe University, Ankara, Turkey; Olov Wiklund, Institute of Medicine, The
Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.

ESC Committee for Practice Guidelines (CPG): Stephan Windecker (Chairperson)
(Switzerland), Victor Aboyans (France), Colin Baigent (United Kingdom),
Jean-Philippe Collet (France), Veronica Dean (France), Victoria Delgado
(Netherlands), Donna Fitzsimons (United Kingdom), Chris P. Gale (United
Kingdom), Diederick E. Grobbee (Netherlands), Sigrun Halvorsen (Norway), Gerhard
Hindricks (Germany), Bernard Iung (France), Peter Jüni (Canada), Hugo A. Katus
(Germany), Ulf Landmesser (Germany), Christophe Leclercq (France), Maddalena
Lettino (Italy), Basil S. Lewis (Israel), Bela Merkely (Hungary), Christian
Mueller (Switzerland), Steffen Petersen (United Kingdom), Anna Sonia Petronio
(Italy), Dimitrios J. Richter (Greece), Marco Roffi (Switzerland), Evgeny
Shlyakhto (Russian Federation), Iain A. Simpson (United Kingdom), Miguel
Sousa-Uva (Portugal), Rhian M. Touyz (United Kingdom).

ESC National Cardiac Societies actively involved in the review process of the
2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification
to reduce cardiovascular risk.

Algeria: Algerian Society of Cardiology, Djamaleddine Nibouche; Armenia:
Armenian Cardiologists Association, Parounak H. Zelveian; Austria: Austrian
Society of Cardiology, Peter Siostrzonek; Azerbaijan: Azerbaijan Society of
Cardiology, Ruslan Najafov; Belgium: Belgian Society of Cardiology, Philippe van
de Borne; Bosnia and Herzegovina: Association of Cardiologists of Bosnia and
Herzegovina, Belma Pojskic; Bulgaria: Bulgarian Society of Cardiology, Arman
Postadzhiyan; Cyprus: Cyprus Society of Cardiology, Lambros Kypris; Czech
Republic: Czech Society of Cardiology, Jindřich Špinar; Denmark: Danish Society
of Cardiology, Mogens Lytken Larsen; Egypt: Egyptian Society of Cardiology,
Hesham Salah Eldin; Estonia: Estonian Society of Cardiology, Margus Viigimaa;
Finland: Finnish Cardiac Society, Timo E. Strandberg; France: French Society of
Cardiology, Jean Ferrières; Georgia: Georgian Society of Cardiology, Rusudan
Agladze; Germany: German Cardiac Society, Ulrich Laufs; Greece: Hellenic Society
of Cardiology, Loukianos Rallidis; Hungary: Hungarian Society of Cardiology,
László Bajnok; Iceland: Icelandic Society of Cardiology, Thorbjörn Gudjónsson;
Ireland: Irish Cardiac Society, Vincent Maher; Israel: Israel Heart Society,
Yaakov Henkin; Italy: Italian Federation of Cardiology, Michele Massimo Gulizia;
Kazakhstan: Association of Cardiologists of Kazakhstan, Aisulu Mussagaliyeva;
Kosovo (Republic of): Kosovo Society of Cardiology, Gani Bajraktari; Kyrgyzstan:
Kyrgyz Society of Cardiology, Alina Kerimkulova; Latvia: Latvian Society of
Cardiology, Gustavs Latkovskis; Lebanon: Lebanese Society of Cardiology, Omar
Hamoui; Lithuania: Lithuanian Society of Cardiology, Rimvydas Slapikas;
Luxembourg: Luxembourg Society of Cardiology, Laurent Visser; Malta: Maltese
Cardiac Society, Philip Dingli; Moldova (Republic of): Moldavian Society of
Cardiology, Victoria Ivanov; Montenegro: Montenegro Society of Cardiology, Aneta
Boskovic; Morocco: Moroccan Society of Cardiology, Mbarek Nazzi; Netherlands:
Netherlands Society of Cardiology, Frank Visseren; North Macedonia: North
Macedonian Society of Cardiology, Irena Mitevska; Norway: Norwegian Society of
Cardiology, Kjetil Retterstøl; Poland: Polish Cardiac Society, Piotr Jankowski;
Portugal: Portuguese Society of Cardiology, Ricardo Fontes-Carvalho; Romania:
Romanian Society of Cardiology, Dan Gaita; Russian Federation: Russian Society
of Cardiology, Marat Ezhov; San Marino: San Marino Society of Cardiology, Marina
Foscoli; Serbia: Cardiology Society of Serbia, Vojislav Giga; Slovakia: Slovak
Society of Cardiology, Daniel Pella; Slovenia: Slovenian Society of Cardiology,
Zlatko Fras; Spain: Spanish Society of Cardiology, Leopoldo Perez de Isla;
Sweden: Swedish Society of Cardiology, Emil Hagström; Switzerland: Swiss Society
of Cardiology, Roger Lehmann; Tunisia: Tunisian Society of Cardiology and
Cardio-Vascular Surgery, Leila Abid; Turkey: Turkish Society of Cardiology, Oner
Ozdogan; Ukraine: Ukrainian Association of Cardiology, Olena Mitchenko; United
Kingdom of Great Britain and Northern Ireland: British Cardiovascular Society,
Riyaz S. Patel.

The disclosure forms of all experts involved in the development of these
Guidelines are available on the ESC website www.escardio.org/guidelines

ESC Committee for Practice Guidelines (CPG), National Cardiac Societies document
reviewers and Author/Task Force Member affiliations: listed in the Appendix.

ESC entities having participated in the development of this document:

Associations: Acute Cardiovascular Care Association (ACCA), Association of
Cardiovascular Nursing & Allied Professions (ACNAP), European Association of
Cardiovascular Imaging (EACVI), European Association of Preventive Cardiology
(EAPC), European Association of Percutaneous Cardiovascular Interventions
(EAPCI).

Councils: Council for Cardiology Practice, Council on Hypertension, Council on
Stroke.

Working Groups: Aorta and Peripheral Vascular Diseases, Atherosclerosis and
Vascular Biology, Cardiovascular Pharmacotherapy, e-Cardiology, Thrombosis.

The content of these European Society of Cardiology (ESC) Guidelines has been
published for personal and educational use only. No commercial use is
authorized. No part of the ESC Guidelines may be translated or reproduced in any
form without written permission from the ESC. Permission can be obtained upon
submission of a written request to Oxford University Press, the publisher of the
European Heart Journal and the party authorized to handle such permissions on
behalf of the ESC (journals.permissions@oxfordjournals.org).

Disclaimer. The ESC/EAS Guidelines represent the views of the ESC and EAS, and
were produced after careful consideration of the scientific and medical
knowledge, and the evidence available at the time of their publication. The ESC
and EAS is not responsible in the event of any contradiction, discrepancy,
and/or ambiguity between the ESC/EAS Guidelines and any other official
recommendations or guidelines issued by the relevant public health authorities,
in particular in relation to good use of healthcare or therapeutic strategies.
Health professionals are encouraged to take the ESC/EAS Guidelines fully into
account when exercising their clinical judgment, as well as in the determination
and the implementation of preventive, diagnostic, or therapeutic medical
strategies; however, the ESC/EAS Guidelines do not override, in any way
whatsoever, the individual responsibility of health professionals to make
appropriate and accurate decisions in consideration of each patient’s health
condition and in consultation with that patient and, where appropriate and/or
necessary, the patient’s caregiver. Nor do the ESC/EAS Guidelines exempt health
professionals from taking into full and careful consideration the relevant
official updated recommendations or guidelines issued by the competent public
health authorities, in order to manage each patient’s case in light of the
scientifically accepted data pursuant to their respective ethical and
professional obligations. It is also the health professional’s responsibility to
verify the applicable rules and regulations relating to drugs and medical
devices at the time of prescription.


19 REFERENCES

1

Catapano
AL
,
Graham
I
,
De Backer
G
,
Wiklund
O
,
Chapman
MJ
,
Drexel
H
,
Hoes
AW
,
Jennings
CS
,
Landmesser
U
,
Pedersen
TR
,
Reiner
Z
,
Riccardi
G
,
Taskinen
MR
,
Tokgozoglu
L
,
Verschuren
WMM
,
Vlachopoulos
C
,
Wood
DA
,
Zamorano
JL
,
Cooney
MT
; ESC Scientific Document Group.
2016 ESC/EAS Guidelines for the management of dyslipidaemias
.
Eur Heart J
2016
;
37
:
2999
–
3058
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
2

Ference
BA
,
Ginsberg
HN
,
Graham
I
,
Ray
KK
,
Packard
CJ
,
Bruckert
E
,
Hegele
RA
,
Krauss
RM
,
Raal
FJ
,
Schunkert
H
,
Watts
GF
,
Boren
J
,
Fazio
S
,
Horton
JD
,
Masana
L
,
Nicholls
SJ
,
Nordestgaard
BG
,
van de Sluis
B
,
Taskinen
MR
,
Tokgozoglu
L
,
Landmesser
U
,
Laufs
U
,
Wiklund
O
,
Stock
JK
,
Chapman
MJ
,
Catapano
AL.
Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1.
Evidence from genetic, epidemiologic, and clinical studies. A consensus
statement from the European Atherosclerosis Society Consensus Panel
.
Eur Heart J
2017
;
38
:
2459
–
2472
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
3

Townsend
N
,
Nichols
M
,
Scarborough
P
,
Rayner
M.
Cardiovascular disease in Europe--epidemiological update 2015
.
Eur Heart J
2015
;
36
:
2696
–
2705
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
4

Cooney
MT
,
Dudina
A
,
Whincup
P
,
Capewell
S
,
Menotti
A
,
Jousilahti
P
,
Njolstad
I
,
Oganov
R
,
Thomsen
T
,
Tverdal
A
,
Wedel
H
,
Wilhelmsen
L
,
Graham
I
;
SCORE Investigators. Re-evaluating the Rose approach: comparative benefits of
the population and high-risk preventive strategies
.
Eur J Cardiovasc Prev Rehabil
2009
;
16
:
541
–
549
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
5

World Health Organization.

Global Status Report on Noncommunicable Diseases 2014
. Geneva, Switzerland: World Health Organization; 2014.
https://www.who.int/nmh/publications/ncd-status-report-2014/en/ (17 July 2019).



Google Scholar

Google Preview

OpenURL Placeholder Text

WorldCat

COPAC
6

Cooney
MT
,
Dudina
AL
,
Graham
IM.
Value and limitations of existing scores for the assessment of cardiovascular
risk: a review for clinicians
.
J Am Coll Cardiol
2009
;
54
:
1209
–
1227
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
7

Hajifathalian
K
,
Ueda
P
,
Lu
Y
,
Woodward
M
,
Ahmadvand
A
,
Aguilar-Salinas
CA
,
Azizi
F
,
Cifkova
R
,
Di Cesare
M
,
Eriksen
L
,
Farzadfar
F
,
Ikeda
N
,
Khalili
D
,
Khang
YH
,
Lanska
V
,
Leon-Munoz
L
,
Magliano
D
,
Msyamboza
KP
,
Oh
K
,
Rodriguez-Artalejo
F
,
Rojas-Martinez
R
,
Shaw
JE
,
Stevens
GA
,
Tolstrup
J
,
Zhou
B
,
Salomon
JA
,
Ezzati
M
,
Danaei
G.
A novel risk score to predict cardiovascular disease risk in national
populations (Globorisk): a pooled analysis of prospective cohorts and health
examination surveys
.
Lancet Diabetes Endocrinol
2015
;
3
:
339
–
355
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
8

Cooney
MT
,
Dudina
A
,
D'Agostino
R
,
Graham
IM.
Cardiovascular risk-estimation systems in primary prevention: do they differ? Do
they make a difference? Can we see the future?
Circulation
2010
;
122
:
300
–
310
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
9

Perk
J
,
De Backer
G
,
Gohlke
H
,
Graham
I
,
Reiner
Z
,
Verschuren
M
,
Albus
C
,
Benlian
P
,
Boysen
G
,
Cifkova
R
,
Deaton
C
,
Ebrahim
S
,
Fisher
M
,
Germano
G
,
Hobbs
R
,
Hoes
A
,
Karadeniz
S
,
Mezzani
A
,
Prescott
E
,
Ryden
L
,
Scherer
M
,
Syvanne
M
,
Scholte op Reimer
WJ
,
Vrints
C
,
Wood
D
,
Zamorano
JL
,
Zannad
F
; European Association for Cardiovascular Prevention & Rehabilitation; ESC
Committee for Practice Guidelines (CPG).
European Guidelines on cardiovascular disease prevention in clinical practice
(version 2012). The Fifth Joint Task Force of the European Society of Cardiology
and Other Societies on Cardiovascular Disease Prevention in Clinical Practice
(constituted by representatives of nine societies and by invited experts)
.
Eur Heart J
2012
;
33
:
1635
–
1701
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
10

Piepoli
MF
,
Hoes
AW
,
Agewall
S
,
Albus
C
,
Brotons
C
,
Catapano
AL
,
Cooney
MT
,
Corra
U
,
Cosyns
B
,
Deaton
C
,
Graham
I
,
Hall
MS
,
Hobbs
FD
,
Lochen
ML
,
Lollgen
H
,
Marques-Vidal
P
,
Perk
J
,
Prescott
E
,
Redon
J
,
Richter
DJ
,
Sattar
N
,
Smulders
Y
,
Tiberi
M
,
van der Worp
HB
,
van Dis
I
,
Verschuren
WM
, Authors/Task Force M.
2016 European Guidelines on cardiovascular disease prevention in clinical
practice: The Sixth Joint Task Force of the European Society of Cardiology and
Other Societies on Cardiovascular Disease Prevention in Clinical Practice
(constituted by representatives of 10 societies and by invited experts)Developed
with the special contribution of the European Association for Cardiovascular
Prevention & Rehabilitation (EACPR)
.
Eur Heart J
2016
;
37
:
2315
–
2381
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
11

Cooney
MT
,
Selmer
R
,
Lindman
A
,
Tverdal
A
,
Menotti
A
,
Thomsen
T
,
DeBacker
G
,
De Bacquer
D
,
Tell
GS
,
Njolstad
I
,
Graham
IM
; SCORE and CONOR investigators.
Cardiovascular risk estimation in older persons: SCORE O.P
.
Eur J Prev Cardiol
2016
;
23
:
1093
–
1103
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
12

Berry
JD
,
Dyer
A
,
Cai
X
,
Garside
DB
,
Ning
H
,
Thomas
A
,
Greenland
P
,
Van Horn
L
,
Tracy
RP
,
Lloyd-Jones
DM.
Lifetime risks of cardiovascular disease
.
N Engl J Med
2012
;
366
:
321
–
329
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
13

Foster
HME
,
Celis-Morales
CA
,
Nicholl
BI
,
Petermann-Rocha
F
,
Pell
JP
,
Gill
JMR
,
O'Donnell
CA
,
Mair
FS.
The effect of socioeconomic deprivation on the association between an extended
measurement of unhealthy lifestyle factors and health outcomes: a prospective
analysis of the UK Biobank cohort
.
Lancet Public Health
2018
;
3
:
e576
–
e585
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
14

Kavousi
M
,
Elias-Smale
S
,
Rutten
JH
,
Leening
MJ
,
Vliegenthart
R
,
Verwoert
GC
,
Krestin
GP
,
Oudkerk
M
,
de Maat
MP
,
Leebeek
FW
,
Mattace-Raso
FU
,
Lindemans
J
,
Hofman
A
,
Steyerberg
EW
,
van der Lugt
A
,
van den Meiracker
AH
,
Witteman
JC.
Evaluation of newer risk markers for coronary heart disease risk classification:
a cohort study
.
Ann Intern Med
2012
;
156
:
438
–
444
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
15

Vlachopoulos
C
,
Xaplanteris
P
,
Aboyans
V
,
Brodmann
M
,
Cifkova
R
,
Cosentino
F
,
De Carlo
M
,
Gallino
A
,
Landmesser
U
,
Laurent
S
,
Lekakis
J
,
Mikhailidis
DP
,
Naka
KK
,
Protogerou
AD
,
Rizzoni
D
,
Schmidt-Trucksass
A
,
Van Bortel
L
,
Weber
T
,
Yamashina
A
,
Zimlichman
R
,
Boutouyrie
P
,
Cockcroft
J
,
O'Rourke
M
,
Park
JB
,
Schillaci
G
,
Sillesen
H
,
Townsend
RR.
The role of vascular biomarkers for primary and secondary prevention. A position
paper from the European Society of Cardiology Working Group on peripheral
circulation: endorsed by the Association for Research into Arterial Structure
and Physiology (ARTERY) Society
.
Atherosclerosis
2015
;
241
:
507
–
532
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
16

Yeboah
J
,
McClelland
RL
,
Polonsky
TS
,
Burke
GL
,
Sibley
CT
,
O'Leary
D
,
Carr
JJ
,
Goff
DC
,
Greenland
P
,
Herrington
DM.
Comparison of novel risk markers for improvement in cardiovascular risk
assessment in intermediate-risk individuals
.
JAMA
2012
;
308
:
788
–
795
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
17

Madsen
CM
,
Varbo
A
,
Nordestgaard
BG.
Extreme high high-density lipoprotein cholesterol is paradoxically associated
with high mortality in men and women: two prospective cohort studies
.
Eur Heart J
2017
;
38
:
2478
–
2486
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
18

Mortensen
MB
,
Falk
E
,
Li
D
,
Nasir
K
,
Blaha
MJ
,
Sandfort
V
,
Rodriguez
CJ
,
Ouyang
P
,
Budoff
M.
Statin trials, cardiovascular events, and coronary artery calcification:
implications for a trial-based approach to statin therapy in MESA
.
JACC Cardiovasc Imaging
2018
;
11
:
221
–
230
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
19

Lin
JS
,
Evans
CV
,
Johnson
E
,
Redmond
N
,
Coppola
EL
,
Smith
N.
Nontraditional risk factors in cardiovascular disease risk assessment: updated
evidence report and systematic review for the US Preventive Services Task Force
.
JAMA
2018
;
320
:
281
–
297
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
20

Baber
U
,
Mehran
R
,
Sartori
S
,
Schoos
MM
,
Sillesen
H
,
Muntendam
P
,
Garcia
MJ
,
Gregson
J
,
Pocock
S
,
Falk
E
,
Fuster
V.
Prevalence, impact, and predictive value of detecting subclinical coronary and
carotid atherosclerosis in asymptomatic adults: the BioImage study
.
J Am Coll Cardiol
2015
;
65
:
1065
–
1074
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
21

McDermott
MM
,
Kramer
CM
,
Tian
L
,
Carr
J
,
Guralnik
JM
,
Polonsky
T
,
Carroll
T
,
Kibbe
M
,
Criqui
MH
,
Ferrucci
L
,
Zhao
L
,
Hippe
DS
,
Wilkins
J
,
Xu
D
,
Liao
Y
,
McCarthy
W
,
Yuan
C.
Plaque composition in the proximal superficial femoral artery and peripheral
artery disease events
.
JACC Cardiovasc Imaging
2017
;
10
:
1003
–
1012
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
22

Sillesen
H
,
Sartori
S
,
Sandholt
B
,
Baber
U
,
Mehran
R
,
Fuster
V.
Carotid plaque thickness and carotid plaque burden predict future cardiovascular
events in asymptomatic adult Americans
.
Eur Heart J Cardiovasc Imaging
2018
;
19
:
1042
–
1050
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
23

Perrone-Filardi
P
,
Achenbach
S
,
Mohlenkamp
S
,
Reiner
Z
,
Sambuceti
G
,
Schuijf
JD
,
Van der Wall
E
,
Kaufmann
PA
,
Knuuti
J
,
Schroeder
S
,
Zellweger
MJ.
Cardiac computed tomography and myocardial perfusion scintigraphy for risk
stratification in asymptomatic individuals without known cardiovascular disease:
a position statement of the Working Group on Nuclear Cardiology and Cardiac CT
of the European Society of Cardiology
.
Eur Heart J
2011
;
32
:
1986
–
1993
, 1993a, 1993b.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
24

Den Ruijter
HM
,
Peters
SA
,
Anderson
TJ
,
Britton
AR
,
Dekker
JM
,
Eijkemans
MJ
,
Engstrom
G
,
Evans
GW
,
de Graaf
J
,
Grobbee
DE
,
Hedblad
B
,
Hofman
A
,
Holewijn
S
,
Ikeda
A
,
Kavousi
M
,
Kitagawa
K
,
Kitamura
A
,
Koffijberg
H
,
Lonn
EM
,
Lorenz
MW
,
Mathiesen
EB
,
Nijpels
G
,
Okazaki
S
,
O'Leary
DH
,
Polak
JF
,
Price
JF
,
Robertson
C
,
Rembold
CM
,
Rosvall
M
,
Rundek
T
,
Salonen
JT
,
Sitzer
M
,
Stehouwer
CD
,
Witteman
JC
,
Moons
KG
,
Bots
ML.
Common carotid intima-media thickness measurements in cardiovascular risk
prediction: a meta-analysis
.
JAMA
2012
;
308
:
796
–
803
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
25

Lorenz
MW
,
Schaefer
C
,
Steinmetz
H
,
Sitzer
M.
Is carotid intima media thickness useful for individual prediction of
cardiovascular risk? Ten-year results from the Carotid Atherosclerosis
Progression Study (CAPS)
.
Eur Heart J
2010
;
31
:
2041
–
2048
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
26

Garg
PK
,
Jorgensen
NW
,
McClelland
RL
,
Leigh
JA
,
Greenland
P
,
Blaha
MJ
,
Yoon
AJ
,
Wong
ND
,
Yeboah
J
,
Budoff
MJ.
Use of coronary artery calcium testing to improve coronary heart disease risk
assessment in a lung cancer screening population: the Multi-Ethnic Study of
Atherosclerosis (MESA)
.
J Cardiovasc Comput Tomogr
2018
;
12
:
493
–
499
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
27

Hong
JC
,
Blankstein
R
,
Shaw
LJ
,
Padula
WV
,
Arrieta
A
,
Fialkow
JA
,
Blumenthal
RS
,
Blaha
MJ
,
Krumholz
HM
,
Nasir
K.
Implications of coronary artery calcium testing for treatment decisions among
statin candidates according to the ACC/AHA cholesterol management guidelines: a
cost-effectiveness analysis
.
JACC Cardiovasc Imaging
2017
;
10
:
938
–
952
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
28

Cho
I
,
Al'Aref
SJ
,
Berger
AB OH
,
Gransar
H
,
Valenti
V
,
Lin
FY
,
Achenbach
S
,
Berman
DS
,
Budoff
MJ
,
Callister
TQ
,
Al-Mallah
MH
,
Cademartiri
F
,
Chinnaiyan
K
,
Chow
BJW
,
DeLago
A
,
Villines
TC
,
Hadamitzky
M
,
Hausleiter
J
,
Leipsic
J
,
Shaw
LJ
,
Kaufmann
PA
,
Feuchtner
G
,
Kim
YJ
,
Maffei
E
,
Raff
G
,
Pontone
G
,
Andreini
D
,
Marques
H
,
Rubinshtein
R
,
Chang
HJ
,
Min
JK.
Prognostic value of coronary computed tomographic angiography findings in
asymptomatic individuals: a 6-year follow-up from the prospective multicentre
international CONFIRM study
.
Eur Heart J
2018
;
39
:
934
–
941
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
29

Kavousi
M
,
Desai
CS
,
Ayers
C
,
Blumenthal
RS
,
Budoff
MJ
,
Mahabadi
AA
,
Ikram
MA
,
van der Lugt
A
,
Hofman
A
,
Erbel
R
,
Khera
A
,
Geisel
MH
,
Jockel
KH
,
Lehmann
N
,
Hoffmann
U
,
O'Donnell
CJ
,
Massaro
JM
,
Liu
K
,
Mohlenkamp
S
,
Ning
H
,
Franco
OH
,
Greenland
P.
Prevalence and prognostic implications of coronary artery calcification in
low-risk women: a meta-analysis
.
JAMA
2016
;
316
:
2126
–
2134
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
30

Lorenz
MW
,
Polak
JF
,
Kavousi
M
,
Mathiesen
EB
,
Volzke
H
,
Tuomainen
TP
,
Sander
D
,
Plichart
M
,
Catapano
AL
,
Robertson
CM
,
Kiechl
S
,
Rundek
T
,
Desvarieux
M
,
Lind
L
,
Schmid
C
,
DasMahapatra
P
,
Gao
L
,
Ziegelbauer
K
,
Bots
ML
,
Thompson
SG
; PROG-IMT Study Group.
Carotid intima-media thickness progression to predict cardiovascular events in
the general population (the PROG-IMT collaborative project): a meta-analysis of
individual participant data
.
Lancet
2012
;
379
:
2053
–
2062
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
31

Boekholdt
SM
,
Hovingh
GK
,
Mora
S
,
Arsenault
BJ
,
Amarenco
P
,
Pedersen
TR
,
LaRosa
JC
,
Waters
DD
,
DeMicco
DA
,
Simes
RJ
,
Keech
AC
,
Colquhoun
D
,
Hitman
GA
,
Betteridge
DJ
,
Clearfield
MB
,
Downs
JR
,
Colhoun
HM
,
Gotto
AM
Jr,
Ridker
PM
,
Grundy
SM
,
Kastelein
JJ.
Very low levels of atherogenic lipoproteins and the risk for cardiovascular
events: a meta-analysis of statin trials
.
J Am Coll Cardiol
2014
;
64
:
485
–
494
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
32

Brugts
JJ
,
Yetgin
T
,
Hoeks
SE
,
Gotto
AM
,
Shepherd
J
,
Westendorp
RG
,
de Craen
AJ
,
Knopp
RH
,
Nakamura
H
,
Ridker
P
,
van Domburg
R
,
Deckers
JW.
The benefits of statins in people without established cardiovascular disease but
with cardiovascular risk factors: meta-analysis of randomised controlled trials
.
BMJ
2009
;
338
:
b2376
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
33

Cannon
CP
,
Blazing
MA
,
Giugliano
RP
,
McCagg
A
,
White
JA
,
Theroux
P
,
Darius
H
,
Lewis
BS
,
Ophuis
TO
,
Jukema
JW
,
De Ferrari
GM
,
Ruzyllo
W
,
De Lucca
P
,
Im
K
,
Bohula
EA
,
Reist
C
,
Wiviott
SD
,
Tershakovec
AM
,
Musliner
TA
,
Braunwald
E
,
Califf
RM
; IMPROVE-IT Investigators.
Ezetimibe added to statin therapy after acute coronary syndromes
.
N Engl J Med
2015
;
372
:
2387
–
2397
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
34

Cholesterol Treatment Trialists Collaboration,

Baigent
C
,
Blackwell
L
,
Emberson
J
,
Holland
LE
,
Reith
C
,
Bhala
N
,
Peto
R
,
Barnes
EH
,
Keech
A
,
Simes
J
,
Collins
R.
Efficacy and safety of more intensive lowering of LDL cholesterol: a
meta-analysis of data from 170,000 participants in 26 randomised trials
.
Lancet
2010
;
376
:
1670
–
1681
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
35

Cholesterol Treatment Trialists Collaboration,

Fulcher
J
,
O'Connell
R
,
Voysey
M
,
Emberson
J
,
Blackwell
L
,
Mihaylova
B
,
Simes
J
,
Collins
R
,
Kirby
A
,
Colhoun
H
,
Braunwald
E
,
La Rosa
J
,
Pedersen
TR
,
Tonkin
A
,
Davis
B
,
Sleight
P
,
Franzosi
MG
,
Baigent
C
,
Keech
A.
Efficacy and safety of LDL-lowering therapy among men and women: meta-analysis
of individual data from 174,000 participants in 27 randomised trials
.
Lancet
2015
;
385
:
1397
–
1405
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
36

Cholesterol Treatment Trialists Collaboration,

Mihaylova
B
,
Emberson
J
,
Blackwell
L
,
Keech
A
,
Simes
J
,
Barnes
EH
,
Voysey
M
,
Gray
A
,
Collins
R
,
Baigent
C.
The effects of lowering LDL cholesterol with statin therapy in people at low
risk of vascular disease: meta-analysis of individual data from 27 randomised
trials
.
Lancet
2012
;
380
:
581
–
590
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
37

Hegele
RA
,
Ginsberg
HN
,
Chapman
MJ
,
Nordestgaard
BG
,
Kuivenhoven
JA
,
Averna
M
,
Boren
J
,
Bruckert
E
,
Catapano
AL
,
Descamps
OS
,
Hovingh
GK
,
Humphries
SE
,
Kovanen
PT
,
Masana
L
,
Pajukanta
P
,
Parhofer
KG
,
Raal
FJ
,
Ray
KK
,
Santos
RD
,
Stalenhoef
AF
,
Stroes
E
,
Taskinen
MR
,
Tybjaerg-Hansen
A
,
Watts
GF
,
Wiklund
O
; European Atherosclerosis Society Consensus Panel.
The polygenic nature of hypertriglyceridaemia: implications for definition,
diagnosis, and management
.
Lancet Diabetes Endocrinol
2014
;
2
:
655
–
666
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
38

Mills
EJ
,
Rachlis
B
,
Wu
P
,
Devereaux
PJ
,
Arora
P
,
Perri
D.
Primary prevention of cardiovascular mortality and events with statin
treatments: a network meta-analysis involving more than 65,000 patients
.
J Am Coll Cardiol
2008
;
52
:
1769
–
1781
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
39

Pedersen
TR
,
Faergeman
O
,
Kastelein
JJ
,
Olsson
AG
,
Tikkanen
MJ
,
Holme
I
,
Larsen
ML
,
Bendiksen
FS
,
Lindahl
C
,
Szarek
M
,
Tsai
J
;
Incremental Decrease in End Points Through Aggressive Lipid Lowering (IDEAL)
Study Group. High-dose atorvastatin vs usual-dose simvastatin for secondary
prevention after myocardial infarction: the IDEAL study: a randomized controlled
trial
.
JAMA
2005
;
294
:
2437
–
2445
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
40

Stone
NJ
,
Robinson
JG
,
Lichtenstein
AH
,
Bairey Merz
CN
,
Blum
CB
,
Eckel
RH
,
Goldberg
AC
,
Gordon
D
,
Levy
D
,
Lloyd-Jones
DM
,
McBride
P
,
Schwartz
JS
,
Shero
ST
,
Smith
SC
Jr,
Watson
K
,
Wilson
PW
,
Eddleman
KM
,
Jarrett
NM
,
LaBresh
K
,
Nevo
L
,
Wnek
J
,
Anderson
JL
,
Halperin
JL
,
Albert
NM
,
Bozkurt
B
,
Brindis
RG
,
Curtis
LH
,
DeMets
D
,
Hochman
JS
,
Kovacs
RJ
,
Ohman
EM
,
Pressler
SJ
,
Sellke
FW
,
Shen
WK
,
Smith
SC
Jr,
Tomaselli
GF
; American College of Cardiology/American Heart Association Task Force on
Practice Guidelines.
2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce
atherosclerotic cardiovascular risk in adults: a report of the American College
of Cardiology/American Heart Association Task Force on Practice Guidelines
.
Circulation
2014
;
129
:
S1
–
S45
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
41

Vallejo-Vaz
AJ
,
Robertson
M
,
Catapano
AL
,
Watts
GF
,
Kastelein
JJ
,
Packard
CJ
,
Ford
I
,
Ray
KK.
Low-density lipoprotein cholesterol lowering for the primary prevention of
cardiovascular disease among men with primary elevations of low-density
lipoprotein cholesterol levels of 190 mg/dL or above: analyses from the WOSCOPS
(West of Scotland Coronary Prevention Study) 5-year randomized trial and 20-year
observational follow-up
.
Circulation
2017
;
136
:
1878
–
1891
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
42

Tabas
I
,
Williams
KJ
,
Boren
J.
Subendothelial lipoprotein retention as the initiating process in
atherosclerosis: update and therapeutic implications
.
Circulation
2007
;
116
:
1832
–
1844
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
43

Boren
J
,
Williams
KJ.
The central role of arterial retention of cholesterol-rich
apolipoprotein-B-containing lipoproteins in the pathogenesis of atherosclerosis:
a triumph of simplicity
.
Curr Opin Lipidol
2016
;
27
:
473
–
483
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
44

Ference
BA
,
Graham
I
,
Tokgozoglu
L
,
Catapano
AL.
Impact of lipids on cardiovascular health: JACC Health Promotion Series
.
J Am Coll Cardiol
2018
;
72
:
1141
–
1156
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
45

Emerging Risk Factors Collaboration,

Di Angelantonio
E
,
Gao
P
,
Pennells
L
,
Kaptoge
S
,
Caslake
M
,
Thompson
A
,
Butterworth
AS
,
Sarwar
N
,
Wormser
D
,
Saleheen
D
,
Ballantyne
CM
,
Psaty
BM
,
Sundstrom
J
,
Ridker
PM
,
Nagel
D
,
Gillum
RF
,
Ford
I
,
Ducimetiere
P
,
Kiechl
S
,
Koenig
W
,
Dullaart
RP
,
Assmann
G
,
D'Agostino
RB
Sr,
Dagenais
GR
,
Cooper
JA
,
Kromhout
D
,
Onat
A
,
Tipping
RW
,
Gomez-de-la-Camara
A
,
Rosengren
A
,
Sutherland
SE
,
Gallacher
J
,
Fowkes
FG
,
Casiglia
E
,
Hofman
A
,
Salomaa
V
,
Barrett-Connor
E
,
Clarke
R
,
Brunner
E
,
Jukema
JW
,
Simons
LA
,
Sandhu
M
,
Wareham
NJ
,
Khaw
KT
,
Kauhanen
J
,
Salonen
JT
,
Howard
WJ
,
Nordestgaard
BG
,
Wood
AM
,
Thompson
SG
,
Boekholdt
SM
,
Sattar
N
,
Packard
C
,
Gudnason
V
,
Danesh
J.
Lipid-related markers and cardiovascular disease prediction
.
JAMA
2012
;
307
:
2499
–
2506
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
46

Willer
CJ
,
Schmidt
EM
,
Sengupta
S
,
Peloso
GM
,
Gustafsson
S
,
Kanoni
S
,
Ganna
A
,
Chen
J
,
Buchkovich
ML
,
Mora
S
,
Beckmann
JS
,
Bragg-Gresham
JL
,
Chang
HY
,
Demirkan
A
,
Den Hertog
HM
,
Do
R
,
Donnelly
LA
,
Ehret
GB
,
Esko
T
,
Feitosa
MF
,
Ferreira
T
,
Fischer
K
,
Fontanillas
P
,
Fraser
RM
,
Freitag
DF
,
Gurdasani
D
,
Heikkila
K
,
Hypponen
E
,
Isaacs
A
,
Jackson
AU
,
Johansson
A
,
Johnson
T
,
Kaakinen
M
,
Kettunen
J
,
Kleber
ME
,
Li
X
,
Luan
J
,
Lyytikainen
LP
,
Magnusson
PKE
,
Mangino
M
,
Mihailov
E
,
Montasser
ME
,
Muller-Nurasyid
M
,
Nolte
IM
,
O'Connell
JR
,
Palmer
CD
,
Perola
M
,
Petersen
AK
,
Sanna
S
,
Saxena
R
,
Service
SK
,
Shah
S
,
Shungin
D
,
Sidore
C
,
Song
C
,
Strawbridge
RJ
,
Surakka
I
,
Tanaka
T
,
Teslovich
TM
,
Thorleifsson
G
,
Van den Herik
EG
,
Voight
BF
,
Volcik
KA
,
Waite
LL
,
Wong
A
,
Wu
Y
,
Zhang
W
,
Absher
D
,
Asiki
G
,
Barroso
I
,
Been
LF
,
Bolton
JL
,
Bonnycastle
LL
,
Brambilla
P
,
Burnett
MS
,
Cesana
G
,
Dimitriou
M
,
Doney
ASF
,
Doring
A
,
Elliott
P
,
Epstein
SE
,
Ingi Eyjolfsson
G
,
Gigante
B
,
Goodarzi
MO
,
Grallert
H
,
Gravito
ML
,
Groves
CJ
,
Hallmans
G
,
Hartikainen
AL
,
Hayward
C
,
Hernandez
D
,
Hicks
AA
,
Holm
H
,
Hung
YJ
,
Illig
T
,
Jones
MR
,
Kaleebu
P
,
Kastelein
JJP
,
Khaw
KT
,
Kim
E
,
Klopp
N
,
Komulainen
P
,
Kumari
M
,
Langenberg
C
,
Lehtimaki
T
,
Lin
SY
,
Lindstrom
J
,
Loos
RJF
,
Mach
F
,
McArdle
WL
,
Meisinger
C
,
Mitchell
BD
,
Muller
G
,
Nagaraja
R
,
Narisu
N
,
Nieminen
TVM
,
Nsubuga
RN
,
Olafsson
I
,
Ong
KK
,
Palotie
A
,
Papamarkou
T
,
Pomilla
C
,
Pouta
A
,
Rader
DJ
,
Reilly
MP
,
Ridker
PM
,
Rivadeneira
F
,
Rudan
I
,
Ruokonen
A
,
Samani
N
,
Scharnagl
H
,
Seeley
J
,
Silander
K
,
Stancakova
A
,
Stirrups
K
,
Swift
AJ
,
Tiret
L
,
Uitterlinden
AG
,
van Pelt
LJ
,
Vedantam
S
,
Wainwright
N
,
Wijmenga
C
,
Wild
SH
,
Willemsen
G
,
Wilsgaard
T
,
Wilson
JF
,
Young
EH
,
Zhao
JH
,
Adair
LS
,
Arveiler
D
,
Assimes
TL
,
Bandinelli
S
,
Bennett
F
,
Bochud
M
,
Boehm
BO
,
Boomsma
DI
,
Borecki
IB
,
Bornstein
SR
,
Bovet
P
,
Burnier
M
,
Campbell
H
,
Chakravarti
A
,
Chambers
JC
,
Chen
YI
,
Collins
FS
,
Cooper
RS
,
Danesh
J
,
Dedoussis
G
,
de Faire
U
,
Feranil
AB
,
Ferrieres
J
,
Ferrucci
L
,
Freimer
NB
,
Gieger
C
,
Groop
LC
,
Gudnason
V
,
Gyllensten
U
,
Hamsten
A
,
Harris
TB
,
Hingorani
A
,
Hirschhorn
JN
,
Hofman
A
,
Hovingh
GK
,
Hsiung
CA
,
Humphries
SE
,
Hunt
SC
,
Hveem
K
,
Iribarren
C
,
Jarvelin
MR
,
Jula
A
,
Kahonen
M
,
Kaprio
J
,
Kesaniemi
A
,
Kivimaki
M
,
Kooner
JS
,
Koudstaal
PJ
,
Krauss
RM
,
Kuh
D
,
Kuusisto
J
,
Kyvik
KO
,
Laakso
M
,
Lakka
TA
,
Lind
L
,
Lindgren
CM
,
Martin
NG
,
Marz
W
,
McCarthy
MI
,
McKenzie
CA
,
Meneton
P
,
Metspalu
A
,
Moilanen
L
,
Morris
AD
,
Munroe
PB
,
Njolstad
I
,
Pedersen
NL
,
Power
C
,
Pramstaller
PP
,
Price
JF
,
Psaty
BM
,
Quertermous
T
,
Rauramaa
R
,
Saleheen
D
,
Salomaa
V
,
Sanghera
DK
,
Saramies
J
,
Schwarz
PEH
,
Sheu
WH
,
Shuldiner
AR
,
Siegbahn
A
,
Spector
TD
,
Stefansson
K
,
Strachan
DP
,
Tayo
BO
,
Tremoli
E
,
Tuomilehto
J
,
Uusitupa
M
,
van Duijn
CM
,
Vollenweider
P
,
Wallentin
L
,
Wareham
NJ
,
Whitfield
JB
,
Wolffenbuttel
BHR
,
Ordovas
JM
,
Boerwinkle
E
,
Palmer
CNA
,
Thorsteinsdottir
U
,
Chasman
DI
,
Rotter
JI
,
Franks
PW
,
Ripatti
S
,
Cupples
LA
,
Sandhu
MS
,
Rich
SS
,
Boehnke
M
,
Deloukas
P
,
Kathiresan
S
,
Mohlke
KL
,
Ingelsson
E
,
Abecasis
GR
; Global Lipids Genetics Consortium.
Discovery and refinement of loci associated with lipid levels
.
Nat Genet
2013
;
45
:
1274
–
1283
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
47

Nikpay
M
,
Goel
A
,
Won
HH
,
Hall
LM
,
Willenborg
C
,
Kanoni
S
,
Saleheen
D
,
Kyriakou
T
,
Nelson
CP
,
Hopewell
JC
,
Webb
TR
,
Zeng
L
,
Dehghan
A
,
Alver
M
,
Armasu
SM
,
Auro
K
,
Bjonnes
A
,
Chasman
DI
,
Chen
S
,
Ford
I
,
Franceschini
N
,
Gieger
C
,
Grace
C
,
Gustafsson
S
,
Huang
J
,
Hwang
SJ
,
Kim
YK
,
Kleber
ME
,
Lau
KW
,
Lu
X
,
Lu
Y
,
Lyytikainen
LP
,
Mihailov
E
,
Morrison
AC
,
Pervjakova
N
,
Qu
L
,
Rose
LM
,
Salfati
E
,
Saxena
R
,
Scholz
M
,
Smith
AV
,
Tikkanen
E
,
Uitterlinden
A
,
Yang
X
,
Zhang
W
,
Zhao
W
,
de Andrade
M
,
de Vries
PS
,
van Zuydam
NR
,
Anand
SS
,
Bertram
L
,
Beutner
F
,
Dedoussis
G
,
Frossard
P
,
Gauguier
D
,
Goodall
AH
,
Gottesman
O
,
Haber
M
,
Han
BG
,
Huang
J
,
Jalilzadeh
S
,
Kessler
T
,
Konig
IR
,
Lannfelt
L
,
Lieb
W
,
Lind
L
,
Lindgren
CM
,
Lokki
ML
,
Magnusson
PK
,
Mallick
NH
,
Mehra
N
,
Meitinger
T
,
Memon
FU
,
Morris
AP
,
Nieminen
MS
,
Pedersen
NL
,
Peters
A
,
Rallidis
LS
,
Rasheed
A
,
Samuel
M
,
Shah
SH
,
Sinisalo
J
,
Stirrups
KE
,
Trompet
S
,
Wang
L
,
Zaman
KS
,
Ardissino
D
,
Boerwinkle
E
,
Borecki
IB
,
Bottinger
EP
,
Buring
JE
,
Chambers
JC
,
Collins
R
,
Cupples
LA
,
Danesh
J
,
Demuth
I
,
Elosua
R
,
Epstein
SE
,
Esko
T
,
Feitosa
MF
,
Franco
OH
,
Franzosi
MG
,
Granger
CB
,
Gu
D
,
Gudnason
V
,
Hall
AS
,
Hamsten
A
,
Harris
TB
,
Hazen
SL
,
Hengstenberg
C
,
Hofman
A
,
Ingelsson
E
,
Iribarren
C
,
Jukema
JW
,
Karhunen
PJ
,
Kim
BJ
,
Kooner
JS
,
Kullo
IJ
,
Lehtimaki
T
,
Loos
RJF
,
Melander
O
,
Metspalu
A
,
Marz
W
,
Palmer
CN
,
Perola
M
,
Quertermous
T
,
Rader
DJ
,
Ridker
PM
,
Ripatti
S
,
Roberts
R
,
Salomaa
V
,
Sanghera
DK
,
Schwartz
SM
,
Seedorf
U
,
Stewart
AF
,
Stott
DJ
,
Thiery
J
,
Zalloua
PA
,
O'Donnell
CJ
,
Reilly
MP
,
Assimes
TL
,
Thompson
JR
,
Erdmann
J
,
Clarke
R
,
Watkins
H
,
Kathiresan
S
,
McPherson
R
,
Deloukas
P
,
Schunkert
H
,
Samani
NJ
,
Farrall
M.
A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of
coronary artery disease
.
Nat Genet
2015
;
47
:
1121
–
1130
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
48

Ference
BA
,
Yoo
W
,
Alesh
I
,
Mahajan
N
,
Mirowska
KK
,
Mewada
A
,
Kahn
J
,
Afonso
L
,
Williams
KA
Sr,
Flack
JM.
Effect of long-term exposure to lower low-density lipoprotein cholesterol
beginning early in life on the risk of coronary heart disease: a Mendelian
randomization analysis
.
J Am Coll Cardiol
2012
;
60
:
2631
–
2639
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
49

Holmes
MV
,
Asselbergs
FW
,
Palmer
TM
,
Drenos
F
,
Lanktree
MB
,
Nelson
CP
,
Dale
CE
,
Padmanabhan
S
,
Finan
C
,
Swerdlow
DI
,
Tragante
V
,
van Iperen
EP
,
Sivapalaratnam
S
,
Shah
S
,
Elbers
CC
,
Shah
T
,
Engmann
J
,
Giambartolomei
C
,
White
J
,
Zabaneh
D
,
Sofat
R
,
McLachlan
S
,
consortium
U
,
Doevendans
PA
,
Balmforth
AJ
,
Hall
AS
,
North
KE
,
Almoguera
B
,
Hoogeveen
RC
,
Cushman
M
,
Fornage
M
,
Patel
SR
,
Redline
S
,
Siscovick
DS
,
Tsai
MY
,
Karczewski
KJ
,
Hofker
MH
,
Verschuren
WM
,
Bots
ML
,
van der Schouw
YT
,
Melander
O
,
Dominiczak
AF
,
Morris
R
,
Ben-Shlomo
Y
,
Price
J
,
Kumari
M
,
Baumert
J
,
Peters
A
,
Thorand
B
,
Koenig
W
,
Gaunt
TR
,
Humphries
SE
,
Clarke
R
,
Watkins
H
,
Farrall
M
,
Wilson
JG
,
Rich
SS
,
de Bakker
PI
,
Lange
LA
,
Davey Smith
G
,
Reiner
AP
,
Talmud
PJ
,
Kivimaki
M
,
Lawlor
DA
,
Dudbridge
F
,
Samani
NJ
,
Keating
BJ
,
Hingorani
AD
,
Casas
JP.
Mendelian randomization of blood lipids for coronary heart disease
.
Eur Heart J
2015
;
36
:
539
–
550
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
50

Silverman
MG
,
Ference
BA
,
Im
K
,
Wiviott
SD
,
Giugliano
RP
,
Grundy
SM
,
Braunwald
E
,
Sabatine
MS.
Association between lowering LDL-C and cardiovascular risk reduction among
different therapeutic interventions: a systematic review and meta-analysis
.
JAMA
2016
;
316
:
1289
–
1297
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
51

Baigent
C
,
Keech
A
,
Kearney
PM
,
Blackwell
L
,
Buck
G
,
Pollicino
C
,
Kirby
A
,
Sourjina
T
,
Peto
R
,
Collins
R
,
Simes
R
; Cholesterol Treatment Trialists' (CTT) Collaborators.
Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis
of data from 90,056 participants in 14 randomised trials of statins
.
Lancet
2005
;
366
:
1267
–
1278
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
52

Cohen
JC
,
Boerwinkle
E
,
Mosley
TH
Jr,
Hobbs
HH.
Sequence variations in PCSK9, low LDL, and protection against coronary heart
disease
.
N Engl J Med
2006
;
354
:
1264
–
1272
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
53

Ference
BA
,
Kastelein
JJP
,
Ray
KK
,
Ginsberg
HN
,
Chapman
MJ
,
Packard
CJ
,
Laufs
U
,
Oliver-Williams
C
,
Wood
AM
,
Butterworth
AS
,
Di Angelantonio
E
,
Danesh
J
,
Nicholls
SJ
,
Bhatt
DL
,
Sabatine
MS
,
Catapano
AL.
Association of triglyceride-lowering LPL variants and LDL-C-lowering LDLR
variants with risk of coronary heart disease
.
JAMA
2019
;
321
:
364
–
373
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
54

Ference
BA
,
Majeed
F
,
Penumetcha
R
,
Flack
JM
,
Brook
RD.
Effect of naturally random allocation to lower low-density lipoprotein
cholesterol on the risk of coronary heart disease mediated by polymorphisms in
NPC1L1, HMGCR, or both: a 2 x 2 factorial Mendelian randomization study
.
J Am Coll Cardiol
2015
;
65
:
1552
–
1561
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
55

Ference
BA
,
Robinson
JG
,
Brook
RD
,
Catapano
AL
,
Chapman
MJ
,
Neff
DR
,
Voros
S
,
Giugliano
RP
,
Davey Smith
G
,
Fazio
S
,
Sabatine
MS.
Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes
.
N Engl J Med
2016
;
375
:
2144
–
2153
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
56

Triglyceride Coronary Disease Genetics Consortium, Emerging Risk Factors
Collaboration,

Sarwar
N
,
Sandhu
MS
,
Ricketts
SL
,
Butterworth
AS
,
Di Angelantonio
E
,
Boekholdt
SM
,
Ouwehand
W
,
Watkins
H
,
Samani
NJ
,
Saleheen
D
,
Lawlor
D
,
Reilly
MP
,
Hingorani
AD
,
Talmud
PJ
,
Danesh
J.
Triglyceride-mediated pathways and coronary disease: collaborative analysis of
101 studies
.
Lancet
2010
;
375
:
1634
–
1639
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
57

Varbo
A
,
Benn
M
,
Tybjaerg-Hansen
A
,
Jorgensen
AB
,
Frikke-Schmidt
R
,
Nordestgaard
BG.
Remnant cholesterol as a causal risk factor for ischemic heart disease
.
J Am Coll Cardiol
2013
;
61
:
427
–
436
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
58

Lewis
GF
,
Xiao
C
,
Hegele
RA.
Hypertriglyceridemia in the genomic era: a new paradigm
.
Endocr Rev
2015
;
36
:
131
–
147
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
59

Dron
JS
,
Hegele
RA.
Complexity of mechanisms among human proprotein convertase subtilisin-kexin type
9 variants
.
Curr Opin Lipidol
2017
;
28
:
161
–
169
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
60

Prospective Studies Collaboration,

Lewington
S
,
Whitlock
G
,
Clarke
R
,
Sherliker
P
,
Emberson
J
,
Halsey
J
,
Qizilbash
N
,
Peto
R
,
Collins
R.
Blood cholesterol and vascular mortality by age, sex, and blood pressure: a
meta-analysis of individual data from 61 prospective studies with 55,000
vascular deaths
.
Lancet
2007
;
370
:
1829
–
1839
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
61

Frikke-Schmidt
R
,
Nordestgaard
BG
,
Stene
MC
,
Sethi
AA
,
Remaley
AT
,
Schnohr
P
,
Grande
P
,
Tybjaerg-Hansen
A.
Association of loss-of-function mutations in the ABCA1 gene with high-density
lipoprotein cholesterol levels and risk of ischemic heart disease
.
JAMA
2008
;
299
:
2524
–
2532
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
62

Voight
BF
,
Peloso
GM
,
Orho-Melander
M
,
Frikke-Schmidt
R
,
Barbalic
M
,
Jensen
MK
,
Hindy
G
,
Holm
H
,
Ding
EL
,
Johnson
T
,
Schunkert
H
,
Samani
NJ
,
Clarke
R
,
Hopewell
JC
,
Thompson
JF
,
Li
M
,
Thorleifsson
G
,
Newton-Cheh
C
,
Musunuru
K
,
Pirruccello
JP
,
Saleheen
D
,
Chen
L
,
Stewart
A
,
Schillert
A
,
Thorsteinsdottir
U
,
Thorgeirsson
G
,
Anand
S
,
Engert
JC
,
Morgan
T
,
Spertus
J
,
Stoll
M
,
Berger
K
,
Martinelli
N
,
Girelli
D
,
McKeown
PP
,
Patterson
CC
,
Epstein
SE
,
Devaney
J
,
Burnett
MS
,
Mooser
V
,
Ripatti
S
,
Surakka
I
,
Nieminen
MS
,
Sinisalo
J
,
Lokki
ML
,
Perola
M
,
Havulinna
A
,
de Faire
U
,
Gigante
B
,
Ingelsson
E
,
Zeller
T
,
Wild
P
,
de Bakker
PI
,
Klungel
OH
,
Maitland-van der Zee
AH
,
Peters
BJ
,
de Boer
A
,
Grobbee
DE
,
Kamphuisen
PW
,
Deneer
VH
,
Elbers
CC
,
Onland-Moret
NC
,
Hofker
MH
,
Wijmenga
C
,
Verschuren
WM
,
Boer
JM
,
van der Schouw
YT
,
Rasheed
A
,
Frossard
P
,
Demissie
S
,
Willer
C
,
Do
R
,
Ordovas
JM
,
Abecasis
GR
,
Boehnke
M
,
Mohlke
KL
,
Daly
MJ
,
Guiducci
C
,
Burtt
NP
,
Surti
A
,
Gonzalez
E
,
Purcell
S
,
Gabriel
S
,
Marrugat
J
,
Peden
J
,
Erdmann
J
,
Diemert
P
,
Willenborg
C
,
Konig
IR
,
Fischer
M
,
Hengstenberg
C
,
Ziegler
A
,
Buysschaert
I
,
Lambrechts
D
,
Van de Werf
F
,
Fox
KA
,
El Mokhtari
NE
,
Rubin
D
,
Schrezenmeir
J
,
Schreiber
S
,
Schafer
A
,
Danesh
J
,
Blankenberg
S
,
Roberts
R
,
McPherson
R
,
Watkins
H
,
Hall
AS
,
Overvad
K
,
Rimm
E
,
Boerwinkle
E
,
Tybjaerg-Hansen
A
,
Cupples
LA
,
Reilly
MP
,
Melander
O
,
Mannucci
PM
,
Ardissino
D
,
Siscovick
D
,
Elosua
R
,
Stefansson
K
,
O'Donnell
CJ
,
Salomaa
V
,
Rader
DJ
,
Peltonen
L
,
Schwartz
SM
,
Altshuler
D
,
Kathiresan
S.
Plasma HDL cholesterol and risk of myocardial infarction: a Mendelian
randomisation study
.
Lancet
2012
;
380
:
572
–
580
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
63

Lincoff
AM
,
Nicholls
SJ
,
Riesmeyer
JS
,
Barter
PJ
,
Brewer
HB
,
Fox
KAA
,
Gibson
CM
,
Granger
C
,
Menon
V
,
Montalescot
G
,
Rader
D
,
Tall
AR
,
McErlean
E
,
Wolski
K
,
Ruotolo
G
,
Vangerow
B
,
Weerakkody
G
,
Goodman
SG
,
Conde
D
,
McGuire
DK
,
Nicolau
JC
,
Leiva-Pons
JL
,
Pesant
Y
,
Li
W
,
Kandath
D
,
Kouz
S
,
Tahirkheli
N
,
Mason
D
,
Nissen
SE
; ACCELERATE Investigators.
Evacetrapib and cardiovascular outcomes in high-risk vascular disease
.
N Engl J Med
2017
;
376
:
1933
–
1942
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
64

HPS/TIMI/REVEAL Collaborative Group,

Bowman
L
,
Hopewell
JC
,
Chen
F
,
Wallendszus
K
,
Stevens
W
,
Collins
R
,
Wiviott
SD
,
Cannon
CP
,
Braunwald
E
,
Sammons
E
,
Landray
MJ.
Effects of anacetrapib in patients with atherosclerotic vascular disease
.
N Engl J Med
2017
;
377
:
1217
–
1227
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
65

Schwartz
GG
,
Olsson
AG
,
Abt
M
,
Ballantyne
CM
,
Barter
PJ
,
Brumm
J
,
Chaitman
BR
,
Holme
IM
,
Kallend
D
,
Leiter
LA
,
Leitersdorf
E
,
McMurray
JJ
,
Mundl
H
,
Nicholls
SJ
,
Shah
PK
,
Tardif
JC
,
Wright
RS
; dal-OUTCOMES Investigators.
Effects of dalcetrapib in patients with a recent acute coronary syndrome
.
N Engl J Med
2012
;
367
:
2089
–
2099
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
66

Aim-High Investigators,

Boden
WE
,
Probstfield
JL
,
Anderson
T
,
Chaitman
BR
,
Desvignes-Nickens
P
,
Koprowicz
K
,
McBride
R
,
Teo
K
,
Weintraub
W.
Niacin in patients with low HDL cholesterol levels receiving intensive statin
therapy
.
N Engl J Med
2011
;
365
:
2255
–
2267
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
67

Group
HTC
,
Landray
MJ
,
Haynes
R
,
Hopewell
JC
,
Parish
S
,
Aung
T
,
Tomson
J
,
Wallendszus
K
,
Craig
M
,
Jiang
L
,
Collins
R
,
Armitage
J.
Effects of extended-release niacin with laropiprant in high-risk patients
.
N Engl J Med
2014
;
371
:
203
–
212
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
68

Andrews
J
,
Janssan
A
,
Nguyen
T
,
Pisaniello
AD
,
Scherer
DJ
,
Kastelein
JJ
,
Merkely
B
,
Nissen
SE
,
Ray
K
,
Schwartz
GG
,
Worthley
SG
,
Keyserling
C
,
Dasseux
JL
,
Butters
J
,
Girardi
J
,
Miller
R
,
Nicholls
SJ.
Effect of serial infusions of reconstituted high-density lipoprotein (CER-001)
on coronary atherosclerosis: rationale and design of the CARAT study
.
Cardiovasc Diagn Ther
2017
;
7
:
45
–
51
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
69

Tardif
JC
,
Ballantyne
CM
,
Barter
P
,
Dasseux
JL
,
Fayad
ZA
,
Guertin
MC
,
Kastelein
JJ
,
Keyserling
C
,
Klepp
H
,
Koenig
W
,
L'Allier
PL
,
Lesperance
J
,
Luscher
TF
,
Paolini
JF
,
Tawakol
A
,
Waters
DD
; Can HDL Infusions Significantly QUicken Atherosclerosis REgression
(CHI-SQUARE) Investigators.
Effects of the high-density lipoprotein mimetic agent CER-001 on coronary
atherosclerosis in patients with acute coronary syndromes: a randomized trial
.
Eur Heart J
2014
;
35
:
3277
–
3286
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
70

Nordestgaard
BG
,
Langsted
A.
Lipoprotein (a) as a cause of cardiovascular disease: insights from
epidemiology, genetics, and biology
.
J Lipid Res
2016
;
57
:
1953
–
1975
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
71

van der Valk
FM
,
Bekkering
S
,
Kroon
J
,
Yeang
C
,
Van den Bossche
J
,
van Buul
JD
,
Ravandi
A
,
Nederveen
AJ
,
Verberne
HJ
,
Scipione
C
,
Nieuwdorp
M
,
Joosten
LA
,
Netea
MG
,
Koschinsky
ML
,
Witztum
JL
,
Tsimikas
S
,
Riksen
NP
,
Stroes
ES.
Oxidized phospholipids on lipoprotein(a) elicit arterial wall inflammation and
an inflammatory monocyte response in humans
.
Circulation
2016
;
134
:
611
–
624
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
72

Nordestgaard
BG
,
Chapman
MJ
,
Ray
K
,
Borén
J
,
Andreotti
F
,
Watts
GF
,
Ginsberg
H
,
Amarenco
P
,
Catapano
A
,
Descamps
OS
,
Fisher
E
,
Kovanen
PT
,
Kuivenhoven
JA
,
Lesnik
P
,
Masana
L
,
Reiner
Z
,
Taskinen
MR
,
Tokgözoglu
L
,
Tybjærg-Hansen
A
; European Atherosclerosis Society Consensus Panel.
Lipoprotein(a) as a cardiovascular risk factor: current status
.
Eur Heart J
2010
;
31
:
2844
–
2853
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
73

Emerging Risk Factors Collaboration,

Erqou
S
,
Kaptoge
S
,
Perry
PL
,
Di Angelantonio
E
,
Thompson
A
,
White
IR
,
Marcovina
SM
,
Collins
R
,
Thompson
SG
,
Danesh
J.
Lipoprotein(a) concentration and the risk of coronary heart disease, stroke, and
nonvascular mortality
.
JAMA
2009
;
302
:
412
–
423
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
74

Clarke
R
,
Peden
JF
,
Hopewell
JC
,
Kyriakou
T
,
Goel
A
,
Heath
SC
,
Parish
S
,
Barlera
S
,
Franzosi
MG
,
Rust
S
,
Bennett
D
,
Silveira
A
,
Malarstig
A
,
Green
FR
,
Lathrop
M
,
Gigante
B
,
Leander
K
,
de Faire
U
,
Seedorf
U
,
Hamsten
A
,
Collins
R
,
Watkins
H
,
Farrall
M
; PROCARDIS Consortium.
Genetic variants associated with Lp(a) lipoprotein level and coronary disease
.
N Engl J Med
2009
;
361
:
2518
–
2528
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
75

Kamstrup
PR
,
Tybjaerg-Hansen
A
,
Steffensen
R
,
Nordestgaard
BG.
Genetically elevated lipoprotein(a) and increased risk of myocardial infarction
.
JAMA
2009
;
301
:
2331
–
2339
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
76

O'Donoghue
ML
,
Fazio
S
,
Giugliano
RP
,
Stroes
ESG
,
Kanevsky
E
,
Gouni-Berthold
I
,
Im
K
,
Lira Pineda
A
,
Wasserman
SM
,
Ceska
R
,
Ezhov
MV
,
Jukema
JW
,
Jensen
HK
,
Tokgozoglu
SL
,
Mach
F
,
Huber
K
,
Sever
PS
,
Keech
AC
,
Pedersen
TR
,
Sabatine
MS.
Lipoprotein(a), PCSK9 inhibition, and cardiovascular risk
.
Circulation
2019
;
139
:
1483
–
1492
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
77

Burgess
S
,
Ference
BA
,
Staley
JR
,
Freitag
DF
,
Mason
AM
,
Nielsen
SF
,
Willeit
P
,
Young
R
,
Surendran
P
,
Karthikeyan
S
,
Bolton
TR
,
Peters
JE
,
Kamstrup
PR
,
Tybjaerg-Hansen
A
,
Benn
M
,
Langsted
A
,
Schnohr
P
,
Vedel-Krogh
S
,
Kobylecki
CJ
,
Ford
I
,
Packard
C
,
Trompet
S
,
Jukema
JW
,
Sattar
N
,
Di Angelantonio
E
,
Saleheen
D
,
Howson
JMM
,
Nordestgaard
BG
,
Butterworth
AS
,
Danesh
J
; European Prospective Investigation Into Cancer and Nutrition–Cardiovascular
Disease (EPIC-CVD) Consortium.
Association of LPA variants with risk of coronary disease and the implications
for lipoprotein(a)-lowering therapies: a Mendelian randomization analysis
.
JAMA Cardiol
2018
;
3
:
619
–
627
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
78

Parish
S
,
Hopewell
JC
,
Hill
MR
,
Marcovina
S
,
Valdes-Marquez
E
,
Haynes
R
,
Offer
A
,
Pedersen
TR
,
Baigent
C
,
Collins
R
,
Landray
M
,
Armitage
J
;
HPS2-THRIVE Collaborative Group. Impact of apolipoprotein(a) isoform size on
lipoprotein(a) lowering in the HPS2-THRIVE Study
.
Circ Genom Precis Med
2018
;
11
:
e001696
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
79

Langlois
MR
,
Chapman
MJ
,
Cobbaert
C
,
Mora
S
,
Remaley
AT
,
Ros
E
,
Watts
GF
,
Borén
J
,
Baum
H
,
Bruckert
E
,
Catapano
A
,
Descamps
OS
,
von Eckardstein
A
,
Kamstrup
PR
,
Kolovou
G
,
Kronenberg
F
,
Langsted
A
,
Pulkki
K
,
Rifai
N
,
Sypniewska
G
,
Wiklund
O
,
Nordestgaard
BG
; European Atherosclerosis Society (EAS) and the European Federation of Clinical
Chemistry and Laboratory Medicine (EFLM) Joint Consensus Initiative.
Quantifying atherogenic lipoproteins: current and future challenges in the era
of personalized medicine and very low concentrations of LDL cholesterol. A
consensus statement from EAS and EFLM
.
Clin Chem
2018
;
64
:
1006
–
1033
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
80

Jialal
I
,
Inn
M
,
Siegel
D
,
Devaraj
S.
Underestimation of low density lipoprotein-cholesterol with the Friedewald
equation versus a direct homogenous low density lipoprotein-cholesterol assay
.
Lab Med
2017
;
48
:
220
–
224
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
81

Martin
SS
,
Blaha
MJ
,
Elshazly
MB
,
Brinton
EA
,
Toth
PP
,
McEvoy
JW
,
Joshi
PH
,
Kulkarni
KR
,
Mize
PD
,
Kwiterovich
PO
,
Defilippis
AP
,
Blumenthal
RS
,
Jones
SR.
Friedewald-estimated versus directly measured low-density lipoprotein
cholesterol and treatment implications
.
J Am Coll Cardiol
2013
;
62
:
732
–
739
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
82

Nauck
M
,
Warnick
GR
,
Rifai
N.
Methods for measurement of LDL-cholesterol: a critical assessment of direct
measurement by homogeneous assays versus calculation
.
Clin Chem
2002
;
48
:
236
–
254
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
83

Razi
F
,
Forouzanfar
K
,
Bandarian
F
,
Nasli-Esfahani
E.
LDL-cholesterol measurement in diabetic type 2 patients: a comparison between
direct assay and popular equations
.
J Diabetes Metab Disord
2017
;
16
:
43
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
84

Robinson
JG
,
Rosenson
RS
,
Farnier
M
,
Chaudhari
U
,
Sasiela
WJ
,
Merlet
L
,
Miller
K
,
Kastelein
JJ.
Safety of very low low-density lipoprotein cholesterol levels with alirocumab:
pooled data from randomized trials
.
J Am Coll Cardiol
2017
;
69
:
471
–
482
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
85

Sathiyakumar
V
,
Park
J
,
Golozar
A
,
Lazo
M
,
Quispe
R
,
Guallar
E
,
Blumenthal
RS
,
Jones
SR
,
Martin
SS.
Fasting versus nonfasting and low-density lipoprotein cholesterol accuracy
.
Circulation
2018
;
137
:
10
–
19
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
86

Whelton
SP
,
Meeusen
JW
,
Donato
LJ
,
Jaffe
AS
,
Saenger
A
,
Sokoll
LJ
,
Blumenthal
RS
,
Jones
SR
,
Martin
SS.
Evaluating the atherogenic burden of individuals with a Friedewald-estimated
low-density lipoprotein cholesterol <70 mg/dL compared with a novel low-density
lipoprotein estimation method
.
J Clin Lipidol
2017
;
11
:
1065
–
1072
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
87

Meeusen
JW
,
Lueke
AJ
,
Jaffe
AS
,
Saenger
AK.
Validation of a proposed novel equation for estimating LDL cholesterol
.
Clin Chem
2014
;
60
:
1519
–
1523
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
88

Langlois
MR
,
Descamps
OS
,
van der Laarse
A
,
Weykamp
C
,
Baum
H
,
Pulkki
K
,
von Eckardstein
A
,
De Bacquer
D
,
Borén
J
,
Wiklund
O
,
Laitinen
P
,
Oosterhuis
WP
,
Cobbaert
C
; EAS-EFLM Collaborative Project.
Clinical impact of direct HDLc and LDLc method bias in hypertriglyceridemia. A
simulation study of the EAS-EFLM Collaborative Project Group
.
Atherosclerosis
2014
;
233
:
83
–
90
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
89

Miida
T
,
Nishimura
K
,
Okamura
T
,
Hirayama
S
,
Ohmura
H
,
Yoshida
H
,
Miyashita
Y
,
Ai
M
,
Tanaka
A
,
Sumino
H
,
Murakami
M
,
Inoue
I
,
Kayamori
Y
,
Nakamura
M
,
Nobori
T
,
Miyazawa
Y
,
Teramoto
T
,
Yokoyama
S.
A multicenter study on the precision and accuracy of homogeneous assays for
LDL-cholesterol: comparison with a beta-quantification method using fresh serum
obtained from non-diseased and diseased subjects
.
Atherosclerosis
2012
;
225
:
208
–
215
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
90

Miller
WG
,
Myers
GL
,
Sakurabayashi
I
,
Bachmann
LM
,
Caudill
SP
,
Dziekonski
A
,
Edwards
S
,
Kimberly
MM
,
Korzun
WJ
,
Leary
ET
,
Nakajima
K
,
Nakamura
M
,
Nilsson
G
,
Shamburek
RD
,
Vetrovec
GW
,
Warnick
GR
,
Remaley
AT.
Seven direct methods for measuring HDL and LDL cholesterol compared with
ultracentrifugation reference measurement procedures
.
Clin Chem
2010
;
56
:
977
–
986
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
91

Marcovina
SM
,
Albers
JJ.
Lipoprotein (a) measurements for clinical application
.
J Lipid Res
2016
;
57
:
526
–
537
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
92

Marcovina
SM
,
Koschinsky
ML
,
Albers
JJ
,
Skarlatos
S.
Report of the National Heart, Lung, and Blood Institute Workshop on
Lipoprotein(a) and Cardiovascular Disease: recent advances and future directions
.
Clin Chem
2003
;
49
:
1785
–
1796
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
93

Tsimikas
S
,
Fazio
S
,
Viney
NJ
,
Xia
S
,
Witztum
JL
,
Marcovina
SM.
Relationship of lipoprotein(a) molar concentrations and mass according to
lipoprotein(a) thresholds and apolipoprotein(a) isoform size
.
J Clin Lipidol
2018
;
12
:
1313
–
1323
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
94

Mora
S
,
Rifai
N
,
Buring
JE
,
Ridker
PM.
Fasting compared with nonfasting lipids and apolipoproteins for predicting
incident cardiovascular events
.
Circulation
2008
;
118
:
993
–
1001
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
95

Jorgensen
AB
,
Frikke-Schmidt
R
,
West
AS
,
Grande
P
,
Nordestgaard
BG
,
Tybjaerg-Hansen
A.
Genetically elevated non-fasting triglycerides and calculated remnant
cholesterol as causal risk factors for myocardial infarction
.
Eur Heart J
2013
;
34
:
1826
–
1833
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
96

Kolovou
GD
,
Mikhailidis
DP
,
Kovar
J
,
Lairon
D
,
Nordestgaard
BG
,
Ooi
TC
,
Perez-Martinez
P
,
Bilianou
H
,
Anagnostopoulou
K
,
Panotopoulos
G.
Assessment and clinical relevance of non-fasting and postprandial triglycerides:
an expert panel statement
.
Curr Vasc Pharmacol
2011
;
9
:
258
–
270
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
97

Mihas
C
,
Kolovou
GD
,
Mikhailidis
DP
,
Kovar
J
,
Lairon
D
,
Nordestgaard
BG
,
Ooi
TC
,
Perez-Martinez
P
,
Bilianou
H
,
Anagnostopoulou
K
,
Panotopoulos
G.
Diagnostic value of postprandial triglyceride testing in healthy subjects: a
meta-analysis
.
Curr Vasc Pharmacol
2011
;
9
:
271
–
280
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
98

Nordestgaard
BG
,
Varbo
A.
Triglycerides and cardiovascular disease
.
Lancet
2014
;
384
:
626
–
635
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
99

Baca
AM
,
Warnick
GR.
Estimation of LDL-associated apolipoprotein B from measurements of triglycerides
and total apolipoprotein B
.
Clin Chem
2008
;
54
:
907
–
910
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
100

Chapman
MJ
,
Ginsberg
HN
,
Amarenco
P
,
Andreotti
F
,
Borén
J
,
Catapano
AL
,
Descamps
OS
,
Fisher
E
,
Kovanen
PT
,
Kuivenhoven
JA
,
Lesnik
P
,
Masana
L
,
Nordestgaard
BG
,
Ray
KK
,
Reiner
Z
,
Taskinen
MR
,
Tokgözoglu
L
,
Tybjærg-Hansen
A
,
Watts
GF
; European Atherosclerosis Society Consensus Panel.
Triglyceride-rich lipoproteins and high-density lipoprotein cholesterol in
patients at high risk of cardiovascular disease: evidence and guidance for
management
.
Eur Heart J
2011
;
32
:
1345
–
1361
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
101

Cartier
LJ
,
Collins
C
,
Lagace
M
,
Douville
P.
Comparison of fasting and non-fasting lipid profiles in a large cohort of
patients presenting at a community hospital
.
Clin Biochem
2018
;
52
:
61
–
66
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
102

National Clinical Guideline Centre (UK).

Lipid Modification: Cardiovascular Risk Assessment and the Modification of Blood
Lipids for the Primary and Secondary Prevention of Cardiovascular Disease
.
London
:
National Institute for Health and Care Excellence (UK
);
2014
.





Google Scholar

PubMed
OpenURL Placeholder Text

Google Preview

WorldCat

COPAC
 
103

Joint British Societies Board.

Joint British Societies' consensus recommendations for the prevention of
cardiovascular disease (JBS3)
.
Heart
2014
;
100
:
ii1
–
ii67
.




Crossref
Search ADS

PubMed

WorldCat

 
104

Doran
B
,
Guo
Y
,
Xu
J
,
Weintraub
H
,
Mora
S
,
Maron
DJ
,
Bangalore
S.
Prognostic value of fasting versus nonfasting low-density lipoprotein
cholesterol levels on long-term mortality: insight from the National Health and
Nutrition Examination Survey III (NHANES-III)
.
Circulation
2014
;
130
:
546
–
553
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
105

Harari
G
,
Green
MS
,
Magid
A
,
Zelber-Sagi
S.
Usefulness of non-high-density lipoprotein cholesterol as a predictor of
cardiovascular disease mortality in men in 22-year follow-up
.
Am J Cardiol
2017
;
119
:
1193
–
1198
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
106

Gu
X
,
Yang
X
,
Li
Y
,
Cao
J
,
Li
J
,
Liu
X
,
Chen
J
,
Shen
C
,
Yu
L
,
Huang
J
,
Gu
D.
Usefulness of low-density lipoprotein cholesterol and non-high-density
lipoprotein cholesterol as predictors of cardiovascular disease in Chinese
.
Am J Cardiol
2015
;
116
:
1063
–
1070
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
107

van den Berg
MJ
,
van der Graaf
Y
,
de Borst
GJ
,
Kappelle
LJ
,
Nathoe
HM
,
Visseren
FLJ
; SMART Study Group.
Low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol,
triglycerides, and apolipoprotein B and cardiovascular risk in patients with
manifest arterial disease
.
Am J Cardiol
2016
;
118
:
804
–
810
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
108

van Deventer
HE
,
Miller
WG
,
Myers
GL
,
Sakurabayashi
I
,
Bachmann
LM
,
Caudill
SP
,
Dziekonski
A
,
Edwards
S
,
Kimberly
MM
,
Korzun
WJ
,
Leary
ET
,
Nakajima
K
,
Nakamura
M
,
Shamburek
RD
,
Vetrovec
GW
,
Warnick
GR
,
Remaley
AT.
Non-HDL cholesterol shows improved accuracy for cardiovascular risk score
classification compared to direct or calculated LDL cholesterol in a
dyslipidemic population
.
Clin Chem
2011
;
57
:
490
–
501
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
109

Sniderman
AD
,
Islam
S
,
Yusuf
S
,
McQueen
MJ.
Discordance analysis of apolipoprotein B and non-high density lipoprotein
cholesterol as markers of cardiovascular risk in the INTERHEART study
.
Atherosclerosis
2012
;
225
:
444
–
449
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
110

Cook
NR
,
Mora
S
,
Ridker
PM.
Lipoprotein(a) and cardiovascular risk prediction among women
.
J Am Coll Cardiol
2018
;
72
:
287
–
296
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
111

Kamstrup
PR
,
Tybjaerg-Hansen
A
,
Nordestgaard
BG.
Extreme lipoprotein(a) levels and improved cardiovascular risk prediction
.
J Am Coll Cardiol
2013
;
61
:
1146
–
1156
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
112

Willeit
P
,
Kiechl
S
,
Kronenberg
F
,
Witztum
JL
,
Santer
P
,
Mayr
M
,
Xu
Q
,
Mayr
A
,
Willeit
J
,
Tsimikas
S.
Discrimination and net reclassification of cardiovascular risk with
lipoprotein(a): prospective 15-year outcomes in the Bruneck Study
.
J Am Coll Cardiol
2014
;
64
:
851
–
860
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
113

European Association for Cardiovascular Prevention & Rehabilitation,

Reiner
Z
,
Catapano
AL
,
De Backer
G
,
Graham
I
,
Taskinen
MR
,
Wiklund
O
,
Agewall
S
,
Alegria
E
,
Chapman
MJ
,
Durrington
P
,
Erdine
S
,
Halcox
J
,
Hobbs
R
,
Kjekshus
J
,
Filardi
PP
,
Riccardi
G
,
Storey
RF
,
Wood
D
;
ESC Committee for Practice Guidelines Committees (CPG) 2008-2010 and 2010-2012
Committees. ESC/EAS Guidelines for the management of dyslipidaemias: the Task
Force for the management of dyslipidaemias of the European Society of Cardiology
(ESC) and the European Atherosclerosis Society (EAS)
.
Eur Heart J
2011
;
32
:
1769
–
1818
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
114

Lloyd-Jones
DM
,
Morris
PB
,
Ballantyne
CM
,
Birtcher
KK
,
Daly
DD
Jr,
DePalma
SM
,
Minissian
MB
,
Orringer
CE
,
Smith
SC
Jr.
2017 Focused Update of the 2016 ACC Expert Consensus Decision Pathway on the
role of non-statin therapies for LDL-cholesterol lowering in the management of
atherosclerotic cardiovascular disease risk:
a report of the American College of Cardiology Task Force on Expert Consensus
Decision Pathways. J Am Coll Cardiol
2017
;
70
:
1785
–
1822
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
115

Navarese
EP
,
Robinson
JG
,
Kowalewski
M
,
Kolodziejczak
M
,
Andreotti
F
,
Bliden
K
,
Tantry
U
,
Kubica
J
,
Raggi
P
,
Gurbel
PA.
Association between baseline LDL-C level and total and cardiovascular mortality
after LDL-C lowering: a systematic review and meta-analysis
.
JAMA
2018
;
319
:
1566
–
1579
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
116

Hsia
J
,
MacFadyen
JG
,
Monyak
J
,
Ridker
PM.
Cardiovascular event reduction and adverse events among subjects attaining
low-density lipoprotein cholesterol <50 mg/dl with rosuvastatin. The JUPITER
trial (Justification for the Use of Statins in Prevention: an Intervention Trial
Evaluating Rosuvastatin)
.
J Am Coll Cardiol
2011
;
57
:
1666
–
1675
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
117

McCormack
T
,
Dent
R
,
Blagden
M.
Very low LDL-C levels may safely provide additional clinical cardiovascular
benefit: the evidence to date
.
Int J Clin Pract
2016
;
70
:
886
–
897
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
118

Williams
B
,
Mancia
G
,
Spiering
W
,
Agabiti Rosei
E
,
Azizi
M
,
Burnier
M
,
Clement
DL
,
Coca
A
,
de Simone
G
,
Dominiczak
A
,
Kahan
T
,
Mahfoud
F
,
Redon
J
,
Ruilope
L
,
Zanchetti
A
,
Kerins
M
,
Kjeldsen
SE
,
Kreutz
R
,
Laurent
S
,
Lip
GYH
,
McManus
R
,
Narkiewicz
K
,
Ruschitzka
F
,
Schmieder
RE
,
Shlyakhto
E
,
Tsioufis
C
,
Aboyans
V
,
Desormais
I
; Authors/Task Force Members.
2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task
Force for the management of arterial hypertension of the European Society of
Cardiology and the European Society of Hypertension: The Task Force for the
management of arterial hypertension of the European Society of Cardiology and
the European Society of Hypertension
.
J Hypertens
2018
;
36
:
1953
–
2041
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
119

Sabatine
MS
,
Giugliano
RP
,
Keech
AC
,
Honarpour
N
,
Wiviott
SD
,
Murphy
SA
,
Kuder
JF
,
Wang
H
,
Liu
T
,
Wasserman
SM
,
Sever
PS
,
Pedersen
TR
; FOURIER Steering Committee and Investigators.
Evolocumab and clinical outcomes in patients with cardiovascular disease
.
N Engl J Med
2017
;
376
:
1713
–
1722
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
120

Schwartz
GG
,
Steg
PG
,
Szarek
M
,
Bhatt
DL
,
Bittner
VA
,
Diaz
R
,
Edelberg
JM
,
Goodman
SG
,
Hanotin
C
,
Harrington
RA
,
Jukema
JW
,
Lecorps
G
,
Mahaffey
KW
,
Moryusef
A
,
Pordy
R
,
Quintero
K
,
Roe
MT
,
Sasiela
WJ
,
Tamby
JF
,
Tricoci
P
,
White
HD
,
Zeiher
AM
; ODYSSEY OUTCOMES Committees and Investigators.
Alirocumab and cardiovascular outcomes after acute coronary syndrome
.
N Engl J Med
2018
;
379
:
2097
–
2107
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
121

Charlton-Menys
V
,
Betteridge
DJ
,
Colhoun
H
,
Fuller
J
,
France
M
,
Hitman
GA
,
Livingstone
SJ
,
Neil
HA
,
Newman
CB
,
Szarek
M
,
DeMicco
DA
,
Durrington
PN.
Targets of statin therapy: LDL cholesterol, non-HDL cholesterol, and
apolipoprotein B in type 2 diabetes in the Collaborative Atorvastatin Diabetes
Study (CARDS)
.
Clin Chem
2009
;
55
:
473
–
480
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
122

Thompson
A
,
Danesh
J.
Associations between apolipoprotein B, apolipoprotein AI, the apolipoprotein
B/AI ratio and coronary heart disease: a literature-based meta-analysis of
prospective studies
.
J Intern Med
2006
;
259
:
481
–
492
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
123

Thanassoulis
G
,
Williams
K
,
Ye
K
,
Brook
R
,
Couture
P
,
Lawler
PR
,
de Graaf
J
,
Furberg
CD
,
Sniderman
A.
Relations of change in plasma levels of LDL-C, non-HDL-C and apoB with risk
reduction from statin therapy: a meta-analysis of randomized trials
.
J Am Heart Assoc
2014
;
3
:
e000759
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
124

Robinson
JG
,
Wang
S
,
Smith
BJ
,
Jacobson
TA.
Meta-analysis of the relationship between non-high-density lipoprotein
cholesterol reduction and coronary heart disease risk
.
J Am Coll Cardiol
2009
;
53
:
316
–
322
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
125

Dalen
JE
,
Devries
S.
Diets to prevent coronary heart disease 1957-2013: what have we learned?
Am J Med
2014
;
127
:
364
–
369
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
126

Eckel
RH
,
Jakicic
JM
,
Ard
JD
,
de Jesus
JM
,
Houston Miller
N
,
Hubbard
VS
,
Lee
IM
,
Lichtenstein
AH
,
Loria
CM
,
Millen
BE
,
Nonas
CA
,
Sacks
FM
,
Smith
SC
Jr,
Svetkey
LP
,
Wadden
TA
,
Yanovski
SZ
,
Kendall
KA
,
Morgan
LC
,
Trisolini
MG
,
Velasco
G
,
Wnek
J
,
Anderson
JL
,
Halperin
JL
,
Albert
NM
,
Bozkurt
B
,
Brindis
RG
,
Curtis
LH
,
DeMets
D
,
Hochman
JS
,
Kovacs
RJ
,
Ohman
EM
,
Pressler
SJ
,
Sellke
FW
,
Shen
WK
,
Smith
SC
Jr,
Tomaselli
GF
; American College of Cardiology/American Heart Association Task Force on
Practice Guidelines.
2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: a
report of the American College of Cardiology/American Heart Association Task
Force on Practice Guidelines
.
Circulation
2014
;
129
:
S76
–
S99
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
127

Mente
A
,
de Koning
L
,
Shannon
HS
,
Anand
SS.
A systematic review of the evidence supporting a causal link between dietary
factors and coronary heart disease
.
Arch Intern Med
2009
;
169
:
659
–
669
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
128

Chowdhury
R
,
Warnakula
S
,
Kunutsor
S
,
Crowe
F
,
Ward
HA
,
Johnson
L
,
Franco
OH
,
Butterworth
AS
,
Forouhi
NG
,
Thompson
SG
,
Khaw
KT
,
Mozaffarian
D
,
Danesh
J
,
Di Angelantonio
E.
Association of dietary, circulating, and supplement fatty acids with coronary
risk: a systematic review and meta-analysis
.
Ann Intern Med
2014
;
160
:
398
–
406
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
129

Mozaffarian
D
,
Micha
R
,
Wallace
S.
Effects on coronary heart disease of increasing polyunsaturated fat in place of
saturated fat: a systematic review and meta-analysis of randomized controlled
trials
.
PLoS Med
2010
;
7
:
e1000252
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
130

Forouhi
NG
,
Krauss
RM
,
Taubes
G
,
Willett
W.
Dietary fat and cardiometabolic health: evidence, controversies, and consensus
for guidance
.
BMJ
2018
;
361
:
k2139
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
131

Mozaffarian
D.
Natural trans fat, dairy fat, partially hydrogenated oils, and cardiometabolic
health: the Ludwigshafen Risk and Cardiovascular Health Study
.
Eur Heart J
2016
;
37
:
1079
–
1081
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
132

Chen
M
,
Li
Y
,
Sun
Q
,
Pan
A
,
Manson
JE
,
Rexrode
KM
,
Willett
WC
,
Rimm
EB
,
Hu
FB.
Dairy fat and risk of cardiovascular disease in 3 cohorts of US adults
.
Am J Clin Nutr
2016
;
104
:
1209
–
1217
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
133

Moore
TJ
,
Vollmer
WM
,
Appel
LJ
,
Sacks
FM
,
Svetkey
LP
,
Vogt
TM
,
Conlin
PR
,
Simons-Morton
DG
,
Carter-Edwards
L
,
Harsha
DW.
Effect of dietary patterns on ambulatory blood pressure : results from the
Dietary Approaches to Stop Hypertension (DASH) Trial. DASH Collaborative
Research Group
.
Hypertension
1999
;
34
:
472
–
477
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
134

Sofi
F
,
Macchi
C
,
Abbate
R
,
Gensini
GF
,
Casini
A.
Mediterranean diet and health status: an updated meta-analysis and a proposal
for a literature-based adherence score
.
Public Health Nutr
2014
;
17
:
2769
–
2782
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
135

Grosso
G
,
Marventano
S
,
Yang
J
,
Micek
A
,
Pajak
A
,
Scalfi
L
,
Galvano
F
,
Kales
SN.
A comprehensive meta-analysis on evidence of Mediterranean diet and
cardiovascular disease: are individual components equal?
Crit Rev Food Sci Nutr
2017
;
57
:
3218
–
3232
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
136

de Lorgeril
M
,
Salen
P
,
Martin
JL
,
Monjaud
I
,
Delaye
J
,
Mamelle
N.
Mediterranean diet, traditional risk factors, and the rate of cardiovascular
complications after myocardial infarction: final report of the Lyon Diet Heart
Study
.
Circulation
1999
;
99
:
779
–
785
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
137

Estruch
R
,
Ros
E
,
Salas-Salvadó
J
,
Covas
MI
,
Corella
D
,
Arós
F
,
Gómez-Gracia
E
,
Ruiz-Gutiérrez
V
,
Fiol
M
,
Lapetra
J
,
Lamuela-Raventos
RM
,
Serra-Majem
L
,
Pintó
X
,
Basora
J
,
Muñoz
MA
,
Sorlí
JV
,
Martínez
JA
,
Martínez-González
MA.
Retraction and republication: primary prevention of cardiovascular disease with
a Mediterranean diet
.
N Engl J Med
2018
;
378
:
2441
–
2442
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
138

Mozaffarian
D
,
Aro
A
,
Willett
WC.
Health effects of trans-fatty acids: experimental and observational evidence
.
Eur J Clin Nutr
2009
;
63
:
S5
–
S21
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
139

Clifton
PM
,
Keogh
JB.
A systematic review of the effect of dietary saturated and polyunsaturated fat
on heart disease
.
Nutr Metab Cardiovasc Dis
2017
;
27
:
1060
–
1080
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
140

Brown
L
,
Rosner
B
,
Willett
WW
,
Sacks
FM.
Cholesterol-lowering effects of dietary fiber: a meta-analysis
.
Am J Clin Nutr
1999
;
69
:
30
–
42
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
141

Hollaender
PL
,
Ross
AB
,
Kristensen
M.
Whole-grain and blood lipid changes in apparently healthy adults: a systematic
review and meta-analysis of randomized controlled studies
.
Am J Clin Nutr
2015
;
102
:
556
–
572
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
142

Gylling
H
,
Plat
J
,
Turley
S
,
Ginsberg
HN
,
Ellegård
L
,
Jessup
W
,
Jones
PJ
,
Lütjohann
D
,
Maerz
W
,
Masana
L
,
Silbernagel
G
,
Staels
B
,
Borén
J
,
Catapano
AL
,
De Backer
G
,
Deanfield
J
,
Descamps
OS
,
Kovanen
PT
,
Riccardi
G
,
Tokgözoglu
L
,
Chapman
MJ
; European Atherosclerosis Society Consensus Panel on Phytosterols.
Plant sterols and plant stanols in the management of dyslipidaemia and
prevention of cardiovascular disease
.
Atherosclerosis
2014
;
232
:
346
–
360
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
143

Musa-Veloso
K
,
Poon
TH
,
Elliot
JA
,
Chung
C.
A comparison of the LDL-cholesterol lowering efficacy of plant stanols and plant
sterols over a continuous dose range: results of a meta-analysis of randomized,
placebo-controlled trials
.
Prostaglandins Leukot Essent Fatty Acids
2011
;
85
:
9
–
28
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
144

Poli
A
,
Barbagallo
CM
,
Cicero
AFG
,
Corsini
A
,
Manzato
E
,
Trimarco
B
,
Bernini
F
,
Visioli
F
,
Bianchi
A
,
Canzone
G
,
Crescini
C
,
de Kreutzenberg
S
,
Ferrara
N
,
Gambacciani
M
,
Ghiselli
A
,
Lubrano
C
,
Marelli
G
,
Marrocco
W
,
Montemurro
V
,
Parretti
D
,
Pedretti
R
,
Perticone
F
,
Stella
R
,
Marangoni
F.
Nutraceuticals and functional foods for the control of plasma cholesterol
levels. An intersociety position paper
.
Pharmacol Res
2018
;
134
:
51
–
60
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
145

Li
Y
,
Jiang
L
,
Jia
Z
,
Xin
W
,
Yang
S
,
Yang
Q
,
Wang
L.
A meta-analysis of red yeast rice: an effective and relatively safe alternative
approach for dyslipidemia
.
PLoS One
2014
;
9
:
e98611
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
146

Lu
Z
,
Kou
W
,
Du
B
,
Wu
Y
,
Zhao
S
,
Brusco
OA
,
Morgan
JM
,
Capuzzi
DM
,
Chinese Coronary
Secondary Prevention Study Group
,
Li
S.
Effect of Xuezhikang, an extract from red yeast Chinese rice, on coronary events
in a Chinese population with previous myocardial infarction
.
Am J Cardiol
2008
;
101
:
1689
–
1693
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
147

Nordmann
AJ
,
Nordmann
A
,
Briel
M
,
Keller
U
,
Yancy
WS
Jr,
Brehm
BJ
,
Bucher
HC.
Effects of low-carbohydrate vs low-fat diets on weight loss and cardiovascular
risk factors: a meta-analysis of randomized controlled trials
.
Arch Intern Med
2006
;
166
:
285
–
293
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
148

Zomer
E
,
Gurusamy
K
,
Leach
R
,
Trimmer
C
,
Lobstein
T
,
Morris
S
,
James
WP
,
Finer
N.
Interventions that cause weight loss and the impact on cardiovascular risk
factors: a systematic review and meta-analysis
.
Obes Rev
2016
;
17
:
1001
–
1011
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
149

Berger
S
,
Raman
G
,
Vishwanathan
R
,
Jacques
PF
,
Johnson
EJ.
Dietary cholesterol and cardiovascular disease: a systematic review and
meta-analysis
.
Am J Clin Nutr
2015
;
102
:
276
–
294
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
150

Griffin
JD
,
Lichtenstein
AH.
Dietary cholesterol and plasma lipoprotein profiles: randomized-controlled
trials
.
Curr Nutr Rep
2013
;
2
:
274
–
282
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
151

Shaw
K
,
Gennat
H
,
O'Rourke
P
,
Del Mar
C.
Exercise for overweight or obesity
.
Cochrane Database Syst Rev
2006
;
4
:
CD003817
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
152

Droste
DW
,
Iliescu
C
,
Vaillant
M
,
Gantenbein
M
,
De Bremaeker
N
,
Lieunard
C
,
Velez
T
,
Meyer
M
,
Guth
T
,
Kuemmerle
A
,
Gilson
G
,
Chioti
A.
A daily glass of red wine associated with lifestyle changes independently
improves blood lipids in patients with carotid arteriosclerosis: results from a
randomized controlled trial
.
Nutr J
2013
;
12
:
147
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
153

Rimm
EB
,
Williams
P
,
Fosher
K
,
Criqui
M
,
Stampfer
MJ.
Moderate alcohol intake and lower risk of coronary heart disease: meta-analysis
of effects on lipids and haemostatic factors
.
BMJ
1999
;
319
:
1523
–
1528
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
154

Yu-Poth
S
,
Zhao
G
,
Etherton
T
,
Naglak
M
,
Jonnalagadda
S
,
Kris-Etherton
PM.
Effects of the National Cholesterol Education Program's Step I and Step II
dietary intervention programs on cardiovascular disease risk factors: a
meta-analysis
.
Am J Clin Nutr
1999
;
69
:
632
–
646
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
155

Santos
FL
,
Esteves
SS
,
da Costa Pereira
A
,
Yancy
WS
Jr,
Nunes
JP.
Systematic review and meta-analysis of clinical trials of the effects of low
carbohydrate diets on cardiovascular risk factors
.
Obes Rev
2012
;
13
:
1048
–
1066
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
156

Rivellese
AA
,
Maffettone
A
,
Vessby
B
,
Uusitupa
M
,
Hermansen
K
,
Berglund
L
,
Louheranta
A
,
Meyer
BJ
,
Riccardi
G.
Effects of dietary saturated, monounsaturated and n-3 fatty acids on fasting
lipoproteins, LDL size and post-prandial lipid metabolism in healthy subjects
.
Atherosclerosis
2003
;
167
:
149
–
158
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
157

Wei
MY
,
Jacobson
TA.
Effects of eicosapentaenoic acid versus docosahexaenoic acid on serum lipids: a
systematic review and meta-analysis
.
Curr Atheroscler Rep
2011
;
13
:
474
–
483
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
158

Kelishadi
R
,
Mansourian
M
,
Heidari-Beni
M.
Association of fructose consumption and components of metabolic syndrome in
human studies: a systematic review and meta-analysis
.
Nutrition
2014
;
30
:
503
–
510
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
159

Stanhope
KL
,
Schwarz
JM
,
Keim
NL
,
Griffen
SC
,
Bremer
AA
,
Graham
JL
,
Hatcher
B
,
Cox
CL
,
Dyachenko
A
,
Zhang
W
,
McGahan
JP
,
Seibert
A
,
Krauss
RM
,
Chiu
S
,
Schaefer
EJ
,
Ai
M
,
Otokozawa
S
,
Nakajima
K
,
Nakano
T
,
Beysen
C
,
Hellerstein
MK
,
Berglund
L
,
Havel
PJ.
Consuming fructose-sweetened, not glucose-sweetened, beverages increases
visceral adiposity and lipids and decreases insulin sensitivity in
overweight/obese humans
.
J Clin Invest
2009
;
119
:
1322
–
1334
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
160

Gayet-Boyer
C
,
Tenenhaus-Aziza
F
,
Prunet
C
,
Marmonier
C
,
Malpuech-Brugere
C
,
Lamarche
B
,
Chardigny
JM.
Is there a linear relationship between the dose of ruminant trans-fatty acids
and cardiovascular risk markers in healthy subjects: results from a systematic
review and meta-regression of randomised clinical trials
.
Br J Nutr
2014
;
112
:
1914
–
1922
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
161

Kelley
GA
,
Kelley
KS.
Impact of progressive resistance training on lipids and lipoproteins in adults:
a meta-analysis of randomized controlled trials
.
Prev Med
2009
;
48
:
9
–
19
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
162

Kastorini
CM
,
Milionis
HJ
,
Esposito
K
,
Giugliano
D
,
Goudevenos
JA
,
Panagiotakos
DB.
The effect of Mediterranean diet on metabolic syndrome and its components: a
meta-analysis of 50 studies and 534,906 individuals
.
J Am Coll Cardiol
2011
;
57
:
1299
–
1313
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
163

Maeda
K
,
Noguchi
Y
,
Fukui
T.
The effects of cessation from cigarette smoking on the lipid and lipoprotein
profiles: a meta-analysis
.
Prev Med
2003
;
37
:
283
–
290
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
164

Mensink
RP
,
Zock
PL
,
Kester
AD
,
Katan
MB.
Effects of dietary fatty acids and carbohydrates on the ratio of serum total to
HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60
controlled trials
.
Am J Clin Nutr
2003
;
77
:
1146
–
1155
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
165

Micha
R
,
Khatibzadeh
S
,
Shi
P
,
Fahimi
S
,
Lim
S
,
Andrews
KG
,
Engell
RE
,
Powles
J
,
Ezzati
M
,
Mozaffarian
D
; Global Burden of Diseases Nutrition and Chronic Diseases Expert Group
NutriCoDE.
Global, regional, and national consumption levels of dietary fats and oils in
1990 and 2010: a systematic analysis including 266 country-specific nutrition
surveys
.
BMJ
2014
;
348
:
g2272
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
166

Schwingshackl
L
,
Bogensberger
B
,
Bencic
A
,
Knuppel
S
,
Boeing
H
,
Hoffmann
G.
Effects of oils and solid fats on blood lipids: a systematic review and network
meta-analysis
.
J Lipid Res
2018
;
59
:
1771
–
1782
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
167

Dattilo
AM
,
Kris-Etherton
PM.
Effects of weight reduction on blood lipids and lipoproteins: a meta-analysis
.
Am J Clin Nutr
1992
;
56
:
320
–
328
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
168

Huffman
KM
,
Hawk
VH
,
Henes
ST
,
Ocampo
CI
,
Orenduff
MC
,
Slentz
CA
,
Johnson
JL
,
Houmard
JA
,
Samsa
GP
,
Kraus
WE
,
Bales
CW.
Exercise effects on lipids in persons with varying dietary patterns-does diet
matter if they exercise? Responses in studies of a targeted risk reduction
intervention through defined exercise I
.
Am Heart J
2012
;
164
:
117
–
124
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
169

Kraus
WE
,
Houmard
JA
,
Duscha
BD
,
Knetzger
KJ
,
Wharton
MB
,
McCartney
JS
,
Bales
CW
,
Henes
S
,
Samsa
GP
,
Otvos
JD
,
Kulkarni
KR
,
Slentz
CA.
Effects of the amount and intensity of exercise on plasma lipoproteins
.
N Engl J Med
2002
;
347
:
1483
–
1492
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
170

Brien
SE
,
Ronksley
PE
,
Turner
BJ
,
Mukamal
KJ
,
Ghali
WA.
Effect of alcohol consumption on biological markers associated with risk of
coronary heart disease: systematic review and meta-analysis of interventional
studies
.
BMJ
2011
;
342
:
d636
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
171

De Natale
C
,
Annuzzi
G
,
Bozzetto
L
,
Mazzarella
R
,
Costabile
G
,
Ciano
O
,
Riccardi
G
,
Rivellese
AA.
Effects of a plant-based high-carbohydrate/high-fiber diet versus
high-monounsaturated fat/low-carbohydrate diet on postprandial lipids in type 2
diabetic patients
.
Diabetes Care
2009
;
32
:
2168
–
2173
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
172

Liu
S
,
Manson
JE
,
Stampfer
MJ
,
Holmes
MD
,
Hu
FB
,
Hankinson
SE
,
Willett
WC.
Dietary glycemic load assessed by food-frequency questionnaire in relation to
plasma high-density-lipoprotein cholesterol and fasting plasma triacylglycerols
in postmenopausal women
.
Am J Clin Nutr
2001
;
73
:
560
–
566
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
173

Stanhope
KL
,
Medici
V
,
Bremer
AA
,
Lee
V
,
Lam
HD
,
Nunez
MV
,
Chen
GX
,
Keim
NL
,
Havel
PJ.
A dose-response study of consuming high-fructose corn syrup-sweetened beverages
on lipid/lipoprotein risk factors for cardiovascular disease in young adults
.
Am J Clin Nutr
2015
;
101
:
1144
–
1154
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
174

Taskinen
MR
,
Soderlund
S
,
Bogl
LH
,
Hakkarainen
A
,
Matikainen
N
,
Pietilainen
KH
,
Rasanen
S
,
Lundbom
N
,
Bjornson
E
,
Eliasson
B
,
Mancina
RM
,
Romeo
S
,
Almeras
N
,
Pepa
GD
,
Vetrani
C
,
Prinster
A
,
Annuzzi
G
,
Rivellese
A
,
Despres
JP
,
Boren
J.
Adverse effects of fructose on cardiometabolic risk factors and hepatic lipid
metabolism in subjects with abdominal obesity
.
J Intern Med
2017
;
282
:
187
–
201
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
175

Look Ahead Research Group,

Wing
RR
,
Bolin
P
,
Brancati
FL
,
Bray
GA
,
Clark
JM
,
Coday
M
,
Crow
RS
,
Curtis
JM
,
Egan
CM
,
Espeland
MA
,
Evans
M
,
Foreyt
JP
,
Ghazarian
S
,
Gregg
EW
,
Harrison
B
,
Hazuda
HP
,
Hill
JO
,
Horton
ES
,
Hubbard
VS
,
Jakicic
JM
,
Jeffery
RW
,
Johnson
KC
,
Kahn
SE
,
Kitabchi
AE
,
Knowler
WC
,
Lewis
CE
,
Maschak-Carey
BJ
,
Montez
MG
,
Murillo
A
,
Nathan
DM
,
Patricio
J
,
Peters
A
,
Pi-Sunyer
X
,
Pownall
H
,
Reboussin
D
,
Regensteiner
JG
,
Rickman
AD
,
Ryan
DH
,
Safford
M
,
Wadden
TA
,
Wagenknecht
LE
,
West
DS
,
Williamson
DF
,
Yanovski
SZ.
Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes
.
N Engl J Med
2013
;
369
:
145
–
154
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
176

Batsis
JA
,
Gill
LE
,
Masutani
RK
,
Adachi-Mejia
AM
,
Blunt
HB
,
Bagley
PJ
,
Lopez-Jimenez
F
,
Bartels
SJ.
Weight loss interventions in older adults with obesity: a systematic review of
randomized controlled trials since 2005
.
J Am Geriatr Soc
2017
;
65
:
257
–
268
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
177

Harris
WS
,
Mozaffarian
D
,
Rimm
E
,
Kris-Etherton
P
,
Rudel
LL
,
Appel
LJ
,
Engler
MM
,
Engler
MB
,
Sacks
F.
Omega-6 fatty acids and risk for cardiovascular disease: a science advisory from
the American Heart Association Nutrition Subcommittee of the Council on
Nutrition, Physical Activity, and Metabolism; Council on Cardiovascular Nursing;
and Council on Epidemiology and Prevention
.
Circulation
2009
;
119
:
902
–
907
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
178

Mozaffarian
D
,
Lemaitre
RN
,
King
IB
,
Song
X
,
Huang
H
,
Sacks
FM
,
Rimm
EB
,
Wang
M
,
Siscovick
DS.
Plasma phospholipid long-chain omega-3 fatty acids and total and cause-specific
mortality in older adults: a cohort study
.
Ann Intern Med
2013
;
158
:
515
–
525
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
179

Riccardi
G
,
Vaccaro
O
,
Costabile
G
,
Rivellese
AA.
How well can we control dyslipidemias through lifestyle modifications?
Curr Cardiol Rep
2016
;
18
:
66
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
180

Seidelmann
SB
,
Claggett
B
,
Cheng
S
,
Henglin
M
,
Shah
A
,
Steffen
LM
,
Folsom
AR
,
Rimm
EB
,
Willett
WC
,
Solomon
SD.
Dietary carbohydrate intake and mortality: a prospective cohort study and
meta-analysis
.
Lancet Public Health
2018
;
3
:
e419
–
e428
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
181

Dehghan
M
,
Mente
A
,
Rangarajan
S
,
Sheridan
P
,
Mohan
V
,
Iqbal
R
,
Gupta
R
,
Lear
S
,
Wentzel-Viljoen
E
,
Avezum
A
,
Lopez-Jaramillo
P
,
Mony
P
,
Varma
RP
,
Kumar
R
,
Chifamba
J
,
Alhabib
KF
,
Mohammadifard
N
,
Oguz
A
,
Lanas
F
,
Rozanska
D
,
Bostrom
KB
,
Yusoff
K
,
Tsolkile
LP
,
Dans
A
,
Yusufali
A
,
Orlandini
A
,
Poirier
P
,
Khatib
R
,
Hu
B
,
Wei
L
,
Yin
L
,
Deeraili
A
,
Yeates
K
,
Yusuf
R
,
Ismail
N
,
Mozaffarian
D
,
Teo
K
,
Anand
SS
,
Yusuf
S
; Prospective Urban Rural Epidemiology study investigators.
Association of dairy intake with cardiovascular disease and mortality in 21
countries from five continents (PURE): a prospective cohort study
.
Lancet
2018
;
392
:
2288
–
2297
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
182

Poli
A
,
Marangoni
F
,
Paoletti
R
,
Mannarino
E
,
Lupattelli
G
,
Notarbartolo
A
,
Aureli
P
,
Bernini
F
,
Cicero
A
,
Gaddi
A
,
Catapano
A
,
Cricelli
C
,
Gattone
M
,
Marrocco
W
,
Porrini
M
,
Stella
R
,
Vanotti
A
,
Volpe
M
,
Volpe
R
,
Cannella
C
,
Pinto
A
,
Del Toma
E
,
La Vecchia
C
,
Tavani
A
,
Manzato
E
,
Riccardi
G
,
Sirtori
C
,
Zambon
A
; Nutrition Foundation of Italy.
Non-pharmacological control of plasma cholesterol levels
.
Nutr Metab Cardiovasc Dis
2008
;
18
:
S1
–
S16
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
183

Global Burden of Disease 2016 Alcohol Collaborators.

Alcohol use and burden for 195 countries and territories, 1990–2016: a
systematic analysis for the Global Burden of Disease Study 2016
.
Lancet
2018
;
392
:
1015
–
1035
.




Crossref
Search ADS

PubMed

WorldCat

 
184

Wood
AM
,
Kaptoge
S
,
Butterworth
AS
,
Willeit
P
,
Warnakula
S
,
Bolton
T
,
Paige
E
,
Paul
DS
,
Sweeting
M
,
Burgess
S
,
Bell
S
,
Astle
W
,
Stevens
D
,
Koulman
A
,
Selmer
RM
,
Verschuren
WMM
,
Sato
S
,
Njolstad
I
,
Woodward
M
,
Salomaa
V
,
Nordestgaard
BG
,
Yeap
BB
,
Fletcher
A
,
Melander
O
,
Kuller
LH
,
Balkau
B
,
Marmot
M
,
Koenig
W
,
Casiglia
E
,
Cooper
C
,
Arndt
V
,
Franco
OH
,
Wennberg
P
,
Gallacher
J
,
de la Camara
AG
,
Volzke
H
,
Dahm
CC
,
Dale
CE
,
Bergmann
MM
,
Crespo
CJ
,
van der Schouw
YT
,
Kaaks
R
,
Simons
LA
,
Lagiou
P
,
Schoufour
JD
,
Boer
JMA
,
Key
TJ
,
Rodriguez
B
,
Moreno-Iribas
C
,
Davidson
KW
,
Taylor
JO
,
Sacerdote
C
,
Wallace
RB
,
Quiros
JR
,
Tumino
R
,
Blazer
DG II
,
Linneberg
A
,
Daimon
M
,
Panico
S
,
Howard
B
,
Skeie
G
,
Strandberg
T
,
Weiderpass
E
,
Nietert
PJ
,
Psaty
BM
,
Kromhout
D
,
Salamanca-Fernandez
E
,
Kiechl
S
,
Krumholz
HM
,
Grioni
S
,
Palli
D
,
Huerta
JM
,
Price
J
,
Sundstrom
J
,
Arriola
L
,
Arima
H
,
Travis
RC
,
Panagiotakos
DB
,
Karakatsani
A
,
Trichopoulou
A
,
Kuhn
T
,
Grobbee
DE
,
Barrett-Connor
E
,
van Schoor
N
,
Boeing
H
,
Overvad
K
,
Kauhanen
J
,
Wareham
N
,
Langenberg
C
,
Forouhi
N
,
Wennberg
M
,
Despres
JP
,
Cushman
M
,
Cooper
JA
,
Rodriguez
CJ
,
Sakurai
M
,
Shaw
JE
,
Knuiman
M
,
Voortman
T
,
Meisinger
C
,
Tjonneland
A
,
Brenner
H
,
Palmieri
L
,
Dallongeville
J
,
Brunner
EJ
,
Assmann
G
,
Trevisan
M
,
Gillum
RF
,
Ford
I
,
Sattar
N
,
Lazo
M
,
Thompson
SG
,
Ferrari
P
,
Leon
DA
,
Smith
GD
,
Peto
R
,
Jackson
R
,
Banks
E
,
Di Angelantonio
E
,
Danesh
J
; Emerging Risk Factors Collaboration/EPIC-CVD/UK Biobank Alcohol Study Group.
Risk thresholds for alcohol consumption: combined analysis of
individual-participant data for 599 912 current drinkers in 83 prospective
studies
.
Lancet
2018
;
391
:
1513
–
1523
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
185

De Backer
GG.
Food supplements with red yeast rice: more regulations are needed
.
Eur J Prev Cardiol
2017
;
24
:
1429
–
1430
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
186

Hartley
L
,
May
MD
,
Loveman
E
,
Colquitt
JL
,
Rees
K.
Dietary fibre for the primary prevention of cardiovascular disease
.
Cochrane Database Syst Rev
2016
;
1
:
CD011472
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
187

Pirro
M
,
Vetrani
C
,
Bianchi
C
,
Mannarino
MR
,
Bernini
F
,
Rivellese
AA.
Joint position statement on "Nutraceuticals for the treatment of
hypercholesterolemia" of the Italian Society of Diabetology (SID) and of the
Italian Society for the Study of Arteriosclerosis (SISA)
.
Nutr Metab Cardiovasc Dis
2017
;
27
:
2
–
17
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
188

Dewell
A
,
Hollenbeck
PL
,
Hollenbeck
CB.
Clinical review: a critical evaluation of the role of soy protein and isoflavone
supplementation in the control of plasma cholesterol concentrations
.
J Clin Endocrinol Metab
2006
;
91
:
772
–
780
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
189

Mas
R
,
Castano
G
,
Illnait
J
,
Fernandez
L
,
Fernandez
J
,
Aleman
C
,
Pontigas
V
,
Lescay
M.
Effects of policosanol in patients with type II hypercholesterolemia and
additional coronary risk factors
.
Clin Pharmacol Ther
1999
;
65
:
439
–
447
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
190

Reiner
Z
,
Tedeschi-Reiner
E
,
Romic
Z.
Effects of rice policosanol on serum lipoproteins, homocysteine, fibrinogen and
C-reactive protein in hypercholesterolaemic patients
.
Clin Drug Investig
2005
;
25
:
701
–
707
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
191

Lan
J
,
Zhao
Y
,
Dong
F
,
Yan
Z
,
Zheng
W
,
Fan
J
,
Sun
G.
Meta-analysis of the effect and safety of berberine in the treatment of type 2
diabetes mellitus, hyperlipemia and hypertension
.
J Ethnopharmacol
2015
;
161
:
69
–
81
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
192

Sacks
FM
,
Lichtenstein
AH
,
Wu
JHY
,
Appel
LJ
,
Creager
MA
,
Kris-Etherton
PM
,
Miller
M
,
Rimm
EB
,
Rudel
LL
,
Robinson
JG
,
Stone
NJ
,
Van Horn
LV
; American Heart Association.
Dietary fats and cardiovascular disease: a presidential advisory from the
American Heart Association
.
Circulation
2017
;
136
:
e1
–
e23
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
193

Jacobson
TA
,
Glickstein
SB
,
Rowe
JD
,
Soni
PN.
Effects of eicosapentaenoic acid and docosahexaenoic acid on low-density
lipoprotein cholesterol and other lipids: a review
.
J Clin Lipidol
2012
;
6
:
5
–
18
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
194

Bhatt
DL
,
Steg
PG
,
Miller
M
,
Brinton
EA
,
Jacobson
TA
,
Ketchum
SB
,
Doyle
RT
Jr,
Juliano
RA
,
Jiao
L
,
Granowitz
C
,
Tardif
JC
,
Ballantyne
CM
; REDUCE-IT Investigators.
Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia
.
N Engl J Med
2019
;
380
:
11
–
22
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
195

Chasman
DI
,
Giulianini
F
,
MacFadyen
J
,
Barratt
BJ
,
Nyberg
F
,
Ridker
PM.
Genetic determinants of statin-induced low-density lipoprotein cholesterol
reduction: the Justification for the Use of Statins in Prevention: an
Intervention Trial Evaluating Rosuvastatin (JUPITER) trial
.
Circ Cardiovasc Genet
2012
;
5
:
257
–
264
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
196

Reiner
Z.
Resistance and intolerance to statins
.
Nutr Metab Cardiovasc Dis
2014
;
24
:
1057
–
1066
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
197

Moriarty
PM
,
Thompson
PD
,
Cannon
CP
,
Guyton
JR
,
Bergeron
J
,
Zieve
FJ
,
Bruckert
E
,
Jacobson
TA
,
Kopecky
SL
,
Baccara-Dinet
MT
,
Du
Y
,
Pordy
R
,
Gipe
DA
,
ODYSSEY ALTERNATIVE
Investigators.
Efficacy and safety of alirocumab vs ezetimibe in statin-intolerant patients,
with a statin rechallenge arm: The ODYSSEY ALTERNATIVE randomized trial
.
J Clin Lipidol
2015
;
9
:
758
–
769
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
198

Stroes
E
,
Colquhoun
D
,
Sullivan
D
,
Civeira
F
,
Rosenson
RS
,
Watts
GF
,
Bruckert
E
,
Cho
L
,
Dent
R
,
Knusel
B
,
Xue
A
,
Scott
R
,
Wasserman
SM
,
Rocco
M
; GAUSS-2 Investigators.
Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin
intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial
of evolocumab
.
J Am Coll Cardiol
2014
;
63
:
2541
–
2548
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
199

Reiner
Z.
Managing the residual cardiovascular disease risk associated with
HDL-cholesterol and triglycerides in statin-treated patients: a clinical update
.
Nutr Metab Cardiovasc Dis
2013
;
23
:
799
–
807
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
200

Sharma
A
,
Joshi
PH
,
Rinehart
S
,
Thakker
KM
,
Lele
A
,
Voros
S.
Baseline very low-density lipoprotein cholesterol is associated with the
magnitude of triglyceride lowering on statins, fenofibric acid, or their
combination in patients with mixed dyslipidemia
.
J Cardiovasc Transl Res
2014
;
7
:
465
–
474
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
201

Barter
PJ
,
Brandrup-Wognsen
G
,
Palmer
MK
,
Nicholls
SJ.
Effect of statins on HDL-C: a complex process unrelated to changes in LDL-C:
analysis of the VOYAGER Database
.
J Lipid Res
2010
;
51
:
1546
–
1553
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
202

Tsimikas
S
,
Witztum
JL
,
Miller
ER
,
Sasiela
WJ
,
Szarek
M
,
Olsson
AG
,
Schwartz
GG
; Myocardial Ischemia Reduction with Aggressive Cholesterol Lowering (MIRACL)
Study Investigators.
High-dose atorvastatin reduces total plasma levels of oxidized phospholipids and
immune complexes present on apolipoprotein B-100 in patients with acute coronary
syndromes in the MIRACL trial
.
Circulation
2004
;
110
:
1406
–
1412
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
203

Khera
AV
,
Everett
BM
,
Caulfield
MP
,
Hantash
FM
,
Wohlgemuth
J
,
Ridker
PM
,
Mora
S.
Lipoprotein(a) concentrations, rosuvastatin therapy, and residual vascular risk:
an analysis from the JUPITER Trial (Justification for the Use of Statins in
Prevention: an Intervention Trial Evaluating Rosuvastatin)
.
Circulation
2014
;
129
:
635
–
642
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
204

Davignon
J.
Beneficial cardiovascular pleiotropic effects of statins
.
Circulation
2004
;
109
:
III39
–
III43
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
205

Oesterle
A
,
Laufs
U
,
Liao
JK.
Pleiotropic effects of statins on the cardiovascular system
.
Circ Res
2017
;
120
:
229
–
243
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
206

Pedersen
TR.
Pleiotropic effects of statins: evidence against benefits beyond LDL-cholesterol
lowering
.
Am J Cardiovasc Drugs
2010
;
10
:
10
–
17
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
207

Genser
B
,
Marz
W.
Low density lipoprotein cholesterol, statins and cardiovascular events: a
meta-analysis
.
Clin Res Cardiol
2006
;
95
:
393
–
404
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
208

Gould
AL
,
Rossouw
JE
,
Santanello
NC
,
Heyse
JF
,
Furberg
CD.
Cholesterol reduction yields clinical benefit. A new look at old data
.
Circulation
1995
;
91
:
2274
–
2282
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
209

Gould
AL
,
Rossouw
JE
,
Santanello
NC
,
Heyse
JF
,
Furberg
CD.
Cholesterol reduction yields clinical benefit: impact of statin trials
.
Circulation
1998
;
97
:
946
–
952
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
210

LaRosa
JC
,
He
J
,
Vupputuri
S.
Effect of statins on risk of coronary disease: a meta-analysis of randomized
controlled trials
.
JAMA
1999
;
282
:
2340
–
2346
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
211

Mills
EJ
,
Wu
P
,
Chong
G
,
Ghement
I
,
Singh
S
,
Akl
EA
,
Eyawo
O
,
Guyatt
G
,
Berwanger
O
,
Briel
M.
Efficacy and safety of statin treatment for cardiovascular disease: a network
meta-analysis of 170,255 patients from 76 randomized trials
.
QJM
2011
;
104
:
109
–
124
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
212

Ray
KK
,
Seshasai
SR
,
Erqou
S
,
Sever
P
,
Jukema
JW
,
Ford
I
,
Sattar
N.
Statins and all-cause mortality in high-risk primary prevention: a meta-analysis
of 11 randomized controlled trials involving 65,229 participants
.
Arch Intern Med
2010
;
170
:
1024
–
1031
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
213

Taylor
F
,
Huffman
MD
,
Macedo
AF
,
Moore
TH
,
Burke
M
,
Davey Smith
G
,
Ward
K
,
Ebrahim
S.
Statins for the primary prevention of cardiovascular disease
.
Cochrane Database Syst Rev
2013
;
1
:
CD004816
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
214

Cholesterol Treatment Trialists Collaboration,

Herrington
WG
,
Emberson
J
,
Mihaylova
B
,
Blackwell
L
,
Reith
C
,
Solbu
MD
,
Mark
PB
,
Fellstrom
B
,
Jardine
AG
,
Wanner
C
,
Holdaas
H
,
Fulcher
J
,
Haynes
R
,
Landray
MJ
,
Keech
A
,
Simes
J
,
Collins
R
,
Baigent
C.
Impact of renal function on the effects of LDL cholesterol lowering with
statin-based regimens: a meta-analysis of individual participant data from 28
randomised trials
.
Lancet Diabetes Endocrinol
2016
;
4
:
829
–
839
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
215

Naci
H
,
Brugts
JJ
,
Fleurence
R
,
Tsoi
B
,
Toor
H
,
Ades
AE.
Comparative benefits of statins in the primary and secondary prevention of major
coronary events and all-cause mortality: a network meta-analysis of
placebo-controlled and active-comparator trials
.
Eur J Prev Cardiol
2013
;
20
:
641
–
657
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
216

Ford
I
,
Murray
H
,
McCowan
C
,
Packard
CJ.
Long-term safety and efficacy of lowering low-density lipoprotein cholesterol
with statin therapy: 20-year follow-up of West of Scotland Coronary Prevention
Study
.
Circulation
2016
;
133
:
1073
–
1080
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
217

Cholesterol Treatment Trialists C.

Efficacy and safety of statin therapy in older people: a meta-analysis of
individual participant data from 28 randomised controlled trials
.
Lancet
2019
;
393
:
407
–
415
.




Crossref
Search ADS

PubMed

WorldCat

 
218

Rogers
JK
,
Jhund
PS
,
Perez
AC
,
Bohm
M
,
Cleland
JG
,
Gullestad
L
,
Kjekshus
J
,
van Veldhuisen
DJ
,
Wikstrand
J
,
Wedel
H
,
McMurray
JJ
,
Pocock
SJ.
Effect of rosuvastatin on repeat heart failure hospitalizations: the CORONA
Trial (Controlled Rosuvastatin Multinational Trial in Heart Failure)
.
JACC Heart Fail
2014
;
2
:
289
–
297
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
219

Tavazzi
L
,
Maggioni
AP
,
Marchioli
R
,
Barlera
S
,
Franzosi
MG
,
Latini
R
,
Lucci
D
,
Nicolosi
GL
,
Porcu
M
,
Tognoni
G
; Gissi-HF Investigator.
Effect of rosuvastatin in patients with chronic heart failure (the GISSI-HF
trial): a randomised, double-blind, placebo-controlled trial
.
Lancet
2008
;
372
:
1231
–
1239
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
220

Wanner
C
,
Krane
V
,
Marz
W
,
Olschewski
M
,
Mann
JF
,
Ruf
G
,
Ritz
E
; German Diabetes and Dialysis Study Investigators.
Atorvastatin in patients with type 2 diabetes mellitus undergoing hemodialysis
.
N Engl J Med
2005
;
353
:
238
–
248
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
221

Fellström
BC
,
Jardine
AG
,
Schmieder
RE
,
Holdaas
H
,
Bannister
K
,
Beutler
J
,
Chae
DW
,
Chevaile
A
,
Cobbe
SM
,
Gronhagen-Riska
C
,
De Lima
JJ
,
Lins
R
,
Mayer
G
,
McMahon
AW
,
Parving
HH
,
Remuzzi
G
,
Samuelsson
O
,
Sonkodi
S
,
Sci
D
,
Süleymanlar
G
,
Tsakiris
D
,
Tesar
V
,
Todorov
V
,
Wiecek
A
,
Wüthrich
RP
,
Gottlow
M
,
Johnsson
E
,
Zannad
F
; AURORA Study Group.
Rosuvastatin and cardiovascular events in patients undergoing hemodialysis
.
N Engl J Med
2009
;
360
:
1395
–
1407
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
222

Baigent
C
,
Landray
MJ
,
Reith
C
,
Emberson
J
,
Wheeler
DC
,
Tomson
C
,
Wanner
C
,
Krane
V
,
Cass
A
,
Craig
J
,
Neal
B
,
Jiang
L
,
Hooi
LS
,
Levin
A
,
Agodoa
L
,
Gaziano
M
,
Kasiske
B
,
Walker
R
,
Massy
ZA
,
Feldt-Rasmussen
B
,
Krairittichai
U
,
Ophascharoensuk
V
,
Fellstrom
B
,
Holdaas
H
,
Tesar
V
,
Wiecek
A
,
Grobbee
D
,
de Zeeuw
D
,
Gronhagen-Riska
C
,
Dasgupta
T
,
Lewis
D
,
Herrington
W
,
Mafham
M
,
Majoni
W
,
Wallendszus
K
,
Grimm
R
,
Pedersen
T
,
Tobert
J
,
Armitage
J
,
Baxter
A
,
Bray
C
,
Chen
Y
,
Chen
Z
,
Hill
M
,
Knott
C
,
Parish
S
,
Simpson
D
,
Sleight
P
,
Young
A
,
Collins
R
; SHARP Investigators.
The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in
patients with chronic kidney disease (Study of Heart and Renal Protection): a
randomised placebo-controlled trial
.
Lancet
2011
;
377
:
2181
–
2192
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
223

Cholesterol Treatment Trialists Collaboration,

Emberson
JR
,
Kearney
PM
,
Blackwell
L
,
Newman
C
,
Reith
C
,
Bhala
N
,
Holland
L
,
Peto
R
,
Keech
A
,
Collins
R
,
Simes
J
,
Baigent
C.
Lack of effect of lowering LDL cholesterol on cancer: meta-analysis of
individual data from 175,000 people in 27 randomised trials of statin therapy
.
PLoS One
2012
;
7
:
e29849
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
224

McGuinness
B
,
Craig
D
,
Bullock
R
,
Malouf
R
,
Passmore
P.
Statins for the treatment of dementia
.
Cochrane Database Syst Rev
2014
;
7
:
CD007514
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
225

Eslami
L
,
Merat
S
,
Malekzadeh
R
,
Nasseri-Moghaddam
S
,
Aramin
H.
Statins for non-alcoholic fatty liver disease and non-alcoholic steatohepatitis
.
Cochrane Database Syst Rev
2013
;
12
:
CD008623
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
226

Rahimi
K
,
Bhala
N
,
Kamphuisen
P
,
Emberson
J
,
Biere-Rafi
S
,
Krane
V
,
Robertson
M
,
Wikstrand
J
,
McMurray
J.
Effect of statins on venous thromboembolic events: a meta-analysis of published
and unpublished evidence from randomised controlled trials
.
PLoS Med
2012
;
9
:
e1001310
. doi: 10.1371/journal.pmed.1001310. Epub 18 September 2012.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
227

Rahimi
K
,
Emberson
J
,
McGale
P
,
Majoni
W
,
Merhi
A
,
Asselbergs
FW
,
Krane
V
,
Macfarlane
PW
; PROSPER Executive.
Effect of statins on atrial fibrillation: collaborative meta-analysis of
published and unpublished evidence from randomised controlled trials
.
BMJ
2011
;
342
:
d1250
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
228

Zheng
Z
,
Jayaram
R
,
Jiang
L
,
Emberson
J
,
Zhao
Y
,
Li
Q
,
Du
J
,
Guarguagli
S
,
Hill
M
,
Chen
Z
,
Collins
R
,
Casadei
B.
Perioperative rosuvastatin in cardiac surgery
.
N Engl J Med
2016
;
374
:
1744
–
1753
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
229

Raval
AD
,
Hunter
T
,
Stuckey
B
,
Hart
RJ.
Statins for women with polycystic ovary syndrome not actively trying to conceive
.
Cochrane Database Syst Rev
2011
;
10
:
CD008565
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
230

McGuinness
B
,
Craig
D
,
Bullock
R
,
Passmore
P.
Statins for the prevention of dementia
.
Cochrane Database Syst Rev
2016
;
1
:
CD003160
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
231

Giugliano
RP
,
Mach
F
,
Zavitz
K
,
Kurtz
C
,
Im
K
,
Kanevsky
E
,
Schneider
J
,
Wang
H
,
Keech
A
,
Pedersen
TR
,
Sabatine
MS
,
Sever
PS
,
Robinson
JG
,
Honarpour
N
,
Wasserman
SM
,
Ott
BR
; EBBINGHAUS Investigators.
Cognitive function in a randomized trial of evolocumab
.
N Engl J Med
2017
;
377
:
633
–
643
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
232

Mach
F
,
Ray
KK
,
Wiklund
O
,
Corsini
A
,
Catapano
AL
,
Bruckert
E
,
De Backer
G
,
Hegele
RA
,
Hovingh
GK
,
Jacobson
TA
,
Krauss
RM
,
Laufs
U
,
Leiter
LA
,
Marz
W
,
Nordestgaard
BG
,
Raal
FJ
,
Roden
M
,
Santos
RD
,
Stein
EA
,
Stroes
ES
,
Thompson
PD
,
Tokgozoglu
L
,
Vladutiu
GD
,
Gencer
B
,
Stock
JK
,
Ginsberg
HN
,
Chapman
MJ
; European Atherosclerosis Society Consensus Panel.
Adverse effects of statin therapy: perception vs. the evidence - focus on
glucose homeostasis, cognitive, renal and hepatic function, haemorrhagic stroke
and cataract
.
Eur Heart J
2018
;
39
:
2526
–
2539
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
233

Collins
R
,
Reith
C
,
Emberson
J
,
Armitage
J
,
Baigent
C
,
Blackwell
L
,
Blumenthal
R
,
Danesh
J
,
Smith
GD
,
DeMets
D
,
Evans
S
,
Law
M
,
MacMahon
S
,
Martin
S
,
Neal
B
,
Poulter
N
,
Preiss
D
,
Ridker
P
,
Roberts
I
,
Rodgers
A
,
Sandercock
P
,
Schulz
K
,
Sever
P
,
Simes
J
,
Smeeth
L
,
Wald
N
,
Yusuf
S
,
Peto
R.
Interpretation of the evidence for the efficacy and safety of statin therapy
.
Lancet
2016
;
388
:
2532
–
2561
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
234

Stroes
ES
,
Thompson
PD
,
Corsini
A
,
Vladutiu
GD
,
Raal
FJ
,
Ray
KK
,
Roden
M
,
Stein
E
,
Tokgozoglu
L
,
Nordestgaard
BG
,
Bruckert
E
,
De Backer
G
,
Krauss
RM
,
Laufs
U
,
Santos
RD
,
Hegele
RA
,
Hovingh
GK
,
Leiter
LA
,
Mach
F
,
Marz
W
,
Newman
CB
,
Wiklund
O
,
Jacobson
TA
,
Catapano
AL
,
Chapman
MJ
,
Ginsberg
HN
; European Atherosclerosis Society Consensus Panel.
Statin-associated muscle symptoms: impact on statin therapy-European
Atherosclerosis Society Consensus Panel Statement on Assessment, Aetiology and
Management
.
Eur Heart J
2015
;
36
:
1012
–
1022
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
235

Law
M
,
Rudnicka
AR.
Statin safety: a systematic review
.
Am J Cardiol
2006
;
97
:
52C
–
60C
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
236

Bruckert
E
,
Hayem
G
,
Dejager
S
,
Yau
C
,
Begaud
B.
Mild to moderate muscular symptoms with high-dosage statin therapy in
hyperlipidemic patients--the PRIMO study
.
Cardiovasc Drugs Ther
2005
;
19
:
403
–
414
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
237

Davidson
MH
,
Clark
JA
,
Glass
LM
,
Kanumalla
A.
Statin safety: an appraisal from the adverse event reporting system
.
Am J Cardiol
2006
;
97
:
32C
–
43C
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
238

Gupta
A
,
Thompson
D
,
Whitehouse
A
,
Collier
T
,
Dahlof
B
,
Poulter
N
,
Collins
R
,
Sever
P
;
ASCOT Investigators. Adverse events associated with unblinded, but not with
blinded, statin therapy in the Anglo-Scandinavian Cardiac Outcomes
Trial-Lipid-Lowering Arm (ASCOT-LLA): a randomised double-blind
placebo-controlled trial and its non-randomised non-blind extension phase
.
Lancet
2017
;
389
:
2473
–
2481
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
239

Finegold
JA
,
Manisty
CH
,
Goldacre
B
,
Barron
AJ
,
Francis
DP.
What proportion of symptomatic side effects in patients taking statins are
genuinely caused by the drug? Systematic review of randomized placebo-controlled
trials to aid individual patient choice
.
Eur J Prev Cardiol
2014
;
21
:
464
–
474
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
240

Naci
H
,
Brugts
J
,
Ades
T.
Comparative tolerability and harms of individual statins: a study-level network
meta-analysis of 246 955 participants from 135 randomized, controlled trials
.
Circ Cardiovasc Qual Outcomes
2013
;
6
:
390
–
399
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
241

Moriarty
PM
,
Jacobson
TA
,
Bruckert
E
,
Thompson
PD
,
Guyton
JR
,
Baccara-Dinet
MT
,
Gipe
D.
Efficacy and safety of alirocumab, a monoclonal antibody to PCSK9, in
statin-intolerant patients: design and rationale of ODYSSEY ALTERNATIVE, a
randomized phase 3 trial
.
J Clin Lipidol
2014
;
8
:
554
–
561
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
242

Keating
AJ
,
Campbell
KB
,
Guyton
JR.
Intermittent nondaily dosing strategies in patients with previous statin-induced
myopathy
.
Ann Pharmacother
2013
;
47
:
398
–
404
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
243

Marcum
ZA
,
Vande Griend
JP
,
Linnebur
SA.
FDA drug safety communications: a narrative review and clinical considerations
for older adults
.
Am J Geriatr Pharmacother
2012
;
10
:
264
–
271
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
244

Chalasani
N
,
Aljadhey
H
,
Kesterson
J
,
Murray
MD
,
Hall
SD.
Patients with elevated liver enzymes are not at higher risk for statin
hepatotoxicity
.
Gastroenterology
2004
;
126
:
1287
–
1292
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
245

Dongiovanni
P
,
Petta
S
,
Mannisto
V
,
Mancina
RM
,
Pipitone
R
,
Karja
V
,
Maggioni
M
,
Kakela
P
,
Wiklund
O
,
Mozzi
E
,
Grimaudo
S
,
Kaminska
D
,
Rametta
R
,
Craxi
A
,
Fargion
S
,
Nobili
V
,
Romeo
S
,
Pihlajamaki
J
,
Valenti
L.
Statin use and non-alcoholic steatohepatitis in at risk individuals
.
J Hepatol
2015
;
63
:
705
–
712
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
246

Vuppalanchi
R
,
Teal
E
,
Chalasani
N.
Patients with elevated baseline liver enzymes do not have higher frequency of
hepatotoxicity from lovastatin than those with normal baseline liver enzymes
.
Am J Med Sci
2005
;
329
:
62
–
65
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
247

Sattar
N
,
Preiss
D
,
Murray
HM
,
Welsh
P
,
Buckley
BM
,
de Craen
AJ
,
Seshasai
SR
,
McMurray
JJ
,
Freeman
DJ
,
Jukema
JW
,
Macfarlane
PW
,
Packard
CJ
,
Stott
DJ
,
Westendorp
RG
,
Shepherd
J
,
Davis
BR
,
Pressel
SL
,
Marchioli
R
,
Marfisi
RM
,
Maggioni
AP
,
Tavazzi
L
,
Tognoni
G
,
Kjekshus
J
,
Pedersen
TR
,
Cook
TJ
,
Gotto
AM
,
Clearfield
MB
,
Downs
JR
,
Nakamura
H
,
Ohashi
Y
,
Mizuno
K
,
Ray
KK
,
Ford
I.
Statins and risk of incident diabetes: a collaborative meta-analysis of
randomised statin trials
.
Lancet
2010
;
375
:
735
–
742
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
248

Preiss
D
,
Seshasai
SR
,
Welsh
P
,
Murphy
SA
,
Ho
JE
,
Waters
DD
,
DeMicco
DA
,
Barter
P
,
Cannon
CP
,
Sabatine
MS
,
Braunwald
E
,
Kastelein
JJ
,
de Lemos
JA
,
Blazing
MA
,
Pedersen
TR
,
Tikkanen
MJ
,
Sattar
N
,
Ray
KK.
Risk of incident diabetes with intensive-dose compared with moderate-dose statin
therapy: a meta-analysis
.
JAMA
2011
;
305
:
2556
–
2564
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
249

Waters
DD
,
Ho
JE
,
Boekholdt
SM
,
DeMicco
DA
,
Kastelein
JJ
,
Messig
M
,
Breazna
A
,
Pedersen
TR.
Cardiovascular event reduction versus new-onset diabetes during atorvastatin
therapy: effect of baseline risk factors for diabetes
.
J Am Coll Cardiol
2013
;
61
:
148
–
152
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
250

Swerdlow
DI
,
Preiss
D
,
Kuchenbaecker
KB
,
Holmes
MV
,
Engmann
JE
,
Shah
T
,
Sofat
R
,
Stender
S
,
Johnson
PC
,
Scott
RA
,
Leusink
M
,
Verweij
N
,
Sharp
SJ
,
Guo
Y
,
Giambartolomei
C
,
Chung
C
,
Peasey
A
,
Amuzu
A
,
Li
K
,
Palmen
J
,
Howard
P
,
Cooper
JA
,
Drenos
F
,
Li
YR
,
Lowe
G
,
Gallacher
J
,
Stewart
MC
,
Tzoulaki
I
,
Buxbaum
SG
,
van der
AD
,
Forouhi
NG
,
Onland-Moret
NC
,
van der Schouw
YT
,
Schnabel
RB
,
Hubacek
JA
,
Kubinova
R
,
Baceviciene
M
,
Tamosiunas
A
,
Pajak
A
,
Topor-Madry
R
,
Stepaniak
U
,
Malyutina
S
,
Baldassarre
D
,
Sennblad
B
,
Tremoli
E
,
de Faire
U
,
Veglia
F
,
Ford
I
,
Jukema
JW
,
Westendorp
RG
,
de Borst
GJ
,
de Jong
PA
,
Algra
A
,
Spiering
W
,
Maitland-van der Zee
AH
,
Klungel
OH
,
de Boer
A
,
Doevendans
PA
,
Eaton
CB
,
Robinson
JG
,
Duggan
D
,
Consortium
D
,
Consortium
M
,
InterAct
C
,
Kjekshus
J
,
Downs
JR
,
Gotto
AM
,
Keech
AC
,
Marchioli
R
,
Tognoni
G
,
Sever
PS
,
Poulter
NR
,
Waters
DD
,
Pedersen
TR
,
Amarenco
P
,
Nakamura
H
,
McMurray
JJ
,
Lewsey
JD
,
Chasman
DI
,
Ridker
PM
,
Maggioni
AP
,
Tavazzi
L
,
Ray
KK
,
Seshasai
SR
,
Manson
JE
,
Price
JF
,
Whincup
PH
,
Morris
RW
,
Lawlor
DA
,
Smith
GD
,
Ben-Shlomo
Y
,
Schreiner
PJ
,
Fornage
M
,
Siscovick
DS
,
Cushman
M
,
Kumari
M
,
Wareham
NJ
,
Verschuren
WM
,
Redline
S
,
Patel
SR
,
Whittaker
JC
,
Hamsten
A
,
Delaney
JA
,
Dale
C
,
Gaunt
TR
,
Wong
A
,
Kuh
D
,
Hardy
R
,
Kathiresan
S
,
Castillo
BA
,
van der Harst
P
,
Brunner
EJ
,
Tybjaerg-Hansen
A
,
Marmot
MG
,
Krauss
RM
,
Tsai
M
,
Coresh
J
,
Hoogeveen
RC
,
Psaty
BM
,
Lange
LA
,
Hakonarson
H
,
Dudbridge
F
,
Humphries
SE
,
Talmud
PJ
,
Kivimaki
M
,
Timpson
NJ
,
Langenberg
C
,
Asselbergs
FW
,
Voevoda
M
,
Bobak
M
,
Pikhart
H
,
Wilson
JG
,
Reiner
AP
,
Keating
BJ
,
Hingorani
AD
,
Sattar
N.
HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence
from genetic analysis and randomised trials
.
Lancet
2015
;
385
:
351
–
361
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
251

McKinney
JS
,
Kostis
WJ.
Statin therapy and the risk of intracerebral hemorrhage: a meta-analysis of 31
randomized controlled trials
.
Stroke
2012
;
43
:
2149
–
2156
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
252

Hackam
DG
,
Woodward
M
,
Newby
LK
,
Bhatt
DL
,
Shao
M
,
Smith
EE
,
Donner
A
,
Mamdani
M
,
Douketis
JD
,
Arima
H
,
Chalmers
J
,
MacMahon
S
,
Tirschwell
DL
,
Psaty
BM
,
Bushnell
CD
,
Aguilar
MI
,
Capampangan
DJ
,
Werring
DJ
,
De Rango
P
,
Viswanathan
A
,
Danchin
N
,
Cheng
CL
,
Yang
YH
,
Verdel
BM
,
Lai
MS
,
Kennedy
J
,
Uchiyama
S
,
Yamaguchi
T
,
Ikeda
Y
,
Mrkobrada
M.
Statins and intracerebral hemorrhage: collaborative systematic review and
meta-analysis
.
Circulation
2011
;
124
:
2233
–
2242
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
253

Palmer
SC
,
Navaneethan
SD
,
Craig
JC
,
Perkovic
V
,
Johnson
DW
,
Nigwekar
SU
,
Hegbrant
J
,
Strippoli
GF.
HMG CoA reductase inhibitors (statins) for kidney transplant recipients
.
Cochrane Database Syst Rev
2014
;
1
:
CD005019
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
254

Agarwal
R.
Effects of statins on renal function
.
Am J Cardiol
2006
;
97
:
748
–
755
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
255

Sidaway
JE
,
Davidson
RG
,
McTaggart
F
,
Orton
TC
,
Scott
RC
,
Smith
GJ
,
Brunskill
NJ.
Inhibitors of 3-hydroxy-3-methylglutaryl-CoA reductase reduce receptor-mediated
endocytosis in opossum kidney cells
.
J Am Soc Nephrol
2004
;
15
:
2258
–
2265
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
256

Davidson
MH.
Rosuvastatin safety: lessons from the FDA review and post-approval surveillance
.
Expert Opin Drug Saf
2004
;
3
:
547
–
557
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
257

Egan
A
,
Colman
E.
Weighing the benefits of high-dose simvastatin against the risk of myopathy
.
N Engl J Med
2011
;
365
:
285
–
287
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
258

Wiklund
O
,
Pirazzi
C
,
Romeo
S.
Monitoring of lipids, enzymes, and creatine kinase in patients on lipid-lowering
drug therapy
.
Curr Cardiol Rep
2013
;
15
:
397
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
259

Franssen
R
,
Vergeer
M
,
Stroes
ES
,
Kastelein
JJ.
Combination statin-fibrate therapy: safety aspects
.
Diabetes Obes Metab
2009
;
11
:
89
–
94
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
260

Holoshitz
N
,
Alsheikh-Ali
AA
,
Karas
RH.
Relative safety of gemfibrozil and fenofibrate in the absence of concomitant
cerivastatin use
.
Am J Cardiol
2008
;
101
:
95
–
97
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
261

Phan
BA
,
Dayspring
TD
,
Toth
PP.
Ezetimibe therapy: mechanism of action and clinical update
.
Vasc Health Risk Manag
2012
;
8
:
415
–
427
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
262

Pandor
A
,
Ara
RM
,
Tumur
I
,
Wilkinson
AJ
,
Paisley
S
,
Duenas
A
,
Durrington
PN
,
Chilcott
J.
Ezetimibe monotherapy for cholesterol lowering in 2,722 people: systematic
review and meta-analysis of randomized controlled trials
.
J Intern Med
2009
;
265
:
568
–
580
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
263

Morrone
D
,
Weintraub
WS
,
Toth
PP
,
Hanson
ME
,
Lowe
RS
,
Lin
J
,
Shah
AK
,
Tershakovec
AM.
Lipid-altering efficacy of ezetimibe plus statin and statin monotherapy and
identification of factors associated with treatment response: a pooled analysis
of over 21,000 subjects from 27 clinical trials
.
Atherosclerosis
2012
;
223
:
251
–
261
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
264

Jones
MR
,
Nwose
OM.
Role of colesevelam in combination lipid-lowering therapy
.
Am J Cardiovasc Drugs
2013
;
13
:
315
–
323
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
265

Nissen
SE
,
Stroes
E
,
Dent-Acosta
RE
,
Rosenson
RS
,
Lehman
SJ
,
Sattar
N
,
Preiss
D
,
Bruckert
E
,
Ceska
R
,
Lepor
N
,
Ballantyne
CM
,
Gouni-Berthold
I
,
Elliott
M
,
Brennan
DM
,
Wasserman
SM
,
Somaratne
R
,
Scott
R
,
Stein
EA
; Gauss-3 Investigators.
Efficacy and tolerability of evolocumab vs ezetimibe in patients with
muscle-related statin intolerance: the GAUSS-3 randomized clinical trial
.
JAMA
2016
;
315
:
1580
–
1590
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
266

Rossebø
AB
,
Pedersen
TR
,
Boman
K
,
Brudi
P
,
Chambers
JB
,
Egstrup
K
,
Gerdts
E
,
Gohlke-Bärwolf
C
,
Holme
I
,
Kesäniemi
YA
,
Malbecq
W
,
Nienaber
CA
,
Ray
S
,
Skjaerpe
T
,
Wachtell
K
,
Willenheimer
R
; SEAS Investigators.
Intensive lipid lowering with simvastatin and ezetimibe in aortic stenosis
.
N Engl J Med
2008
;
359
:
1343
–
1356
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
267

Sharp Collaborative Group.

Study of Heart and Renal Protection (SHARP): randomized trial to assess the
effects of lowering low-density lipoprotein cholesterol among 9,438 patients
with chronic kidney disease
.
Am Heart J
2010
;
160
:
785
–
794.e10
.




Crossref
Search ADS

PubMed

WorldCat

 
268

Ference
BA
,
Cannon
CP
,
Landmesser
U
,
Luscher
TF
,
Catapano
AL
,
Ray
KK.
Reduction of low density lipoprotein-cholesterol and cardiovascular events with
proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors and statins: an
analysis of FOURIER, SPIRE, and the Cholesterol Treatment Trialists
Collaboration
.
Eur Heart J
2018
;
39
:
2540
–
2545
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
269

Myocardial Infarction Genetics Consortium Investigators,

Stitziel
NO
,
Won
HH
,
Morrison
AC
,
Peloso
GM
,
Do
R
,
Lange
LA
,
Fontanillas
P
,
Gupta
N
,
Duga
S
,
Goel
A
,
Farrall
M
,
Saleheen
D
,
Ferrario
P
,
Konig
I
,
Asselta
R
,
Merlini
PA
,
Marziliano
N
,
Notarangelo
MF
,
Schick
U
,
Auer
P
,
Assimes
TL
,
Reilly
M
,
Wilensky
R
,
Rader
DJ
,
Hovingh
GK
,
Meitinger
T
,
Kessler
T
,
Kastrati
A
,
Laugwitz
KL
,
Siscovick
D
,
Rotter
JI
,
Hazen
SL
,
Tracy
R
,
Cresci
S
,
Spertus
J
,
Jackson
R
,
Schwartz
SM
,
Natarajan
P
,
Crosby
J
,
Muzny
D
,
Ballantyne
C
,
Rich
SS
,
O'Donnell
CJ
,
Abecasis
G
,
Sunyaev
S
,
Nickerson
DA
,
Buring
JE
,
Ridker
PM
,
Chasman
DI
,
Austin
E
,
Ye
Z
,
Kullo
IJ
,
Weeke
PE
,
Shaffer
CM
,
Bastarache
LA
,
Denny
JC
,
Roden
DM
,
Palmer
C
,
Deloukas
P
,
Lin
DY
,
Tang
ZZ
,
Erdmann
J
,
Schunkert
H
,
Danesh
J
,
Marrugat
J
,
Elosua
R
,
Ardissino
D
,
McPherson
R
,
Watkins
H
,
Reiner
AP
,
Wilson
JG
,
Altshuler
D
,
Gibbs
RA
,
Lander
ES
,
Boerwinkle
E
,
Gabriel
S
,
Kathiresan
S.
Inactivating mutations in NPC1L1 and protection from coronary heart disease
.
N Engl J Med
2014
;
371
:
2072
–
2082
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
270

Pirillo
A
,
Catapano
AL
,
Norata
GD.
Niemann-Pick C1-Like 1 (NPC1L1) inhibition and cardiovascular diseases
.
Curr Med Chem
2016
;
23
:
983
–
999
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
271

Tsujita
K
,
Sugiyama
S
,
Sumida
H
,
Shimomura
H
,
Yamashita
T
,
Yamanaga
K
,
Komura
N
,
Sakamoto
K
,
Oka
H
,
Nakao
K
,
Nakamura
S
,
Ishihara
M
,
Matsui
K
,
Sakaino
N
,
Nakamura
N
,
Yamamoto
N
,
Koide
S
,
Matsumura
T
,
Fujimoto
K
,
Tsunoda
R
,
Morikami
Y
,
Matsuyama
K
,
Oshima
S
,
Kaikita
K
,
Hokimoto
S
,
Ogawa
H
; PRECISE-IVUS Investigators.
Impact of dual lipid-lowering strategy with ezetimibe and atorvastatin on
coronary plaque regression in patients with percutaneous coronary intervention:
the multicenter randomized controlled PRECISE-IVUS trial
.
J Am Coll Cardiol
2015
;
66
:
495
–
507
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
272

Khan
SU
,
Talluri
S
,
Riaz
H
,
Rahman
H
,
Nasir
F
,
Bin Riaz
I
,
Sattur
S
,
Ahmed
H
,
Kaluski
E
,
Krasuski
R.
A Bayesian network meta-analysis of PCSK9 inhibitors, statins and ezetimibe with
or without statins for cardiovascular outcomes
.
Eur J Prev Cardiol
2018
;
25
:
844
–
853
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
273

Koskinas
KC
,
Siontis
GCM
,
Piccolo
R
,
Mavridis
D
,
Raber
L
,
Mach
F
,
Windecker
S.
Effect of statins and non-statin LDL-lowering medications on cardiovascular
outcomes in secondary prevention: a meta-analysis of randomized trials
.
Eur Heart J
2018
;
39
:
1172
–
1180
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
274

Mazidi
M
,
Rezaie
P
,
Karimi
E
,
Kengne
AP.
The effects of bile acid sequestrants on lipid profile and blood glucose
concentrations: a systematic review and meta-analysis of randomized controlled
trials
.
Int J Cardiol
2017
;
227
:
850
–
857
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
275

Ooi
CP
,
Loke
SC.
Colesevelam for type 2 diabetes mellitus: an abridged Cochrane review
.
Diabet Med
2014
;
31
:
2
–
14
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
276

The Lipid Research Clinics Program.

Pre-entry characteristics of participants in the Lipid Research Clinics'
Coronary Primary Prevention Trial
.
J Chronic Dis
1983
;
36
:
467
–
479
.




Crossref
Search ADS

PubMed

WorldCat

 
277

The Lipid Research Clinics Program.

The Lipid Research Clinics Coronary Primary Prevention Trial results. I.
Reduction in incidence of coronary heart disease
.
JAMA
1984
;
251
(
3
):
351
–
64
.




Crossref
Search ADS

PubMed

WorldCat

 
278

The Lipid Research Clinics Program.

The Lipid Research Clinics Coronary Primary Prevention Trial. Results of 6 years
of post-trial follow-up. The Lipid Research Clinics Investigators
.
Arch Intern Med
1992
;
152
:
1399
–
1410
.




Crossref
Search ADS

PubMed

WorldCat

 
279

He
L
,
Wickremasingha
P
,
Lee
J
,
Tao
B
,
Mendell-Harary
J
,
Walker
J
,
Wight
D.
Lack of effect of colesevelam HCl on the single-dose pharmacokinetics of
aspirin, atenolol, enalapril, phenytoin, rosiglitazone, and sitagliptin
.
Diabetes Res Clin Pract
2014
;
104
:
401
–
409
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
280

Abifadel
M
,
Varret
M
,
Rabes
JP
,
Allard
D
,
Ouguerram
K
,
Devillers
M
,
Cruaud
C
,
Benjannet
S
,
Wickham
L
,
Erlich
D
,
Derre
A
,
Villeger
L
,
Farnier
M
,
Beucler
I
,
Bruckert
E
,
Chambaz
J
,
Chanu
B
,
Lecerf
JM
,
Luc
G
,
Moulin
P
,
Weissenbach
J
,
Prat
A
,
Krempf
M
,
Junien
C
,
Seidah
NG
,
Boileau
C.
Mutations in PCSK9 cause autosomal dominant hypercholesterolemia
.
Nat Genet
2003
;
34
:
154
–
156
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
281

Norata
GD
,
Tibolla
G
,
Catapano
AL.
Targeting PCSK9 for hypercholesterolemia
.
Annu Rev Pharmacol Toxicol
2014
;
54
:
273
–
293
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
282

Nozue
T.
Lipid lowering therapy and circulating PCSK9 concentration
.
J Atheroscler Thromb
2017
;
24
:
895
–
907
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
283

Cho
L
,
Rocco
M
,
Colquhoun
D
,
Sullivan
D
,
Rosenson
RS
,
Dent
R
,
Xue
A
,
Scott
R
,
Wasserman
SM
,
Stroes
E.
Clinical profile of statin intolerance in the phase 3 GAUSS-2 Study
.
Cardiovasc Drugs Ther
2016
;
30
:
297
–
304
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
284

Schmidt
AF
,
Pearce
LS
,
Wilkins
JT
,
Overington
JP
,
Hingorani
AD
,
Casas
JP.
PCSK9 monoclonal antibodies for the primary and secondary prevention of
cardiovascular disease
.
Cochrane Database Syst Rev
2017
;
4
:
CD011748
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
285

Thedrez
A
,
Blom
DJ
,
Ramin-Mangata
S
,
Blanchard
V
,
Croyal
M
,
Chemello
K
,
Nativel
B
,
Pichelin
M
,
Cariou
B
,
Bourane
S
,
Tang
L
,
Farnier
M
,
Raal
FJ
,
Lambert
G.
Homozygous familial hypercholesterolemia patients with identical mutations
variably express the LDLR (low-density lipoprotein receptor): implications for
the efficacy of evolocumab
.
Arterioscler Thromb Vasc Biol
2018
;
38
:
592
–
598
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
286

Robinson
JG
,
Farnier
M
,
Krempf
M
,
Bergeron
J
,
Luc
G
,
Averna
M
,
Stroes
ES
,
Langslet
G
,
Raal
FJ
,
El Shahawy
M
,
Koren
MJ
,
Lepor
NE
,
Lorenzato
C
,
Pordy
R
,
Chaudhari
U
,
Kastelein
JJ
; ODYSSEY LONG TERM Investigators.
Efficacy and safety of alirocumab in reducing lipids and cardiovascular events
.
N Engl J Med
2015
;
372
:
1489
–
1499
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
287

Stein
EA
,
Turner
TA.
Are the PCSK9 inhibitors the panacea of atherosclerosis treatment?
Expert Rev Cardiovasc Ther
2017
;
15
:
491
–
494
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
288

Gaudet
D
,
Kereiakes
DJ
,
McKenney
JM
,
Roth
EM
,
Hanotin
C
,
Gipe
D
,
Du
Y
,
Ferrand
AC
,
Ginsberg
HN
,
Stein
EA.
Effect of alirocumab, a monoclonal proprotein convertase subtilisin/kexin 9
antibody, on lipoprotein(a) concentrations (a pooled analysis of 150 mg every
two weeks dosing from phase 2 trials)
.
Am J Cardiol
2014
;
114
:
711
–
715
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
289

Raal
FJ
,
Giugliano
RP
,
Sabatine
MS
,
Koren
MJ
,
Langslet
G
,
Bays
H
,
Blom
D
,
Eriksson
M
,
Dent
R
,
Wasserman
SM
,
Huang
F
,
Xue
A
,
Albizem
M
,
Scott
R
,
Stein
EA.
Reduction in lipoprotein(a) with PCSK9 monoclonal antibody evolocumab (AMG 145):
a pooled analysis of more than 1,300 patients in 4 phase II trials
.
J Am Coll Cardiol
2014
;
63
:
1278
–
1288
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
290

Sabatine
MS
,
Giugliano
RP
,
Wiviott
SD
,
Raal
FJ
,
Blom
DJ
,
Robinson
J
,
Ballantyne
CM
,
Somaratne
R
,
Legg
J
,
Wasserman
SM
,
Scott
R
,
Koren
MJ
,
Stein
EA
; Open-Label Study of Long-Term Evaluation against LDL Cholesterol (OSLER)
Investigators.
Efficacy and safety of evolocumab in reducing lipids and cardiovascular events
.
N Engl J Med
2015
;
372
:
1500
–
1509
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
291

Navarese
EP
,
Kolodziejczak
M
,
Kereiakes
DJ
,
Tantry
US
,
O'Connor
C
,
Gurbel
PA.
Proprotein convertase subtilisin/kexin type 9 monoclonal antibodies for acute
coronary syndrome: a narrative review
.
Ann Intern Med
2016
;
164
:
600
–
607
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
292

Cicero
AF
,
Tartagni
E
,
Ertek
S.
Safety and tolerability of injectable lipid-lowering drugs: a review of
available clinical data
.
Expert Opin Drug Saf
2014
;
13
:
1023
–
1030
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
293

Lipinski
MJ
,
Benedetto
U
,
Escarcega
RO
,
Biondi-Zoccai
G
,
Lhermusier
T
,
Baker
NC
,
Torguson
R
,
Brewer
HB
Jr,
Waksman
R.
The impact of proprotein convertase subtilisin-kexin type 9 serine protease
inhibitors on lipid levels and outcomes in patients with primary
hypercholesterolaemia: a network meta-analysis
.
Eur Heart J
2016
;
37
:
536
–
545
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
294

Schmidt
AF
,
Swerdlow
DI
,
Holmes
MV
,
Patel
RS
,
Fairhurst-Hunter
Z
,
Lyall
DM
,
Hartwig
FP
,
Horta
BL
,
Hypponen
E
,
Power
C
,
Moldovan
M
,
van Iperen
E
,
Hovingh
GK
,
Demuth
I
,
Norman
K
,
Steinhagen-Thiessen
E
,
Demuth
J
,
Bertram
L
,
Liu
T
,
Coassin
S
,
Willeit
J
,
Kiechl
S
,
Willeit
K
,
Mason
D
,
Wright
J
,
Morris
R
,
Wanamethee
G
,
Whincup
P
,
Ben-Shlomo
Y
,
McLachlan
S
,
Price
JF
,
Kivimaki
M
,
Welch
C
,
Sanchez-Galvez
A
,
Marques-Vidal
P
,
Nicolaides
A
,
Panayiotou
AG
,
Onland-Moret
NC
,
van der Schouw
YT
,
Matullo
G
,
Fiorito
G
,
Guarrera
S
,
Sacerdote
C
,
Wareham
NJ
,
Langenberg
C
,
Scott
R
,
Luan
J
,
Bobak
M
,
Malyutina
S
,
Pajak
A
,
Kubinova
R
,
Tamosiunas
A
,
Pikhart
H
,
Husemoen
LL
,
Grarup
N
,
Pedersen
O
,
Hansen
T
,
Linneberg
A
,
Simonsen
KS
,
Cooper
J
,
Humphries
SE
,
Brilliant
M
,
Kitchner
T
,
Hakonarson
H
,
Carrell
DS
,
McCarty
CA
,
Kirchner
HL
,
Larson
EB
,
Crosslin
DR
,
de Andrade
M
,
Roden
DM
,
Denny
JC
,
Carty
C
,
Hancock
S
,
Attia
J
,
Holliday
E
,
O'Donnell
M
,
Yusuf
S
,
Chong
M
,
Pare
G
,
van der Harst
P
,
Said
MA
,
Eppinga
RN
,
Verweij
N
,
Snieder
H
,
LifeLines Cohort study
g
,
Christen
T
,
Mook-Kanamori
DO
,
Gustafsson
S
,
Lind
L
,
Ingelsson
E
,
Pazoki
R
,
Franco
O
,
Hofman
A
,
Uitterlinden
A
,
Dehghan
A
,
Teumer
A
,
Baumeister
S
,
Dorr
M
,
Lerch
MM
,
Volker
U
,
Volzke
H
,
Ward
J
,
Pell
JP
,
Smith
DJ
,
Meade
T
,
Maitland-van der Zee
AH
,
Baranova
EV
,
Young
R
,
Ford
I
,
Campbell
A
,
Padmanabhan
S
,
Bots
ML
,
Grobbee
DE
,
Froguel
P
,
Thuillier
D
,
Balkau
B
,
Bonnefond
A
,
Cariou
B
,
Smart
M
,
Bao
Y
,
Kumari
M
,
Mahajan
A
,
Ridker
PM
,
Chasman
DI
,
Reiner
AP
,
Lange
LA
,
Ritchie
MD
,
Asselbergs
FW
,
Casas
JP
,
Keating
BJ
,
Preiss
D
,
Hingorani
AD
UCLEB consortium
Sattar
N.
PCSK9 genetic variants and risk of type 2 diabetes: a Mendelian randomisation
study
.
Lancet Diabetes Endocrinol
2017
;
5
:
97
–
105
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
295

Cao
YX
,
Liu
HH
,
Dong
QT
,
Li
S
,
Li
JJ.
Effect of proprotein convertase subtilisin/kexin type 9 (PCSK9) monoclonal
antibodies on new-onset diabetes mellitus and glucose metabolism: a systematic
review and meta-analysis
.
Diabetes Obes Metab
2018
;
20
:
1391
–
1398
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
296

de Carvalho
LSF
,
Campos
AM
,
Sposito
AC.
Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and incident
type 2 diabetes: a systematic review and meta-analysis with over 96,000
patient-years
.
Diabetes Care
2018
;
41
:
364
–
367
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
297

Sabatine
MS
,
Leiter
LA
,
Wiviott
SD
,
Giugliano
RP
,
Deedwania
P
,
De Ferrari
GM
,
Murphy
SA
,
Kuder
JF
,
Gouni-Berthold
I
,
Lewis
BS
,
Handelsman
Y
,
Pineda
AL
,
Honarpour
N
,
Keech
AC
,
Sever
PS
,
Pedersen
TR.
Cardiovascular safety and efficacy of the PCSK9 inhibitor evolocumab in patients
with and without diabetes and the effect of evolocumab on glycaemia and risk of
new-onset diabetes: a prespecified analysis of the FOURIER randomised controlled
trial
.
Lancet Diabetes Endocrinol
2017
;
5
:
941
–
950
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
298

Zhang
XL
,
Zhu
L
,
Wei
ZH
,
Zhu
QQ
,
Qiao
JZ
,
Dai
Q
,
Huang
W
,
Li
XH
,
Xie
J
,
Kang
LN
,
Wang
L
,
Xu
B.
Comparative efficacy and safety of everolimus-eluting bioresorbable scaffold
versus everolimus-eluting metallic stents: a systematic review and meta-analysis
.
Ann Intern Med
2016
;
164
:
752
–
763
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
299

Giugliano
RP
,
Cannon
CP
,
Blazing
MA
,
Nicolau
JC
,
Corbalan
R
,
Spinar
J
,
Park
JG
,
White
JA
,
Bohula
EA
,
Braunwald
E
; IMPROVE-IT (Improved Reduction of Outcomes: Vytorin Efficacy International
Trial) Investigators.
Benefit of adding ezetimibe to statin therapy on cardiovascular outcomes and
safety in patients with versus without diabetes mellitus: results from
IMPROVE-IT (Improved Reduction of Outcomes: Vytorin Efficacy International
Trial)
.
Circulation
2018
;
137
:
1571
–
1582
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
300

Ridker
PM
,
Tardif
JC
,
Amarenco
P
,
Duggan
W
,
Glynn
RJ
,
Jukema
JW
,
Kastelein
JJP
,
Kim
AM
,
Koenig
W
,
Nissen
S
,
Revkin
J
,
Rose
LM
,
Santos
RD
,
Schwartz
PF
,
Shear
CL
,
Yunis
C
; SPIRE Investigators.
Lipid-reduction variability and antidrug-antibody formation with bococizumab
.
N Engl J Med
2017
;
376
:
1517
–
1526
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
301

Cuchel
M
,
Meagher
EA
,
du Toit Theron
H
,
Blom
DJ
,
Marais
AD
,
Hegele
RA
,
Averna
MR
,
Sirtori
CR
,
Shah
PK
,
Gaudet
D
,
Stefanutti
C
,
Vigna
GB
,
Du Plessis
AM
,
Propert
KJ
,
Sasiela
WJ
,
Bloedon
LT
,
Rader
DJ
; Phase 3 HoFH Lomitapide Study investigators.
Efficacy and safety of a microsomal triglyceride transfer protein inhibitor in
patients with homozygous familial hypercholesterolaemia: a single-arm,
open-label, phase 3 study
.
Lancet
2013
;
381
:
40
–
46
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
302

Cuchel
M
,
Bloedon
LT
,
Szapary
PO
,
Kolansky
DM
,
Wolfe
ML
,
Sarkis
A
,
Millar
JS
,
Ikewaki
K
,
Siegelman
ES
,
Gregg
RE
,
Rader
DJ.
Inhibition of microsomal triglyceride transfer protein in familial
hypercholesterolemia
.
N Engl J Med
2007
;
356
:
148
–
156
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
303

Agarwala
A
,
Jones
P
,
Nambi
V.
The role of antisense oligonucleotide therapy in patients with familial
hypercholesterolemia: risks, benefits, and management recommendations
.
Curr Atheroscler Rep
2015
;
17
:
467
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
304

Li
N
,
Li
Q
,
Tian
XQ
,
Qian
HY
,
Yang
YJ.
Mipomersen is a promising therapy in the management of hypercholesterolemia: a
meta-analysis of randomized controlled trials
.
Am J Cardiovasc Drugs
2014
;
14
:
367
–
376
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
305

Chapman
MJ
,
Redfern
JS
,
McGovern
ME
,
Giral
P.
Niacin and fibrates in atherogenic dyslipidemia: pharmacotherapy to reduce
cardiovascular risk
.
Pharmacol Ther
2010
;
126
:
314
–
345
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
306

Accord Study Group,

Ginsberg
HN
,
Elam
MB
,
Lovato
LC
,
Crouse
JR III
,
Leiter
LA
,
Linz
P
,
Friedewald
WT
,
Buse
JB
,
Gerstein
HC
,
Probstfield
J
,
Grimm
RH
,
Ismail-Beigi
F
,
Bigger
JT
,
Goff
DC
Jr,
Cushman
WC
,
Simons-Morton
DG
,
Byington
RP.
Effects of combination lipid therapy in type 2 diabetes mellitus
.
N Engl J Med
2010
;
362
:
1563
–
1574
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
307

Keech
A
,
Simes
RJ
,
Barter
P
,
Best
J
,
Scott
R
,
Taskinen
MR
,
Forder
P
,
Pillai
A
,
Davis
T
,
Glasziou
P
,
Drury
P
,
Kesaniemi
YA
,
Sullivan
D
,
Hunt
D
,
Colman
P
,
d'Emden
M
,
Whiting
M
,
Ehnholm
C
,
Laakso
M
; FIELD study investigators.
Effects of long-term fenofibrate therapy on cardiovascular events in 9795 people
with type 2 diabetes mellitus (the FIELD study): randomised controlled trial
.
Lancet
2005
;
366
:
1849
–
1861
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
308

Frick
MH
,
Elo
O
,
Haapa
K
,
Heinonen
OP
,
Heinsalmi
P
,
Helo
P
,
Huttunen
JK
,
Kaitaniemi
P
,
Koskinen
P
,
Manninen
V
, et al. 
Helsinki Heart Study: primary-prevention trial with gemfibrozil in middle-aged
men with dyslipidemia. Safety of treatment, changes in risk factors, and
incidence of coronary heart disease
.
N Engl J Med
1987
;
317
:
1237
–
1245
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
309

Rubins
HB
,
Robins
SJ
,
Collins
D
,
Fye
CL
,
Anderson
JW
,
Elam
MB
,
Faas
FH
,
Linares
E
,
Schaefer
EJ
,
Schectman
G
,
Wilt
TJ
,
Wittes
J.
Gemfibrozil for the secondary prevention of coronary heart disease in men with
low levels of high-density lipoprotein cholesterol. Veterans Affairs
High-Density Lipoprotein Cholesterol Intervention Trial Study Group
.
N Engl J Med
1999
;
341
:
410
–
418
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
310

Lipids and lipoproteins in symptomatic coronary heart disease. Distribution,
intercorrelations, and significance for risk classification in 6,700 men and
1,500 women.

The Bezafibrate Infarction Prevention (BIP) Study Group
,
Israel
.
Circulation
1992
;
86
:
839
–
848
.



Google Scholar

Google Preview

OpenURL Placeholder Text

WorldCat

COPAC
311

Meade
T
,
Zuhrie
R
,
Cook
C
,
Cooper
J.
Bezafibrate in men with lower extremity arterial disease: randomised controlled
trial
.
BMJ
2002
;
325
:
1139
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
312

Ip
CK
,
Jin
DM
,
Gao
JJ
,
Meng
Z
,
Meng
J
,
Tan
Z
,
Wang
JF
,
Geng
DF.
Effects of add-on lipid-modifying therapy on top of background statin treatment
on major cardiovascular events: a meta-analysis of randomized controlled trials
.
Int J Cardiol
2015
;
191
:
138
–
148
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
313

Keene
D
,
Price
C
,
Shun-Shin
MJ
,
Francis
DP.
Effect on cardiovascular risk of high density lipoprotein targeted drug
treatments niacin, fibrates, and CETP inhibitors: meta-analysis of randomised
controlled trials including 117,411 patients
.
BMJ
2014
;
349
:
g4379
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
314

Bruckert
E
,
Labreuche
J
,
Deplanque
D
,
Touboul
PJ
,
Amarenco
P.
Fibrates effect on cardiovascular risk is greater in patients with high
triglyceride levels or atherogenic dyslipidemia profile: a systematic review and
meta-analysis
.
J Cardiovasc Pharmacol
2011
;
57
:
267
–
272
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
315

Jun
M
,
Zhu
B
,
Tonelli
M
,
Jardine
MJ
,
Patel
A
,
Neal
B
,
Liyanage
T
,
Keech
A
,
Cass
A
,
Perkovic
V.
Effects of fibrates in kidney disease: a systematic review and meta-analysis
.
J Am Coll Cardiol
2012
;
60
:
2061
–
2071
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
316

Lee
M
,
Saver
JL
,
Towfighi
A
,
Chow
J
,
Ovbiagele
B.
Efficacy of fibrates for cardiovascular risk reduction in persons with
atherogenic dyslipidemia: a meta-analysis
.
Atherosclerosis
2011
;
217
:
492
–
498
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
317

Fruchart
JC.
Pemafibrate (K-877), a novel selective peroxisome proliferator-activated
receptor alpha modulator for management of atherogenic dyslipidaemia
.
Cardiovasc Diabetol
2017
;
16
:
124
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
318

Pradhan
AD
,
Paynter
NP
,
Everett
BM
,
Glynn
RJ
,
Amarenco
P
,
Elam
M
,
Ginsberg
H
,
Hiatt
WR
,
Ishibashi
S
,
Koenig
W
,
Nordestgaard
BG
,
Fruchart
JC
,
Libby
P
,
Ridker
PM.
Rationale and design of the Pemafibrate to Reduce Cardiovascular Outcomes by
Reducing Triglycerides in Patients with Diabetes (PROMINENT) study
.
Am Heart J
2018
;
206
:
80
–
93
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
319

Davidson
MH
,
Armani
A
,
McKenney
JM
,
Jacobson
TA.
Safety considerations with fibrate therapy
.
Am J Cardiol
2007
;
99
:
3C
–
18C
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
320

Graham
DJ
,
Staffa
JA
,
Shatin
D
,
Andrade
SE
,
Schech
SD
,
La Grenade
L
,
Gurwitz
JH
,
Chan
KA
,
Goodman
MJ
,
Platt
R.
Incidence of hospitalized rhabdomyolysis in patients treated with lipid-lowering
drugs
.
JAMA
2004
;
292
:
2585
–
2590
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
321

Preiss
D
,
Tikkanen
MJ
,
Welsh
P
,
Ford
I
,
Lovato
LC
,
Elam
MB
,
LaRosa
JC
,
DeMicco
DA
,
Colhoun
HM
,
Goldenberg
I
,
Murphy
MJ
,
MacDonald
TM
,
Pedersen
TR
,
Keech
AC
,
Ridker
PM
,
Kjekshus
J
,
Sattar
N
,
McMurray
JJ.
Lipid-modifying therapies and risk of pancreatitis: a meta-analysis
.
JAMA
2012
;
308
:
804
–
811
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
322

Taskinen
MR
,
Sullivan
DR
,
Ehnholm
C
,
Whiting
M
,
Zannino
D
,
Simes
RJ
,
Keech
AC
,
Barter
PJ
; FIELD study investigators.
Relationships of HDL cholesterol, ApoA-I, and ApoA-II with homocysteine and
creatinine in patients with type 2 diabetes treated with fenofibrate
.
Arterioscler Thromb Vasc Biol
2009
;
29
:
950
–
955
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
323

Balk
EM
,
Lichtenstein
AH
,
Chung
M
,
Kupelnick
B
,
Chew
P
,
Lau
J.
Effects of omega-3 fatty acids on serum markers of cardiovascular disease risk:
a systematic review
.
Atherosclerosis
2006
;
189
:
19
–
30
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
324

Ballantyne
CM
,
Bays
HE
,
Kastelein
JJ
,
Stein
E
,
Isaacsohn
JL
,
Braeckman
RA
,
Soni
PN.
Efficacy and safety of eicosapentaenoic acid ethyl ester (AMR101) therapy in
statin-treated patients with persistent high triglycerides (from the ANCHOR
study)
.
Am J Cardiol
2012
;
110
:
984
–
992
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
325

Bays
HE
,
Ballantyne
CM
,
Kastelein
JJ
,
Isaacsohn
JL
,
Braeckman
RA
,
Soni
PN.
Eicosapentaenoic acid ethyl ester (AMR101) therapy in patients with very high
triglyceride levels (from the Multi-center, plAcebo-controlled, Randomized,
double-blINd, 12-week study with an open-label Extension [MARINE] trial)
.
Am J Cardiol
2011
;
108
:
682
–
690
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
326

Kastelein
JJ
,
Maki
KC
,
Susekov
A
,
Ezhov
M
,
Nordestgaard
BG
,
Machielse
BN
,
Kling
D
,
Davidson
MH.
Omega-3 free fatty acids for the treatment of severe hypertriglyceridemia: the
EpanoVa fOr Lowering Very high triglyceridEs (EVOLVE) trial
.
J Clin Lipidol
2014
;
8
:
94
–
106
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
327

Stroes
ESG
,
Susekov
AV
,
de Bruin
TWA
,
Kvarnstrom
M
,
Yang
H
,
Davidson
MH.
Omega-3 carboxylic acids in patients with severe hypertriglyceridemia: EVOLVE
II, a randomized, placebo-controlled trial
.
J Clin Lipidol
2018
;
12
:
321
–
330
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
328

Abdelhamid
AS
,
Brown
TJ
,
Brainard
JS
,
Biswas
P
,
Thorpe
GC
,
Moore
HJ
,
Deane
KH
,
AlAbdulghafoor
FK
,
Summerbell
CD
,
Worthington
HV
,
Song
F
,
Hooper
L.
Omega-3 fatty acids for the primary and secondary prevention of cardiovascular
disease
.
Cochrane Database Syst Rev
2018
;
7
:
CD003177
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
329

ASCEND Study Collaborative Group,

Bowman
L
,
Mafham
M
,
Wallendszus
K
,
Stevens
W
,
Buck
G
,
Barton
J
,
Murphy
K
,
Aung
T
,
Haynes
R
,
Cox
J
,
Murawska
A
,
Young
A
,
Lay
M
,
Chen
F
,
Sammons
E
,
Waters
E
,
Adler
A
,
Bodansky
J
,
Farmer
A
,
McPherson
R
,
Neil
A
,
Simpson
D
,
Peto
R
,
Baigent
C
,
Collins
R
,
Parish
S
,
Armitage
J.
Effects of n-3 fatty acid supplements in diabetes mellitus
.
N Engl J Med
2018
;
379
:
1540
–
1550
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
330

Hooper
L
,
Thompson
RL
,
Harrison
RA
,
Summerbell
CD
,
Ness
AR
,
Moore
HJ
,
Worthington
HV
,
Durrington
PN
,
Higgins
JP
,
Capps
NE
,
Riemersma
RA
,
Ebrahim
SB
,
Davey Smith
G.
Risks and benefits of omega 3 fats for mortality, cardiovascular disease, and
cancer: systematic review
.
BMJ
2006
;
332
:
752
–
760
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
331

Marchioli
R
,
Barzi
F
,
Bomba
E
,
Chieffo
C
,
Di Gregorio
D
,
Di Mascio
R
,
Franzosi
MG
,
Geraci
E
,
Levantesi
G
,
Maggioni
AP
,
Mantini
L
,
Marfisi
RM
,
Mastrogiuseppe
G
,
Mininni
N
,
Nicolosi
GL
,
Santini
M
,
Schweiger
C
,
Tavazzi
L
,
Tognoni
G
,
Tucci
C
,
Valagussa
F
; GISSI-Prevenzione Investigators.
Early protection against sudden death by n-3 polyunsaturated fatty acids after
myocardial infarction: time-course analysis of the results of the Gruppo
Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico
(GISSI)-Prevenzione
.
Circulation
2002
;
105
:
1897
–
1903
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
332

Nicholls
SJ
,
Lincoff
AM
,
Bash
D
,
Ballantyne
CM
,
Barter
PJ
,
Davidson
MH
,
Kastelein
JJP
,
Koenig
W
,
McGuire
DK
,
Mozaffarian
D
,
Pedersen
TR
,
Ridker
PM
,
Ray
K
,
Karlson
BW
,
Lundstrom
T
,
Wolski
K
,
Nissen
SE.
Assessment of omega-3 carboxylic acids in statin-treated patients with high
levels of triglycerides and low levels of high-density lipoprotein cholesterol:
rationale and design of the STRENGTH trial
.
Clin Cardiol
2018
;
41
:
1281
–
1288
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
333

Manson
JE
,
Cook
NR
,
Lee
IM
,
Christen
W
,
Bassuk
SS
,
Mora
S
,
Gibson
H
,
Albert
CM
,
Gordon
D
,
Copeland
T
,
D'Agostino
D
,
Friedenberg
G
,
Ridge
C
,
Bubes
V
,
Giovannucci
EL
,
Willett
WC
,
Buring
JE
; VITAL Research Group.
Marine n-3 fatty acids and prevention of cardiovascular disease and cancer
.
N Engl J Med
2019
;
380
:
23
–
32
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
334

Brasky
TM
,
Darke
AK
,
Song
X
,
Tangen
CM
,
Goodman
PJ
,
Thompson
IM
,
Meyskens
FL
Jr,
Goodman
GE
,
Minasian
LM
,
Parnes
HL
,
Klein
EA
,
Kristal
AR.
Plasma phospholipid fatty acids and prostate cancer risk in the SELECT trial
.
J Natl Cancer Inst
2013
;
105
:
1132
–
41
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
335

Kamanna
VS
,
Kashyap
ML.
Mechanism of action of niacin
.
Am J Cardiol
2008
;
101
:
20B
–
26B
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
336

Barter
PJ
,
Caulfield
M
,
Eriksson
M
,
Grundy
SM
,
Kastelein
JJ
,
Komajda
M
,
Lopez-Sendon
J
,
Mosca
L
,
Tardif
JC
,
Waters
DD
,
Shear
CL
,
Revkin
JH
,
Buhr
KA
,
Fisher
MR
,
Tall
AR
,
Brewer
B
; ILLUMINATE Investigators.
Effects of torcetrapib in patients at high risk for coronary events
.
N Engl J Med
2007
;
357
:
2109
–
2122
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
337

Ference
BA
,
Kastelein
JJP
,
Ginsberg
HN
,
Chapman
MJ
,
Nicholls
SJ
,
Ray
KK
,
Packard
CJ
,
Laufs
U
,
Brook
RD
,
Oliver-Williams
C
,
Butterworth
AS
,
Danesh
J
,
Smith
GD
,
Catapano
AL
,
Sabatine
MS.
Association of genetic variants related to CETP inhibitors and statins with
lipoprotein levels and cardiovascular risk
.
JAMA
2017
;
318
:
947
–
956
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
338

Fitzgerald
K
,
White
S
,
Borodovsky
A
,
Bettencourt
BR
,
Strahs
A
,
Clausen
V
,
Wijngaard
P
,
Horton
JD
,
Taubel
J
,
Brooks
A
,
Fernando
C
,
Kauffman
RS
,
Kallend
D
,
Vaishnaw
A
,
Simon
A.
A highly durable RNAi therapeutic inhibitor of PCSK9
.
N Engl J Med
2017
;
376
:
41
–
51
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
339

Ray
KK
,
Landmesser
U
,
Leiter
LA
,
Kallend
D
,
Dufour
R
,
Karakas
M
,
Hall
T
,
Troquay
RP
,
Turner
T
,
Visseren
FL
,
Wijngaard
P
,
Wright
RS
,
Kastelein
JJ.
Inclisiran in patients at high cardiovascular risk with elevated LDL cholesterol
.
N Engl J Med
2017
;
376
:
1430
–
1440
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
340

Saeed
A
,
Ballantyne
CM.
Bempedoic acid (ETC-1002): a current review
.
Cardiol Clin
2018
;
36
:
257
–
264
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
341

Ballantyne
CM
,
Banach
M
,
Mancini
GBJ
,
Lepor
NE
,
Hanselman
JC
,
Zhao
X
,
Leiter
LA.
Efficacy and safety of bempedoic acid added to ezetimibe in statin-intolerant
patients with hypercholesterolemia: a randomized, placebo-controlled study
.
Atherosclerosis
2018
;
277
:
195
–
203
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
342

Ray
KK
,
Bays
HE
,
Catapano
AL
,
Lalwani
ND
,
Bloedon
LT
,
Sterling
LR
,
Robinson
PL
,
Ballantyne
CM
; CLEAR Harmony Trial.
Safety and efficacy of bempedoic acid to reduce LDL cholesterol
.
N Engl J Med
2019
;
380
:
1022
–
1032
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
343

Stitziel
NO
,
Khera
AV
,
Wang
X
,
Bierhals
AJ
,
Vourakis
AC
,
Sperry
AE
,
Natarajan
P
,
Klarin
D
,
Emdin
CA
,
Zekavat
SM
,
Nomura
A
,
Erdmann
J
,
Schunkert
H
,
Samani
NJ
,
Kraus
WE
,
Shah
SH
,
Yu
B
,
Boerwinkle
E
,
Rader
DJ
,
Gupta
N
,
Frossard
PM
,
Rasheed
A
,
Danesh
J
,
Lander
ES
,
Gabriel
S
,
Saleheen
D
,
Musunuru
K
,
Kathiresan
S
; PROMIS and Myocardial Infarction Genetics Consortium Investigators.
ANGPTL3 deficiency and protection against coronary artery disease
.
J Am Coll Cardiol
2017
;
69
:
2054
–
2063
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
344

Gaudet
D
,
Gipe
DA
,
Pordy
R
,
Ahmad
Z
,
Cuchel
M
,
Shah
PK
,
Chyu
KY
,
Sasiela
WJ
,
Chan
KC
,
Brisson
D
,
Khoury
E
,
Banerjee
P
,
Gusarova
V
,
Gromada
J
,
Stahl
N
,
Yancopoulos
GD
,
Hovingh
GK.
ANGPTL3 inhibition in homozygous familial hypercholesterolemia
.
N Engl J Med
2017
;
377
:
296
–
297
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
345

Graham
MJ
,
Lee
RG
,
Brandt
TA
,
Tai
LJ
,
Fu
W
,
Peralta
R
,
Yu
R
,
Hurh
E
,
Paz
E
,
McEvoy
BW
,
Baker
BF
,
Pham
NC
,
Digenio
A
,
Hughes
SG
,
Geary
RS
,
Witztum
JL
,
Crooke
RM
,
Tsimikas
S.
Cardiovascular and metabolic effects of ANGPTL3 antisense oligonucleotides
.
N Engl J Med
2017
;
377
:
222
–
232
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
346

Graham
MJ
,
Lee
RG
,
Bell
TA III
,
Fu
W
,
Mullick
AE
,
Alexander
VJ
,
Singleton
W
,
Viney
N
,
Geary
R
,
Su
J
,
Baker
BF
,
Burkey
J
,
Crooke
ST
,
Crooke
RM.
Antisense oligonucleotide inhibition of apolipoprotein C-III reduces plasma
triglycerides in rodents, nonhuman primates, and humans
.
Circ Res
2013
;
112
:
1479
–
1490
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
347

Gouni-Berthold
I
,
Alexander
V
,
Digenio
A
,
DuFour
R
,
Steinhagen-Thiessen
E
,
Martin
S
,
Moriarty
P
,
Hughes
S
,
Jones
R
,
Witztum
JL
,
Gaudet
D.
Apolipoprotein C-III inhibition with volanesorsen in patients with
hypertriglyceridemia (COMPASS): a randomized, double-blind, placebo-controlled
trial
.
Atherosclerosis Supp
2017
;
28
:
e1
–
e2
.





Google Scholar

Crossref
Search ADS


WorldCat

 
348

Gaudet
D
,
Digenio
A
,
Alexander
V
,
Arca
M
,
Jones
A
,
Stroes
E
,
Bergeron
J
,
Civeira
F
,
Hemphill
L
,
Blom
D
,
Flaim
J
,
Hughes
S
,
Geary
R
,
Tsimikas
S
,
Witztum
J
,
Bruckert
E.
The approach study: a randomized, double-blind, placebo-controlled, phase 3
study of volanesorsen administered subcutaneously to patients with familial
chylomicronemia syndrome (FCS)
.
Atherosclerosis
2017
;
263
:
e10
.





Google Scholar

Crossref
Search ADS


WorldCat

 
349

Rocha
NA
,
East
C
,
Zhang
J
,
McCullough
PA.
ApoCIII as a cardiovascular risk factor and modulation by the novel
lipid-lowering agent volanesorsen
.
Curr Atheroscler Rep
2017
;
19
:
62
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
350

Didichenko
SA
,
Navdaev
AV
,
Cukier
AM
,
Gille
A
,
Schuetz
P
,
Spycher
MO
,
Therond
P
,
Chapman
MJ
,
Kontush
A
,
Wright
SD.
Enhanced HDL functionality in small HDL species produced upon remodeling of HDL
by reconstituted HDL, CSL112: effects on cholesterol efflux, anti-inflammatory
and antioxidative activity
.
Circ Res
2016
;
119
:
751
–
763
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
351

Digenio
A
,
Dunbar
RL
,
Alexander
VJ
,
Hompesch
M
,
Morrow
L
,
Lee
RG
,
Graham
MJ
,
Hughes
SG
,
Yu
R
,
Singleton
W
,
Baker
BF
,
Bhanot
S
,
Crooke
RM.
Antisense-mediated lowering of plasma apolipoprotein C-III by volanesorsen
improves dyslipidemia and insulin sensitivity in type 2 diabetes
.
Diabetes Care
2016
;
39
:
1408
–
1415
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
352

Viney
NJ
,
van Capelleveen
JC
,
Geary
RS
,
Xia
S
,
Tami
JA
,
Yu
RZ
,
Marcovina
SM
,
Hughes
SG
,
Graham
MJ
,
Crooke
RM
,
Crooke
ST
,
Witztum
JL
,
Stroes
ES
,
Tsimikas
S.
Antisense oligonucleotides targeting apolipoprotein(a) in people with raised
lipoprotein(a): two randomised, double-blind, placebo-controlled, dose-ranging
trials
.
Lancet
2016
;
388
:
2239
–
2253
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
353

Schreml
J
,
Gouni-Berthold
I.
Role of anti-PCSK9 antibodies in the treatment of patients with statin
intolerance
.
Curr Med Chem
2018
;
25
:
1538
–
1548
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
354

Maki
KC
,
Guyton
JR
,
Orringer
CE
,
Hamilton-Craig
I
,
Alexander
DD
,
Davidson
MH.
Triglyceride-lowering therapies reduce cardiovascular disease event risk in
subjects with hypertriglyceridemia
.
J Clin Lipidol
2016
;
10
:
905
–
914
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
355

Vallejo-Vaz
AJ
,
Fayyad
R
,
Boekholdt
SM
,
Hovingh
GK
,
Kastelein
JJ
,
Melamed
S
,
Barter
P
,
Waters
DD
,
Ray
KK.
Triglyceride-rich lipoprotein cholesterol and risk of cardiovascular events
among patients receiving statin therapy in the TNT trial
.
Circulation
2018
;
138
:
770
–
781
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
356

Catapano
AL
,
Farnier
M
,
Foody
JM
,
Toth
PP
,
Tomassini
JE
,
Brudi
P
,
Tershakovec
AM.
Combination therapy in dyslipidemia: where are we now?
Atherosclerosis
2014
;
237
:
319
–
335
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
357

Global Lipids Genetics Consortium,

Willer
CJ
,
Schmidt
EM
,
Sengupta
S
,
Peloso
GM
,
Gustafsson
S
,
Kanoni
S
,
Ganna
A
,
Chen
J
,
Buchkovich
ML
,
Mora
S
,
Beckmann
JS
,
Bragg-Gresham
JL
,
Chang
HY
,
Demirkan
A
,
Den Hertog
HM
,
Do
R
,
Donnelly
LA
,
Ehret
GB
,
Esko
T
,
Feitosa
MF
,
Ferreira
T
,
Fischer
K
,
Fontanillas
P
,
Fraser
RM
,
Freitag
DF
,
Gurdasani
D
,
Heikkila
K
,
Hypponen
E
,
Isaacs
A
,
Jackson
AU
,
Johansson
A
,
Johnson
T
,
Kaakinen
M
,
Kettunen
J
,
Kleber
ME
,
Li
X
,
Luan
J
,
Lyytikainen
LP
,
Magnusson
PK
,
Mangino
M
,
Mihailov
E
,
Montasser
ME
,
Muller-Nurasyid
M
,
Nolte
IM
,
O'Connell
JR
,
Palmer
CD
,
Perola
M
,
Petersen
AK
,
Sanna
S
,
Saxena
R
,
Service
SK
,
Shah
S
,
Shungin
D
,
Sidore
C
,
Song
C
,
Strawbridge
RJ
,
Surakka
I
,
Tanaka
T
,
Teslovich
TM
,
Thorleifsson
G
,
Van den Herik
EG
,
Voight
BF
,
Volcik
KA
,
Waite
LL
,
Wong
A
,
Wu
Y
,
Zhang
W
,
Absher
D
,
Asiki
G
,
Barroso
I
,
Been
LF
,
Bolton
JL
,
Bonnycastle
LL
,
Brambilla
P
,
Burnett
MS
,
Cesana
G
,
Dimitriou
M
,
Doney
AS
,
Doring
A
,
Elliott
P
,
Epstein
SE
,
Eyjolfsson
GI
,
Gigante
B
,
Goodarzi
MO
,
Grallert
H
,
Gravito
ML
,
Groves
CJ
,
Hallmans
G
,
Hartikainen
AL
,
Hayward
C
,
Hernandez
D
,
Hicks
AA
,
Holm
H
,
Hung
YJ
,
Illig
T
,
Jones
MR
,
Kaleebu
P
,
Kastelein
JJ
,
Khaw
KT
,
Kim
E
,
Klopp
N
,
Komulainen
P
,
Kumari
M
,
Langenberg
C
,
Lehtimaki
T
,
Lin
SY
,
Lindstrom
J
,
Loos
RJ
,
Mach
F
,
McArdle
WL
,
Meisinger
C
,
Mitchell
BD
,
Muller
G
,
Nagaraja
R
,
Narisu
N
,
Nieminen
TV
,
Nsubuga
RN
,
Olafsson
I
,
Ong
KK
,
Palotie
A
,
Papamarkou
T
,
Pomilla
C
,
Pouta
A
,
Rader
DJ
,
Reilly
MP
,
Ridker
PM
,
Rivadeneira
F
,
Rudan
I
,
Ruokonen
A
,
Samani
N
,
Scharnagl
H
,
Seeley
J
,
Silander
K
,
Stancakova
A
,
Stirrups
K
,
Swift
AJ
,
Tiret
L
,
Uitterlinden
AG
,
van Pelt
LJ
,
Vedantam
S
,
Wainwright
N
,
Wijmenga
C
,
Wild
SH
,
Willemsen
G
,
Wilsgaard
T
,
Wilson
JF
,
Young
EH
,
Zhao
JH
,
Adair
LS
,
Arveiler
D
,
Assimes
TL
,
Bandinelli
S
,
Bennett
F
,
Bochud
M
,
Boehm
BO
,
Boomsma
DI
,
Borecki
IB
,
Bornstein
SR
,
Bovet
P
,
Burnier
M
,
Campbell
H
,
Chakravarti
A
,
Chambers
JC
,
Chen
YD
,
Collins
FS
,
Cooper
RS
,
Danesh
J
,
Dedoussis
G
,
de Faire
U
,
Feranil
AB
,
Ferrieres
J
,
Ferrucci
L
,
Freimer
NB
,
Gieger
C
,
Groop
LC
,
Gudnason
V
,
Gyllensten
U
,
Hamsten
A
,
Harris
TB
,
Hingorani
A
,
Hirschhorn
JN
,
Hofman
A
,
Hovingh
GK
,
Hsiung
CA
,
Humphries
SE
,
Hunt
SC
,
Hveem
K
,
Iribarren
C
,
Jarvelin
MR
,
Jula
A
,
Kahonen
M
,
Kaprio
J
,
Kesaniemi
A
,
Kivimaki
M
,
Kooner
JS
,
Koudstaal
PJ
,
Krauss
RM
,
Kuh
D
,
Kuusisto
J
,
Kyvik
KO
,
Laakso
M
,
Lakka
TA
,
Lind
L
,
Lindgren
CM
,
Martin
NG
,
Marz
W
,
McCarthy
MI
,
McKenzie
CA
,
Meneton
P
,
Metspalu
A
,
Moilanen
L
,
Morris
AD
,
Munroe
PB
,
Njolstad
I
,
Pedersen
NL
,
Power
C
,
Pramstaller
PP
,
Price
JF
,
Psaty
BM
,
Quertermous
T
,
Rauramaa
R
,
Saleheen
D
,
Salomaa
V
,
Sanghera
DK
,
Saramies
J
,
Schwarz
PE
,
Sheu
WH
,
Shuldiner
AR
,
Siegbahn
A
,
Spector
TD
,
Stefansson
K
,
Strachan
DP
,
Tayo
BO
,
Tremoli
E
,
Tuomilehto
J
,
Uusitupa
M
,
van Duijn
CM
,
Vollenweider
P
,
Wallentin
L
,
Wareham
NJ
,
Whitfield
JB
,
Wolffenbuttel
BH
,
Ordovas
JM
,
Boerwinkle
E
,
Palmer
CN
,
Thorsteinsdottir
U
,
Chasman
DI
,
Rotter
JI
,
Franks
PW
,
Ripatti
S
,
Cupples
LA
,
Sandhu
MS
,
Rich
SS
,
Boehnke
M
,
Deloukas
P
,
Kathiresan
S
,
Mohlke
KL
,
Ingelsson
E
,
Abecasis
GR.
Discovery and refinement of loci associated with lipid levels
.
Nat Genet
2013
;
45
:
1274
–
1283
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
358

Brahm
AJ
,
Hegele
RA.
Combined hyperlipidemia: familial but not (usually) monogenic
.
Curr Opin Lipidol
2016
;
27
:
131
–
140
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
359

Ripatti
P
,
Ramo
JT
,
Soderlund
S
,
Surakka
I
,
Matikainen
N
,
Pirinen
M
,
Pajukanta
P
,
Sarin
AP
,
Service
SK
,
Laurila
PP
,
Ehnholm
C
,
Salomaa
V
,
Wilson
RK
,
Palotie
A
,
Freimer
NB
,
Taskinen
MR
,
Ripatti
S.
The contribution of GWAS loci in familial dyslipidemias
.
PLoS Genet
2016
;
12
:
e1006078
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
360

Veerkamp
MJ
,
de Graaf
J
,
Bredie
SJ
,
Hendriks
JC
,
Demacker
PN
,
Stalenhoef
AF.
Diagnosis of familial combined hyperlipidemia based on lipid phenotype
expression in 32 families: results of a 5-year follow-up study
.
Arterioscler Thromb Vasc Biol
2002
;
22
:
274
–
282
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
361

Akioyamen
LE
,
Genest
J
,
Shan
SD
,
Reel
RL
,
Albaum
JM
,
Chu
A
,
Tu
JV.
Estimating the prevalence of heterozygous familial hypercholesterolaemia: a
systematic review and meta-analysis
.
BMJ Open
2017
;
7
:
e016461
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
362

de Ferranti
SD
,
Rodday
AM
,
Mendelson
MM
,
Wong
JB
,
Leslie
LK
,
Sheldrick
RC.
Prevalence of familial hypercholesterolemia in the 1999 to 2012 United States
National Health and Nutrition Examination Surveys (NHANES)
.
Circulation
2016
;
133
:
1067
–
1072
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
363

Nordestgaard
BG
,
Chapman
MJ
,
Humphries
SE
,
Ginsberg
HN
,
Masana
L
,
Descamps
OS
,
Wiklund
O
,
Hegele
RA
,
Raal
FJ
,
Defesche
JC
,
Wiegman
A
,
Santos
RD
,
Watts
GF
,
Parhofer
KG
,
Hovingh
GK
,
Kovanen
PT
,
Boileau
C
,
Averna
M
,
Borén
J
,
Bruckert
E
,
Catapano
AL
,
Kuivenhoven
JA
,
Pajukanta
P
,
Ray
K
,
Stalenhoef
AF
,
Stroes
E
,
Taskinen
MR
,
Tybjærg-Hansen
A
; European Atherosclerosis Society Consensus Panel.
Familial hypercholesterolaemia is underdiagnosed and undertreated in the general
population: guidance for clinicians to prevent coronary heart disease: consensus
statement of the European Atherosclerosis Society
.
Eur Heart J
2013
;
34
:
3478
–
3490a
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
364

Risk of fatal coronary heart disease in familial hypercholesterolaemia.

Scientific Steering Committee on behalf of the Simon Broome Register Group
.
BMJ
1991
;
303
:
893
–
896
.




Crossref
Search ADS

PubMed

WorldCat

 
365

World Health Organization. Human Genetics Programme. Familial
hypercholesterolemia: Report of a second WHO consultation. WHO/HGN/FH/Cons/99.2.
Geneva: World Health Organization;

1999
. https://apps.who.int/iris/handle/10665/66346 (17 July 2019).



366

Landmesser
U
,
Chapman
MJ
,
Farnier
M
,
Gencer
B
,
Gielen
S
,
Hovingh
GK
,
Luscher
TF
,
Sinning
D
,
Tokgozoglu
L
,
Wiklund
O
,
Zamorano
JL
,
Pinto
FJ
,
Catapano
AL
; European Society of Cardiology (ESC); European Atherosclerosis Society (EAS).
European Society of Cardiology/European Atherosclerosis Society Task Force
consensus statement on proprotein convertase subtilisin/kexin type 9 inhibitors:
practical guidance for use in patients at very high cardiovascular risk
.
Eur Heart J
2017
;
38
:
2245
–
2255
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
367

Ridker
PM
,
Revkin
J
,
Amarenco
P
,
Brunell
R
,
Curto
M
,
Civeira
F
,
Flather
M
,
Glynn
RJ
,
Gregoire
J
,
Jukema
JW
,
Karpov
Y
,
Kastelein
JJP
,
Koenig
W
,
Lorenzatti
A
,
Manga
P
,
Masiukiewicz
U
,
Miller
M
,
Mosterd
A
,
Murin
J
,
Nicolau
JC
,
Nissen
S
,
Ponikowski
P
,
Santos
RD
,
Schwartz
PF
,
Soran
H
,
White
H
,
Wright
RS
,
Vrablik
M
,
Yunis
C
,
Shear
CL
,
Tardif
JC
; SPIRE Cardiovascular Outcome Investigators.
Cardiovascular efficacy and safety of bococizumab in high-risk patients
.
N Engl J Med
2017
;
376
:
1527
–
1539
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
368

Cuchel
M
,
Bruckert
E
,
Ginsberg
HN
,
Raal
FJ
,
Santos
RD
,
Hegele
RA
,
Kuivenhoven
JA
,
Nordestgaard
BG
,
Descamps
OS
,
Steinhagen-Thiessen
E
,
Tybjaerg-Hansen
A
,
Watts
GF
,
Averna
M
,
Boileau
C
,
Boren
J
,
Catapano
AL
,
Defesche
JC
,
Hovingh
GK
,
Humphries
SE
,
Kovanen
PT
,
Masana
L
,
Pajukanta
P
,
Parhofer
KG
,
Ray
KK
,
Stalenhoef
AF
,
Stroes
E
,
Taskinen
MR
,
Wiegman
A
,
Wiklund
O
,
Chapman
MJ
; European Atherosclerosis Society Consensus Panel on Familial
Hypercholesterolaemia.
Homozygous familial hypercholesterolaemia: new insights and guidance for
clinicians to improve detection and clinical management. A position paper from
the Consensus Panel on Familial Hypercholesterolaemia of the European
Atherosclerosis Society
.
Eur Heart J
2014
;
35
:
2146
–
2157
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
369

Wiegman
A
,
Gidding
SS
,
Watts
GF
,
Chapman
MJ
,
Ginsberg
HN
,
Cuchel
M
,
Ose
L
,
Averna
M
,
Boileau
C
,
Boren
J
,
Bruckert
E
,
Catapano
AL
,
Defesche
JC
,
Descamps
OS
,
Hegele
RA
,
Hovingh
GK
,
Humphries
SE
,
Kovanen
PT
,
Kuivenhoven
JA
,
Masana
L
,
Nordestgaard
BG
,
Pajukanta
P
,
Parhofer
KG
,
Raal
FJ
,
Ray
KK
,
Santos
RD
,
Stalenhoef
AF
,
Steinhagen-Thiessen
E
,
Stroes
ES
,
Taskinen
MR
,
Tybjaerg-Hansen
A
,
Wiklund
O
; European Atherosclerosis Society Consensus Panel.
Familial hypercholesterolaemia in children and adolescents: gaining decades of
life by optimizing detection and treatment
.
Eur Heart J
2015
;
36
:
2425
–
2437
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
370

Braamskamp
M
,
Langslet
G
,
McCrindle
BW
,
Cassiman
D
,
Francis
GA
,
Gagne
C
,
Gaudet
D
,
Morrison
KM
,
Wiegman
A
,
Turner
T
,
Miller
E
,
Kusters
DM
,
Raichlen
JS
,
Martin
PD
,
Stein
EA
,
Kastelein
JJP
,
Hutten
BA.
Effect of rosuvastatin on carotid intima-media thickness in children with
heterozygous familial hypercholesterolemia: the CHARON study
(Hypercholesterolemia in Children and Adolescents Taking Rosuvastatin Open
Label)
.
Circulation
2017
;
136
:
359
–
366
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
371

Vuorio
A
,
Kuoppala
J
,
Kovanen
PT
,
Humphries
SE
,
Tonstad
S
,
Wiegman
A
,
Drogari
E
,
U
Ramaswami
.
Statins for children with familial hypercholesterolemia
.
Cochrane Database Syst Rev
2017
;
7
:
CD006401
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
372

Reiner
Z.
Treatment of children with homozygous familial hypercholesterolaemia
.
Eur J Prev Cardiol
2018
;
25
:
1095
–
1097
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
373

Koopal
C
,
Marais
AD
,
Visseren
FL.
Familial dysbetalipoproteinemia: an underdiagnosed lipid disorder
.
Curr Opin Endocrinol Diabetes Obes
2017
;
24
:
133
–
139
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
374

Mahley
RW
,
Weisgraber
KH
,
Huang
Y.
Apolipoprotein E: structure determines function, from atherosclerosis to
Alzheimer's disease to AIDS
.
J Lipid Res
2009
;
50
:
S183
–
S188
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
375

Marais
D.
Dysbetalipoproteinemia: an extreme disorder of remnant metabolism
.
Curr Opin Lipidol
2015
;
26
:
292
–
297
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
376

Sniderman
A
,
Couture
P
,
de Graaf
J.
Diagnosis and treatment of apolipoprotein B dyslipoproteinemias
.
Nat Rev Endocrinol
2010
;
6
:
335
–
346
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
377

Brahm
AJ
,
Hegele
RA.
Chylomicronaemia--current diagnosis and future therapies
.
Nat Rev Endocrinol
2015
;
11
:
352
–
362
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
378

Bauer
RC
,
Khetarpal
SA
,
Hand
NJ
,
Rader
DJ.
Therapeutic targets of triglyceride metabolism as informed by human genetics
.
Trends Mol Med
2016
;
22
:
328
–
340
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
379

Gaudet
D
,
Methot
J
,
Dery
S
,
Brisson
D
,
Essiembre
C
,
Tremblay
G
,
Tremblay
K
,
de Wal
J
,
Twisk
J
,
van den Bulk
N
,
Sier-Ferreira
V
,
van Deventer
S.
Efficacy and long-term safety of alipogene tiparvovec (AAV1-LPLS447X) gene
therapy for lipoprotein lipase deficiency: an open-label trial
.
Gene Ther
2013
;
20
:
361
–
369
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
380

Huff
MW
,
Hegele
RA.
Apolipoprotein C-III: going back to the future for a lipid drug target
.
Circ Res
2013
;
112
:
1405
–
1408
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
381

Moulin
P
,
Dufour
R
,
Averna
M
,
Arca
M
,
Cefalu
AB
,
Noto
D
,
D'Erasmo
L
,
Di Costanzo
A
,
Marcais
C
,
Alvarez-Sala Walther
LA
,
Banach
M
,
Boren
J
,
Cramb
R
,
Gouni-Berthold
I
,
Hughes
E
,
Johnson
C
,
Pinto
X
,
Reiner
Z
,
van Lennep
JR
,
Soran
H
,
Stefanutti
C
,
Stroes
E
,
Bruckert
E.
Identification and diagnosis of patients with familial chylomicronaemia syndrome
(FCS): expert panel recommendations and proposal of an "FCS score".
Atherosclerosis
2018
;
275
:
265
–
272
.




Crossref
Search ADS

PubMed
 
382

Meyers
CD
,
Tremblay
K
,
Amer
A
,
Chen
J
,
Jiang
L
,
Gaudet
D.
Effect of the DGAT1 inhibitor pradigastat on triglyceride and apoB48 levels in
patients with familial chylomicronemia syndrome
.
Lipids Health Dis
2015
;
14
:
8
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
383

Lindkvist
B
,
Appelros
S
,
Regner
S
,
Manjer
J.
A prospective cohort study on risk of acute pancreatitis related to serum
triglycerides, cholesterol and fasting glucose
.
Pancreatology
2012
;
12
:
317
–
324
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
384

Ewald
N
,
Hardt
PD
,
Kloer
HU.
Severe hypertriglyceridemia and pancreatitis: presentation and management
.
Curr Opin Lipidol
2009
;
20
:
497
–
504
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
385

Chora
JR
,
Alves
AC
,
Medeiros
AM
,
Mariano
C
,
Lobarinhas
G
,
Guerra
A
,
Mansilha
H
,
Cortez-Pinto
H
,
Bourbon
M.
Lysosomal acid lipase deficiency: a hidden disease among cohorts of familial
hypercholesterolemia?
J Clin Lipidol
2017
;
11
:
477
–
484.e2
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
386

Burton
BK
,
Balwani
M
,
Feillet
F
,
Baric
I
,
Burrow
TA
,
Camarena Grande
C
,
Coker
M
,
Consuelo-Sanchez
A
,
Deegan
P
,
Di Rocco
M
,
Enns
GM
,
Erbe
R
,
Ezgu
F
,
Ficicioglu
C
,
Furuya
KN
,
Kane
J
,
Laukaitis
C
,
Mengel
E
,
Neilan
EG
,
Nightingale
S
,
Peters
H
,
Scarpa
M
,
Schwab
KO
,
Smolka
V
,
Valayannopoulos
V
,
Wood
M
,
Goodman
Z
,
Yang
Y
,
Eckert
S
,
Rojas-Caro
S
,
Quinn
AG.
A phase 3 trial of sebelipase alfa in lysosomal acid lipase deficiency
.
N Engl J Med
2015
;
373
:
1010
–
1020
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
387

Hague
W
,
Forder
P
,
Simes
J
,
Hunt
D
,
Tonkin
A
; LIPID Investigators.
Effect of pravastatin on cardiovascular events and mortality in 1516 women with
coronary heart disease: results from the Long-Term Intervention with Pravastatin
in Ischemic Disease (LIPID) study
.
Am Heart J
2003
;
145
:
643
–
651
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
388

Miettinen
TA
,
Pyorala
K
,
Olsson
AG
,
Musliner
TA
,
Cook
TJ
,
Faergeman
O
,
Berg
K
,
Pedersen
T
,
Kjekshus
J.
Cholesterol-lowering therapy in women and elderly patients with myocardial
infarction or angina pectoris: findings from the Scandinavian Simvastatin
Survival Study (4S)
.
Circulation
1997
;
96
:
4211
–
4218
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
389

d'Emden
MC
,
Jenkins
AJ
,
Li
L
,
Zannino
D
,
Mann
KP
,
Best
JD
,
Stuckey
BG
,
Park
K
,
Saltevo
J
,
Keech
AC
; FIELD Study Investigators.
Favourable effects of fenofibrate on lipids and cardiovascular disease in women
with type 2 diabetes: results from the Fenofibrate Intervention and Event
Lowering in Diabetes (FIELD) study
.
Diabetologia
2014
;
57
:
2296
–
2303
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
390

Spitzer
WO
,
Faith
JM
,
MacRae
KD.
Myocardial infarction and third generation oral contraceptives: aggregation of
recent studies
.
Hum Reprod
2002
;
17
:
2307
–
2314
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
391

Shufelt
CL
,
Bairey Merz
CN.
Contraceptive hormone use and cardiovascular disease
.
J Am Coll Cardiol
2009
;
53
:
221
–
231
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
392

Manson
JE
,
Hsia
J
,
Johnson
KC
,
Rossouw
JE
,
Assaf
AR
,
Lasser
NL
,
Trevisan
M
,
Black
HR
,
Heckbert
SR
,
Detrano
R
,
Strickland
OL
,
Wong
ND
,
Crouse
JR
,
Stein
E
,
Cushman
M
; Women's Health Initiative Investigators.
Estrogen plus progestin and the risk of coronary heart disease
.
N Engl J Med
2003
;
349
:
523
–
534
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
393

Rosengren
A.
Better treatment and improved prognosis in elderly patients with AMI: but do
registers tell the whole truth?
Eur Heart J
2012
;
33
:
562
–
563
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
394

Second Joint Task Force of European and other Societies.

Prevention of coronary heart disease in clinical practice. Recommendations of
the Second Joint Task Force of European and other Societies on coronary
prevention
.
Eur Heart J
1998
;
19
:
1434
–
1503
.




Crossref
Search ADS

PubMed

WorldCat

 
395

Koopman
C
,
Vaartjes
I
,
Heintjes
EM
,
Spiering
W
,
van Dis
I
,
Herings
RM
,
Bots
ML.
Persisting gender differences and attenuating age differences in cardiovascular
drug use for prevention and treatment of coronary heart disease, 1998-2010
.
Eur Heart J
2013
;
34
:
3198
–
3205
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
396

Salami
JA
,
Warraich
H
,
Valero-Elizondo
J
,
Spatz
ES
,
Desai
NR
,
Rana
JS
,
Virani
SS
,
Blankstein
R
,
Khera
A
,
Blaha
MJ
,
Blumenthal
RS
,
Lloyd-Jones
D
,
Nasir
K.
National trends in statin use and expenditures in the US adult population from
2002 to 2013: insights from the medical expenditure panel survey
.
JAMA Cardiol
2017
;
2
:
56
–
65
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
397

Strandberg
TE
,
Kolehmainen
L
,
Vuorio
A.
Evaluation and treatment of older patients with hypercholesterolemia: a clinical
review
.
JAMA
2014
;
312
:
1136
–
1144
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
398

Mangin
D
,
Sweeney
K
,
Heath
I.
Preventive health care in elderly people needs rethinking
.
BMJ
2007
;
335
:
285
–
287
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
399

Zimmet
PZ.
Diabetes and its drivers: the largest epidemic in human history?
Clin Diabetes Endocrinol
2017
;
3
:
1
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
400

Rawshani
A
,
Rawshani
A
,
Franzen
S
,
Eliasson
B
,
Svensson
AM
,
Miftaraj
M
,
McGuire
DK
,
Sattar
N
,
Rosengren
A
,
Gudbjornsdottir
S.
Mortality and cardiovascular disease in type 1 and type 2 diabetes
.
N Engl J Med
2017
;
376
:
1407
–
1418
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
401

Olesen
KKW
,
Madsen
M
,
Egholm
G
,
Thim
T
,
Jensen
LO
,
Raungaard
B
,
Botker
HE
,
Sorensen
HT
,
Maeng
M.
Patients with diabetes without significant angiographic coronary artery disease
have the same risk of myocardial infarction as patients without diabetes in a
real-world population receiving appropriate prophylactic treatment
.
Diabetes Care
2017
;
40
:
1103
–
1110
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
402

Emerging Risk Factors Collaboration,

Sarwar
N
,
Gao
P
,
Seshasai
SR
,
Gobin
R
,
Kaptoge
S
,
Di Angelantonio
E
,
Ingelsson
E
,
Lawlor
DA
,
Selvin
E
,
Stampfer
M
,
Stehouwer
CD
,
Lewington
S
,
Pennells
L
,
Thompson
A
,
Sattar
N
,
White
IR
,
Ray
KK
,
Danesh
J.
Diabetes mellitus, fasting blood glucose concentration, and risk of vascular
disease: a collaborative meta-analysis of 102 prospective studies
.
Lancet
2010
;
375
:
2215
–
2222
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
403

Gregg
EW
,
Li
Y
,
Wang
J
,
Burrows
NR
,
Ali
MK
,
Rolka
D
,
Williams
DE
,
Geiss
L.
Changes in diabetes-related complications in the United States, 1990-2010
.
N Engl J Med
2014
;
370
:
1514
–
1523
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
404

Sattar
N.
Revisiting the links between glycaemia, diabetes and cardiovascular disease
.
Diabetologia
2013
;
56
:
686
–
695
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
405

Brownrigg
JR
,
Hughes
CO
,
Burleigh
D
,
Karthikesalingam
A
,
Patterson
BO
,
Holt
PJ
,
Thompson
MM
,
de Lusignan
S
,
Ray
KK
,
Hinchliffe
RJ.
Microvascular disease and risk of cardiovascular events among individuals with
type 2 diabetes: a population-level cohort study
.
Lancet Diabetes Endocrinol
2016
;
4
:
588
–
597
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
406

Despres
JP.
Body fat distribution and risk of cardiovascular disease: an update
.
Circulation
2012
;
126
:
1301
–
1313
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
407

Targher
G.
Non-alcoholic fatty liver disease as driving force in coronary heart disease?
Gut
2017
;
66
:
213
–
214
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
408

Targher
G
,
Lonardo
A
,
Byrne
CD.
Nonalcoholic fatty liver disease and chronic vascular complications of diabetes
mellitus
.
Nat Rev Endocrinol
2018
;
14
:
99
–
114
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
409

Donahoe
SM
,
Stewart
GC
,
McCabe
CH
,
Mohanavelu
S
,
Murphy
SA
,
Cannon
CP
,
Antman
EM.
Diabetes and mortality following acute coronary syndromes
.
JAMA
2007
;
298
:
765
–
775
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
410

Levesque
V
,
Poirier
P
,
Despres
JP
,
Almeras
N.
Relation between a simple lifestyle risk score and established biological risk
factors for cardiovascular disease
.
Am J Cardiol
2017
;
120
:
1939
–
1946
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
411

Taskinen
MR
,
Boren
J.
New insights into the pathophysiology of dyslipidemia in type 2 diabetes
.
Atherosclerosis
2015
;
239
:
483
–
495
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
412

Taskinen
MR
,
Boren
J.
Why is apolipoprotein CIII emerging as a novel therapeutic target to reduce the
burden of cardiovascular disease?
Curr Atheroscler Rep
2016
;
18
:
59
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
413

Boren
J
,
Watts
GF
,
Adiels
M
,
Soderlund
S
,
Chan
DC
,
Hakkarainen
A
,
Lundbom
N
,
Matikainen
N
,
Kahri
J
,
Verges
B
,
Barrett
PH
,
Taskinen
MR.
Kinetic and related determinants of plasma triglyceride concentration in
abdominal obesity: multicenter tracer kinetic study
.
Arterioscler Thromb Vasc Biol
2015
;
35
:
2218
–
2224
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
414

Gordts
PL
,
Nock
R
,
Son
NH
,
Ramms
B
,
Lew
I
,
Gonzales
JC
,
Thacker
BE
,
Basu
D
,
Lee
RG
,
Mullick
AE
,
Graham
MJ
,
Goldberg
IJ
,
Crooke
RM
,
Witztum
JL
,
Esko
JD.
ApoC-III inhibits clearance of triglyceride-rich lipoproteins through LDL family
receptors
.
J Clin Invest
2016
;
126
:
2855
–
2866
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
415

Mark
L
,
Vallejo-Vaz
AJ
,
Reiber
I
,
Paragh
G
,
Kondapally Seshasai
SR
,
Ray
KK.
Non-HDL cholesterol goal attainment and its relationship with triglyceride
concentrations among diabetic subjects with cardiovascular disease: a nationwide
survey of 2674 individuals in Hungary
.
Atherosclerosis
2015
;
241
:
62
–
68
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
416

Scott
R
,
O'Brien
R
,
Fulcher
G
,
Pardy
C
,
D'Emden
M
,
Tse
D
,
Taskinen
MR
,
Ehnholm
C
,
Keech
A
; Fenofibrate Intervention Event Lowering in Diabetes (FIELD) Study
Investigators.
Effects of fenofibrate treatment on cardiovascular disease risk in 9,795
individuals with type 2 diabetes and various components of the metabolic
syndrome: the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD)
study
.
Diabetes Care
2009
;
32
:
493
–
498
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
417

Annuzzi
G
,
Giacco
R
,
Patti
L
,
Di Marino
L
,
De Natale
C
,
Costabile
G
,
Marra
M
,
Santangelo
C
,
Masella
R
,
Rivellese
AA.
Postprandial chylomicrons and adipose tissue lipoprotein lipase are altered in
type 2 diabetes independently of obesity and whole-body insulin resistance
.
Nutr Metab Cardiovasc Dis
2008
;
18
:
531
–
538
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
418

Cholesterol Treatment Trialists Collaboration,

Kearney
PM
,
Blackwell
L
,
Collins
R
,
Keech
A
,
Simes
J
,
Peto
R
,
Armitage
J
,
Baigent
C.
Efficacy of cholesterol-lowering therapy in 18,686 people with diabetes in 14
randomised trials of statins: a meta-analysis
.
Lancet
2008
;
371
:
117
–
125
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
419

American Diabetes Association.

Cardiovascular disease and risk management: standards of medical care in
diabetes-2018
.
Diabetes Care
2018
;
41
:
S86
–
S104
.




Crossref
Search ADS

PubMed

WorldCat

 
420

Ray
KK
,
Colhoun
HM
,
Szarek
M
,
Baccara-Dinet
M
,
Bhatt
DL
,
Bittner
VA
,
Budaj
AJ
,
Diaz
R
,
Goodman
SG
,
Hanotin
C
,
Harrington
RA
,
Jukema
JW
,
Loizeau
V
,
Lopes
RD
,
Moryusef
A
,
Murin
J
,
Pordy
R
,
Ristic
AD
,
Roe
MT
,
Tuñón
J
,
White
HD
,
Zeiher
AM
,
Schwartz
GG
,
Steg
G
; ODYSSEY OUTCOMES Committees and Investigators.
Effects of alirocumab on cardiovascular and metabolic outcomes after acute
coronary syndrome in patients with or without diabetes: a prespecified analysis
of the ODYSSEY OUTCOMES randomised controlled trial
.
Lancet Diabetes Endocrinol
2019
; pii: S2213-8587(19)30158-5. doi: 10.1016/S2213-8587(19)30158-5. [Epub ahead of
print] Erratum in: Lancet Diabetes Endocrinol. 2019 July 8.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
421

Elam
MB
,
Ginsberg
HN
,
Lovato
LC
,
Corson
M
,
Largay
J
,
Leiter
LA
,
Lopez
C
,
O'Connor
PJ
,
Sweeney
ME
,
Weiss
D
,
Friedewald
WT
,
Buse
JB
,
Gerstein
HC
,
Probstfield
J
,
Grimm
R
,
Ismail-Beigi
F
,
Goff
DC
Jr,
Fleg
JL
,
Rosenberg
Y
,
Byington
RP
; ACCORDION Study Investigators.
Association of fenofibrate therapy with long-term cardiovascular risk in
statin-treated patients with type 2 diabetes
.
JAMA Cardiol
2017
;
2
:
370
–
380
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
422

Saha
SA
,
Arora
RR.
Fibrates in the prevention of cardiovascular disease in patients with type 2
diabetes mellitus--a pooled meta-analysis of randomized placebo-controlled
clinical trials
.
Int J Cardiol
2010
;
141
:
157
–
166
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
423

Araki
E
,
Yamashita
S
,
Arai
H
,
Yokote
K
,
Satoh
J
,
Inoguchi
T
,
Nakamura
J
,
Maegawa
H
,
Yoshioka
N
,
Tanizawa
Y
,
Watada
H
,
Suganami
H
,
Ishibashi
S.
Effects of pemafibrate, a novel selective PPARalpha modulator, on lipid and
glucose metabolism in patients with type 2 diabetes and hypertriglyceridemia: a
randomized, double-blind, placebo-controlled, phase 3 trial
.
Diabetes Care
2018
;
41
:
538
–
546
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
424

Arca
M
,
Borghi
C
,
Pontremoli
R
,
De Ferrari
GM
,
Colivicchi
F
,
Desideri
G
,
Temporelli
PL.
Hypertriglyceridemia and omega-3 fatty acids: their often overlooked role in
cardiovascular disease prevention
.
Nutr Metab Cardiovasc Dis
2018
;
28
:
197
–
205
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
425

Bhatt
DL
,
Steg
PG
,
Brinton
EA
,
Jacobson
TA
,
Miller
M
,
Tardif
JC
,
Ketchum
SB
,
Doyle
RT
Jr,
Murphy
SA
,
Soni
PN
,
Braeckman
RA
,
Juliano
RA
,
Ballantyne
CM
; REDUCE-IT Investigators.
Rationale and design of REDUCE-IT: Reduction of Cardiovascular Events with
Icosapent Ethyl-Intervention Trial
.
Clin Cardiol
2017
;
40
:
138
–
148
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
426

ASCEND Study Collaborative Group,

Bowman
L
,
Mafham
M
,
Wallendszus
K
,
Stevens
W
,
Buck
G
,
Barton
J
,
Murphy
K
,
Aung
T
,
Haynes
R
,
Cox
J
,
Murawska
A
,
Young
A
,
Lay
M
,
Chen
F
,
Sammons
E
,
Waters
E
,
Adler
A
,
Bodansky
J
,
Farmer
A
,
McPherson
R
,
Neil
A
,
Simpson
D
,
Peto
R
,
Baigent
C
,
Collins
R
,
Parish
S
,
Armitage
J.
Effects of aspirin for primary prevention in persons with diabetes mellitus
.
N Engl J Med
2018
;
379
:
1529
–
1539
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
427

Laing
SP
,
Swerdlow
AJ
,
Slater
SD
,
Burden
AC
,
Morris
A
,
Waugh
NR
,
Gatling
W
,
Bingley
PJ
,
Patterson
CC.
Mortality from heart disease in a cohort of 23,000 patients with insulin-treated
diabetes
.
Diabetologia
2003
;
46
:
760
–
765
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
428

Chillaron
JJ
,
Flores Le-Roux
JA
,
Benaiges
D
,
Pedro-Botet
J.
Type 1 diabetes, metabolic syndrome and cardiovascular risk
.
Metabolism
2014
;
63
:
181
–
187
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
429

Annuzzi
G
,
Iovine
C
,
Mandarino
B
,
Patti
L
,
Di Marino
L
,
Riccardi
G
,
Rivellese
AA.
Effect of acute exogenous hyperinsulinaemia on very low density lipoprotein
subfraction composition in normal subjects
.
Eur J Clin Invest
2001
;
31
:
118
–
124
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
430

Cannon
CP
,
Steinberg
BA
,
Murphy
SA
,
Mega
JL
,
Braunwald
E.
Meta-analysis of cardiovascular outcomes trials comparing intensive versus
moderate statin therapy
.
J Am Coll Cardiol
2006
;
48
:
438
–
445
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
431

Mills
EJ
,
O'Regan
C
,
Eyawo
O
,
Wu
P
,
Mills
F
,
Berwanger
O
,
Briel
M.
Intensive statin therapy compared with moderate dosing for prevention of
cardiovascular events: a meta-analysis of >40 000 patients
.
Eur Heart J
2011
;
32
:
1409
–
1415
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
432

Nicholls
SJ
,
Tuzcu
EM
,
Kalidindi
S
,
Wolski
K
,
Moon
KW
,
Sipahi
I
,
Schoenhagen
P
,
Nissen
SE.
Effect of diabetes on progression of coronary atherosclerosis and arterial
remodeling: a pooled analysis of 5 intravascular ultrasound trials
.
J Am Coll Cardiol
2008
;
52
:
255
–
262
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
433

Karalis
DG
,
Hill
AN
,
Clifton
S
,
Wild
RA.
The risks of statin use in pregnancy: a systematic review
.
J Clin Lipidol
2016
;
10
:
1081
–
1090
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
434

Gencer
B
,
Koskinas
KC
,
Räber
L
,
Karagiannis
A
,
Nanchen
D
,
Auer
R
,
Carballo
D
,
Carballo
S
,
Klingenberg
R
,
Heg
D
,
Matter
CM
,
Lüscher
TF
,
Rodondi
N
,
Mach
F
,
Windecker
S.
Eligibility for PCSK9 inhibitors according to American College of Cardiology
(ACC) and European Society of Cardiology/European Atherosclerosis Society
(ESC/EAS) guidelines after acute coronary syndromes
.
J Am Heart Assoc
2017
;
6
:
e006537
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
435

Kureshi
F
,
Kennedy
KF
,
Jones
PG
,
Thomas
RJ
,
Arnold
SV
,
Sharma
P
,
Fendler
T
,
Buchanan
DM
,
Qintar
M
,
Ho
PM
,
Nallamothu
BK
,
Oldridge
NB
,
Spertus
JA.
Association between cardiac rehabilitation participation and health status
outcomes after acute myocardial infarction
.
JAMA Cardiol
2016
;
1
:
980
–
988
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
436

Szummer
K
,
Wallentin
L
,
Lindhagen
L
,
Alfredsson
J
,
Erlinge
D
,
Held
C
,
James
S
,
Kellerth
T
,
Lindahl
B
,
Ravn-Fischer
A
,
Rydberg
E
,
Yndigegn
T
,
Jernberg
T.
Improved outcomes in patients with ST-elevation myocardial infarction during the
last 20 years are related to implementation of evidence-based treatments:
experiences from the SWEDEHEART registry 1995-2014
.
Eur Heart J
2017
;
38
:
3056
–
3065
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
437

Gitt
AK
,
Lautsch
D
,
Ferrieres
J
,
De Ferrari
GM
,
Vyas
A
,
Baxter
CA
,
Bash
LD
,
Ashton
V
,
Horack
M
,
Almahmeed
W
,
Chiang
FT
,
Poh
KK
,
Brudi
P
,
Ambegaonkar
B.
Cholesterol target value attainment and lipid-lowering therapy in patients with
stable or acute coronary heart disease: results from the Dyslipidemia
International Study II
.
Atherosclerosis
2017
;
266
:
158
–
166
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
438

de Lemos
JA
,
Blazing
MA
,
Wiviott
SD
,
Lewis
EF
,
Fox
KA
,
White
HD
,
Rouleau
JL
,
Pedersen
TR
,
Gardner
LH
,
Mukherjee
R
,
Ramsey
KE
,
Palmisano
J
,
Bilheimer
DW
,
Pfeffer
MA
,
Califf
RM
,
Braunwald
E
; for the A to Z Investigators.
Early intensive vs a delayed conservative simvastatin strategy in patients with
acute coronary syndromes: phase Z of the A to Z trial
.
JAMA
2004
;
292
:
1307
–
1316
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
439

Navarese
EP
,
Kowalewski
M
,
Andreotti
F
,
van Wely
M
,
Camaro
C
,
Kolodziejczak
M
,
Gorny
B
,
Wirianta
J
,
Kubica
J
,
Kelm
M
,
de Boer
MJ
,
Suryapranata
H.
Meta-analysis of time-related benefits of statin therapy in patients with acute
coronary syndrome undergoing percutaneous coronary intervention
.
Am J Cardiol
2014
;
113
:
1753
–
1764
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
440

Ray
KK
,
Cannon
CP
,
McCabe
CH
,
Cairns
R
,
Tonkin
AM
,
Sacks
FM
,
Jackson
G
,
Braunwald
E
; PROVE IT-TIMI 22 Investigators.
Early and late benefits of high-dose atorvastatin in patients with acute
coronary syndromes: results from the PROVE IT-TIMI 22 trial
.
J Am Coll Cardiol
2005
;
46
:
1405
–
1410
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
441

Schwartz
GG
,
Fayyad
R
,
Szarek
M
,
DeMicco
D
,
Olsson
AG.
Early, intensive statin treatment reduces ‘hard’ cardiovascular outcomes after
acute coronary syndrome
.
Eur J Prev Cardiol
2017
;
24
:
1294
–
1296
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
442

Schwartz
GG
,
Olsson
AG
,
Ezekowitz
MD
,
Ganz
P
,
Oliver
MF
,
Waters
D
,
Zeiher
A
,
Chaitman
BR
,
Leslie
S
,
Stern
T
; Myocardial Ischemia Reduction with Aggressive Cholesterol Lowering (MIRACL)
Study Investigators.
Effects of atorvastatin on early recurrent ischemic events in acute coronary
syndromes: the MIRACL study: a randomized controlled trial
.
JAMA
2001
;
285
:
1711
–
1718
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
443

Berwanger
O
,
Santucci
EV
,
de Barros
ESPGM
,
Jesuino
IA
,
Damiani
LP
,
Barbosa
LM
,
Santos
RHN
,
Laranjeira
LN
,
Egydio
FM
,
Borges de Oliveira
JA
,
Dall Orto
FTC
,
Beraldo de Andrade
P
,
Bienert
IRC
,
Bosso
CE
,
Mangione
JA
,
Polanczyk
CA
,
Sousa
A
,
Kalil
RAK
,
Santos
LM
,
Sposito
AC
,
Rech
RL
,
Sousa
ACS
,
Baldissera
F
,
Nascimento
BR
,
Giraldez
R
,
Cavalcanti
AB
,
Pereira
SB
,
Mattos
LA
,
Armaganijan
LV
,
Guimaraes
HP
,
Sousa
J
,
Alexander
JH
,
Granger
CB
,
Lopes
RD
; SECURE-PCI Investigators.
Effect of loading dose of atorvastatin prior to planned percutaneous coronary
intervention on major adverse cardiovascular events in acute coronary syndrome:
the SECURE-PCI randomized clinical trial
.
JAMA
2018
;
319
:
1331
–
1340
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
444

Kato
ET
,
Cannon
CP
,
Blazing
MA
,
Bohula
E
,
Guneri
S
,
White
JA
,
Murphy
SA
,
Park
JG
,
Braunwald
E
,
Giugliano
RP.
Efficacy and safety of adding ezetimibe to statin therapy among women and men:
insight from IMPROVE-IT (Improved Reduction of Outcomes: Vytorin Efficacy
International Trial)
.
J Am Heart Assoc
2017
;
6
:
e006901
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
445

Murphy
SA
,
Cannon
CP
,
Blazing
MA
,
Giugliano
RP
,
White
JA
,
Lokhnygina
Y
,
Reist
C
,
Im
K
,
Bohula
EA
,
Isaza
D
,
Lopez-Sendon
J
,
Dellborg
M
,
Kher
U
,
Tershakovec
AM
,
Braunwald
E.
Reduction in total cardiovascular events with ezetimibe/simvastatin post-acute
coronary syndrome: the IMPROVE-IT trial
.
J Am Coll Cardiol
2016
;
67
:
353
–
361
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
446

Bohula
EA
,
Wiviott
SD
,
Giugliano
RP
,
Blazing
MA
,
Park
JG
,
Murphy
SA
,
White
JA
,
Mach
F
,
Van de Werf
F
,
Dalby
AJ
,
White
HD
,
Tershakovec
AM
,
Cannon
CP
,
Braunwald
E.
Prevention of stroke with the addition of ezetimibe to statin therapy in
patients with acute coronary syndrome in IMPROVE-IT (Improved Reduction of
Outcomes: Vytorin Efficacy International Trial)
.
Circulation
2017
;
136
:
2440
–
2450
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
447

Pokharel
Y
,
Chinnakondepalli
K
,
Vilain
K
,
Wang
K
,
Mark
DB
,
Davies
G
,
Blazing
MA
,
Giugliano
RP
,
Braunwald
E
,
Cannon
CP
,
Cohen
DJ
,
Magnuson
EA.
Impact of ezetimibe on the rate of cardiovascular-related hospitalizations and
associated costs among patients with a recent acute coronary syndrome: results
from the IMPROVE-IT trial (Improved Reduction of Outcomes: Vytorin Efficacy
International Trial)
.
Circ Cardiovasc Qual Outcomes
2017
;
10
:
e003201
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
448

Bohula
EA
,
Morrow
DA
,
Giugliano
RP
,
Blazing
MA
,
He
P
,
Park
JG
,
Murphy
SA
,
White
JA
,
Kesaniemi
YA
,
Pedersen
TR
,
Brady
AJ
,
Mitchel
Y
,
Cannon
CP
,
Braunwald
E.
Atherothrombotic risk stratification and ezetimibe for secondary prevention
.
J Am Coll Cardiol
2017
;
69
:
911
–
921
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
449

Hagiwara
N
,
Kawada-Watanabe
E
,
Koyanagi
R
,
Arashi
H
,
Yamaguchi
J
,
Nakao
K
,
Tobaru
T
,
Tanaka
H
,
Oka
T
,
Endoh
Y
,
Saito
K
,
Uchida
T
,
Matsui
K
,
Ogawa
H.
Low-density lipoprotein cholesterol targeting with pitavastatin + ezetimibe for
patients with acute coronary syndrome and dyslipidaemia: the HIJ-PROPER study, a
prospective, open-label, randomized trial
.
Eur Heart J
2017
;
38
:
2264
–
2276
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
450

Sabatine
MS
,
De Ferrari
GM
,
Giugliano
RP
,
Huber
K
,
Lewis
BS
,
Ferreira
J
,
Kuder
JF
,
Murphy
SA
,
Wiviott
SD
,
Kurtz
CE
,
Honarpour
N
,
Keech
AC
,
Sever
PS
,
Pedersen
TR.
Clinical benefit of evolocumab by severity and extent of coronary artery disease
.
Circulation
2018
;
138
:
756
–
766
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
451

Giugliano
RP
,
Pedersen
TR
,
Park
JG
,
De Ferrari
GM
,
Gaciong
ZA
,
Ceska
R
,
Toth
K
,
Gouni-Berthold
I
,
Lopez-Miranda
J
,
Schiele
F
,
Mach
F
,
Ott
BR
,
Kanevsky
E
,
Pineda
AL
,
Somaratne
R
,
Wasserman
SM
,
Keech
AC
,
Sever
PS
,
Sabatine
MS
; FOURIER Investigators.
Clinical efficacy and safety of achieving very low LDL-cholesterol
concentrations with the PCSK9 inhibitor evolocumab: a prespecified secondary
analysis of the FOURIER trial
.
Lancet
2017
;
390
:
1962
–
1971
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
452

Koskinas
KC
,
Windecker
S
,
Buhayer
A
,
Gencer
B
,
Pedrazzini
G
,
Mueller
C
,
Cook
S
,
Muller
O
,
Matter
CM
,
Raber
L
,
Heg
D
,
Mach
F
; EVOPACS Investigators.
Design of the randomized, placebo-controlled evolocumab for early reduction of
LDL-cholesterol levels in patients with acute coronary syndromes (EVOPACS) trial
.
Clin Cardiol
2018
;
41
:
1513
–
1520
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
453

Aung
T
,
Halsey
J
,
Kromhout
D
,
Gerstein
HC
,
Marchioli
R
,
Tavazzi
L
,
Geleijnse
JM
,
Rauch
B
,
Ness
A
,
Galan
P
,
Chew
EY
,
Bosch
J
,
Collins
R
,
Lewington
S
,
Armitage
J
,
Clarke
R
; Omega-3 Treatment Trialists' Collaboration.
Associations of omega-3 fatty acid supplement use with cardiovascular disease
risks: meta-analysis of 10 trials involving 77917 individuals
.
JAMA Cardiol
2018
;
3
:
225
–
234
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
454

Patti
G
,
Cannon
CP
,
Murphy
SA
,
Mega
S
,
Pasceri
V
,
Briguori
C
,
Colombo
A
,
Yun
KH
,
Jeong
MH
,
Kim
JS
,
Choi
D
,
Bozbas
H
,
Kinoshita
M
,
Fukuda
K
,
Jia
XW
,
Hara
H
,
Cay
S
,
Di Sciascio
G.
Clinical benefit of statin pretreatment in patients undergoing percutaneous
coronary intervention: a collaborative patient-level meta-analysis of 13
randomized studies
.
Circulation
2011
;
123
:
1622
–
1632
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
455

Kim
JS
,
Kim
J
,
Choi
D
,
Lee
CJ
,
Lee
SH
,
Ko
YG
,
Hong
MK
,
Kim
BK
,
Oh
SJ
,
Jeon
DW
,
Yang
JY
,
Cho
JR
,
Lee
NH
,
Cho
YH
,
Cho
DK
,
Jang
Y.
Efficacy of high-dose atorvastatin loading before primary percutaneous coronary
intervention in ST-segment elevation myocardial infarction: the STATIN STEMI
trial
.
JACC Cardiovasc Interv
2010
;
3
:
332
–
339
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
456

Briguori
C
,
Visconti
G
,
Focaccio
A
,
Golia
B
,
Chieffo
A
,
Castelli
A
,
Mussardo
M
,
Montorfano
M
,
Ricciardelli
B
,
Colombo
A.
Novel approaches for preventing or limiting events (Naples) II trial: impact of
a single high loading dose of atorvastatin on periprocedural myocardial
infarction
.
J Am Coll Cardiol
2009
;
54
:
2157
–
2163
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
457

Di Sciascio
G
,
Patti
G
,
Pasceri
V
,
Gaspardone
A
,
Colonna
G
,
Montinaro
A.
Efficacy of atorvastatin reload in patients on chronic statin therapy undergoing
percutaneous coronary intervention: results of the ARMYDA-RECAPTURE
(Atorvastatin for Reduction of Myocardial Damage During Angioplasty) randomized
trial
.
J Am Coll Cardiol
2009
;
54
:
558
–
565
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
458

Navarese
EP
,
Gurbel
PA
,
Andreotti
F
,
Kołodziejczak
MM
,
Palmer
SC
,
Dias
S
,
Buffon
A
,
Kubica
J
,
Kowalewski
M
,
Jadczyk
T
,
Laskiewicz
M
,
Jędrzejek
M
,
Brockmeyer
M
,
Airoldi
F
,
Ruospo
M
,
De Servi
S
,
Wojakowski
W
,
O'Connor
C
,
Strippoli
GF.
Prevention of contrast-induced acute kidney injury in patients undergoing
cardiovascular procedures-a systematic review and network meta-analysis
.
PLoS One
2017
;
12
:
e0168726
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
459

Amarenco
P
,
Bogousslavsky
J
,
Callahan
A III
,
Goldstein
LB
,
Hennerici
M
,
Rudolph
AE
,
Sillesen
H
,
Simunovic
L
,
Szarek
M
,
Welch
KM
,
Zivin
JA
; Stroke Prevention by Aggressive Reduction in Cholesterol Levels (SPARCL)
Investigators.
High-dose atorvastatin after stroke or transient ischemic attack
.
N Engl J Med
2006
;
355
:
549
–
559
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
460

Amarenco
P
,
Labreuche
J.
Lipid management in the prevention of stroke: review and updated meta-analysis
of statins for stroke prevention
.
Lancet Neurol
2009
;
8
:
453
–
463
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
461

Merwick
A
,
Albers
GW
,
Arsava
EM
,
Ay
H
,
Calvet
D
,
Coutts
SB
,
Cucchiara
BL
,
Demchuk
AM
,
Giles
MF
,
Mas
JL
,
Olivot
JM
,
Purroy
F
,
Rothwell
PM
,
Saver
JL
,
Sharma
VK
,
Tsivgoulis
G
,
Kelly
PJ.
Reduction in early stroke risk in carotid stenosis with transient ischemic
attack associated with statin treatment
.
Stroke
2013
;
44
:
2814
–
2820
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
462

Flint
AC
,
Conell
C
,
Ren
X
,
Kamel
H
,
Chan
SL
,
Rao
VA
,
Johnston
SC.
Statin adherence is associated with reduced recurrent stroke risk in patients
with or without atrial fibrillation
.
Stroke
2017
;
48
:
1788
–
1794
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
463

The Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) Study
Group.

Prevention of cardiovascular events and death with pravastatin in patients with
coronary heart disease and a broad range of initial cholesterol levels. The
Long-Term Intervention with Pravastatin in Ischaemic Disease (LIPID) Study Group
.
N Engl J Med
1998
;
339
:
1349
–
1357
.




Crossref
Search ADS

PubMed

WorldCat

 
464

Kjekshus
J
,
Pedersen
TR
,
Olsson
AG
,
Faergeman
O
,
Pyorala
K.
The effects of simvastatin on the incidence of heart failure in patients with
coronary heart disease
.
J Card Fail
1997
;
3
:
249
–
254
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
465

Khush
KK
,
Waters
DD
,
Bittner
V
,
Deedwania
PC
,
Kastelein
JJ
,
Lewis
SJ
,
Wenger
NK.
Effect of high-dose atorvastatin on hospitalizations for heart failure: subgroup
analysis of the Treating to New Targets (TNT) study
.
Circulation
2007
;
115
:
576
–
583
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
466

Kjekshus
J
,
Apetrei
E
,
Barrios
V
,
Böhm
M
,
Cleland
JG
,
Cornel
JH
,
Dunselman
P
,
Fonseca
C
,
Goudev
A
,
Grande
P
,
Gullestad
L
,
Hjalmarson
A
,
Hradec
J
,
Jánosi
A
,
Kamenský
G
,
Komajda
M
,
Korewicki
J
,
Kuusi
T
,
Mach
F
,
Mareev
V
,
McMurray
JJ
,
Ranjith
N
,
Schaufelberger
M
,
Vanhaecke
J
,
van Veldhuisen
DJ
,
Waagstein
F
,
Wedel
H
,
Wikstrand
J
; CORONA Group.
Rosuvastatin in older patients with systolic heart failure
.
N Engl J Med
2007
;
357
:
2248
–
2261
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
467

Sacks
FM
,
Pfeffer
MA
,
Moye
LA
,
Rouleau
JL
,
Rutherford
JD
,
Cole
TG
,
Brown
L
,
Warnica
JW
,
Arnold
JM
,
Wun
CC
,
Davis
BR
,
Braunwald
E.
The effect of pravastatin on coronary events after myocardial infarction in
patients with average cholesterol levels. Cholesterol and Recurrent Events Trial
investigators
.
N Engl J Med
1996
;
335
:
1001
–
1009
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
468

Scirica
BM
,
Morrow
DA
,
Cannon
CP
,
Ray
KK
,
Sabatine
MS
,
Jarolim
P
,
Shui
A
,
McCabe
CH
,
Braunwald
E
; PROVE IT-TIMI 22 Investigators.
Intensive statin therapy and the risk of hospitalization for heart failure after
an acute coronary syndrome in the PROVE IT-TIMI 22 study
.
J Am Coll Cardiol
2006
;
47
:
2326
–
2331
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
469

Preiss
D
,
Campbell
RT
,
Murray
HM
,
Ford
I
,
Packard
CJ
,
Sattar
N
,
Rahimi
K
,
Colhoun
HM
,
Waters
DD
,
LaRosa
JC
,
Amarenco
P
,
Pedersen
TR
,
Tikkanen
MJ
,
Koren
MJ
,
Poulter
NR
,
Sever
PS
,
Ridker
PM
,
MacFadyen
JG
,
Solomon
SD
,
Davis
BR
,
Simpson
LM
,
Nakamura
H
,
Mizuno
K
,
Marfisi
RM
,
Marchioli
R
,
Tognoni
G
,
Athyros
VG
,
Ray
KK
,
Gotto
AM
,
Clearfield
MB
,
Downs
JR
,
McMurray
JJ.
The effect of statin therapy on heart failure events: a collaborative
meta-analysis of unpublished data from major randomized trials
.
Eur Heart J
2015
;
36
:
1536
–
1546
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
470

Tavazzi
L
,
Maggioni
AP
,
Marchioli
R
,
Barlera
S
,
Franzosi
MG
,
Latini
R
,
Lucci
D
,
Nicolosi
GL
,
Porcu
M
,
Tognoni
G
; GISSI-HF Investigators.
Effect of rosuvastatin in patients with chronic heart failure (the GISSI-HF
trial): a randomised, double-blind, placebo-controlled trial
.
Lancet
2008
;
372
:
1231
–
1239
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
471

Al-Gobari
M
,
Le
HH
,
Fall
M
,
Gueyffier
F
,
Burnand
B.
No benefits of statins for sudden cardiac death prevention in patients with
heart failure and reduced ejection fraction: a meta-analysis of randomized
controlled trials
.
PLoS One
2017
;
12
:
e0171168
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
472

Feinstein
MJ
,
Jhund
P
,
Kang
J
,
Ning
H
,
Maggioni
A
,
Wikstrand
J
,
Kjekshus
J
,
Tavazzi
L
,
McMurray
J
,
Lloyd-Jones
DM.
Do statins reduce the risk of myocardial infarction in patients with heart
failure? A pooled individual-level reanalysis of CORONA and GISSI-HF
.
Eur J Heart Fail
2015
;
17
:
434
–
441
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
473

Bayes-Genis
A
,
Nunez
J
,
Zannad
F
,
Ferreira
JP
,
Anker
SD
,
Cleland
JG
,
Dickstein
K
,
Filippatos
G
,
Lang
CC
,
Ng
LL
,
Ponikowski
P
,
Samani
NJ
,
van Veldhuisen
DJ
,
Zwinderman
AH
,
Metra
M
,
Lupon
J
,
Voors
AA.
The PCSK9-LDL receptor axis and outcomes in heart failure: BIOSTAT-CHF
subanalysis
.
J Am Coll Cardiol
2017
;
70
:
2128
–
2136
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
474

Francis
GS.
Cholesterol and heart failure: is there an important connection?
J Am Coll Cardiol
2017
;
70
:
2137
–
2138
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
475

Tavazzi
L
,
Maggioni
AP
,
Marchioli
R
,
Barlera
S
,
Franzosi
MG
,
Latini
R
,
Lucci
D
,
Nicolosi
GL
,
Porcu
M
,
Tognoni
G
; GISSI-HF Investigators.
Effect of n-3 polyunsaturated fatty acids in patients with chronic heart failure
(the GISSI-HF trial): a randomised, double-blind, placebo-controlled trial
.
Lancet
2008
;
372
:
1223
–
1230
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
476

Smith
JG
,
Luk
K
,
Schulz
CA
,
Engert
JC
,
Do
R
,
Hindy
G
,
Rukh
G
,
Dufresne
L
,
Almgren
P
,
Owens
DS
,
Harris
TB
,
Peloso
GM
,
Kerr
KF
,
Wong
Q
,
Smith
AV
,
Budoff
MJ
,
Rotter
JI
,
Cupples
LA
,
Rich
S
,
Kathiresan
S
,
Orho-Melander
M
,
Gudnason
V
,
O'Donnell
CJ
,
Post
WS
,
Thanassoulis
G
; Cohorts for Heart and Aging Research in Genetic Epidemiology (CGARGE)
Extracoronary Calcium Working Group.
Association of low-density lipoprotein cholesterol-related genetic variants with
aortic valve calcium and incident aortic stenosis
.
JAMA
2014
;
312
:
1764
–
1771
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
477

Tsimikas
S.
A test in context: lipoprotein(a): diagnosis, prognosis, controversies, and
emerging therapies
.
J Am Coll Cardiol
2017
;
69
:
692
–
711
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
478

Novaro
GM
,
Tiong
IY
,
Pearce
GL
,
Lauer
MS
,
Sprecher
DL
,
Griffin
BP.
Effect of hydroxymethylglutaryl coenzyme a reductase inhibitors on the
progression of calcific aortic stenosis
.
Circulation
2001
;
104
:
2205
–
2209
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
479

Chan
KL
,
Teo
K
,
Dumesnil
JG
,
Ni
A
,
Tam
J
; ASTRONOMER Investigators.
Effect of Lipid lowering with rosuvastatin on progression of aortic stenosis:
results of the aortic stenosis progression observation: measuring effects of
rosuvastatin (ASTRONOMER) trial
.
Circulation
2010
;
121
:
306
–
314
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
480

Cowell
SJ
,
Newby
DE
,
Prescott
RJ
,
Bloomfield
P
,
Reid
J
,
Northridge
DB
,
Boon
NA
; Scottish Aortic Stenosis and Lipid Lowering Trial, Impact on Regression
(SALTIRE) Investigators.
A randomized trial of intensive lipid-lowering therapy in calcific aortic
stenosis
.
N Engl J Med
2005
;
352
:
2389
–
2397
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
481

Dichtl
W
,
Alber
HF
,
Feuchtner
GM
,
Hintringer
F
,
Reinthaler
M
,
Bartel
T
,
Sussenbacher
A
,
Grander
W
,
Ulmer
H
,
Pachinger
O
,
Muller
S.
Prognosis and risk factors in patients with asymptomatic aortic stenosis and
their modulation by atorvastatin (20 mg)
.
Am J Cardiol
2008
;
102
:
743
–
748
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
482

Thiago
L
,
Tsuji
SR
,
Nyong
J
,
Puga
ME
,
Gois
AF
,
Macedo
CR
,
Valente
O
,
Atallah
AN.
Statins for aortic valve stenosis
.
Cochrane Database Syst Rev
2016
;
9
:
CD009571
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
483

Zhao
Y
,
Nicoll
R
,
He
YH
,
Henein
MY.
The effect of statins on valve function and calcification in aortic stenosis: a
meta-analysis
.
Atherosclerosis
2016
;
246
:
318
–
324
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
484

Greve
AM
,
Bang
CN
,
Boman
K
,
Egstrup
K
,
Forman
JL
,
Kesaniemi
YA
,
Ray
S
,
Pedersen
TR
,
Best
P
,
Rajamannan
NM
,
Wachtell
K.
Effect modifications of lipid-lowering therapy on progression of aortic stenosis
(from the Simvastatin and Ezetimibe in Aortic Stenosis [SEAS] Study)
.
Am J Cardiol
2018
;
121
:
739
–
745
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
485

Arsenault
BJ
,
Boekholdt
SM
,
Mora
S
,
DeMicco
DA
,
Bao
W
,
Tardif
JC
,
Amarenco
P
,
Pedersen
T
,
Barter
P
,
Waters
DD.
Impact of high-dose atorvastatin therapy and clinical risk factors on incident
aortic valve stenosis in patients with cardiovascular disease (from TNT, IDEAL,
and SPARCL)
.
Am J Cardiol
2014
;
113
:
1378
–
1382
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
486

Huded
CP
,
Benck
LR
,
Stone
NJ
,
Sweis
RN
,
Ricciardi
MJ
,
Malaisrie
SC
,
Davidson
CJ
,
Flaherty
JD.
Relation of intensity of statin therapy and outcomes after transcatheter aortic
valve replacement
.
Am J Cardiol
2017
;
119
:
1832
–
1838
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
487

Milin
AC
,
Vorobiof
G
,
Aksoy
O
,
Ardehali
R.
Insights into aortic sclerosis and its relationship with coronary artery disease
.
J Am Heart Assoc
2014
;
3
:
e001111
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
488

Stevens
PE
,
Levin
A
; Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline
Development Work Group Members.
Evaluation and management of chronic kidney disease: synopsis of the kidney
disease: improving global outcomes 2012 clinical practice guideline
.
Ann Intern Med
2013
;
158
:
825
–
830
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
489

Franczyk-Skora
B
,
Gluba
A
,
Banach
M
,
Rozentryt
P
,
Polonski
L
,
Rysz
J.
Acute coronary syndromes in patients with chronic kidney disease
.
Curr Vasc Pharmacol
2013
;
11
:
758
–
767
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
490

Gansevoort
RT
,
Correa-Rotter
R
,
Hemmelgarn
BR
,
Jafar
TH
,
Heerspink
HJ
,
Mann
JF
,
Matsushita
K
,
Wen
CP.
Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and
prevention
.
Lancet
2013
;
382
:
339
–
352
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
491

Olechnowicz-Tietz
S
,
Gluba
A
,
Paradowska
A
,
Banach
M
,
Rysz
J.
The risk of atherosclerosis in patients with chronic kidney disease
.
Int Urol Nephrol
2013
;
45
:
1605
–
1612
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
492

Chronic Kidney Disease Prognosis Consortium

Matsushita
K
,
van der Velde
M
,
Astor
BC
,
Woodward
M
,
Levey
AS
,
de Jong
PE
,
Coresh
J
,
Gansevoort
RT.
Association of estimated glomerular filtration rate and albuminuria with
all-cause and cardiovascular mortality in general population cohorts: a
collaborative meta-analysis
.
Lancet
2010
;
375
:
2073
–
2081
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
493

Loncar
G
,
Barthelemy
O
,
Berman
E
,
Kerneis
M
,
Petroni
T
,
Payot
L
,
Choussat
R
,
Silvain
J
,
Collet
JP
,
Helft
G
,
Montalescot
G
,
Le Feuvre
C.
Impact of renal failure on all-cause mortality and other outcomes in patients
treated by percutaneous coronary intervention
.
Arch Cardiovasc Dis
2015
;
108
:
554
–
562
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
494

Tonelli
M
,
Wanner
C
; Kidney Disease: Improving Global Outcomes Lipid Guideline Development Work
Group Members.
Lipid management in chronic kidney disease: synopsis of the Kidney Disease:
Improving Global Outcomes 2013 clinical practice guideline
.
Ann Intern Med
2014
;
160
:
182
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
495

Barylski
M
,
Nikfar
S
,
Mikhailidis
DP
,
Toth
PP
,
Salari
P
,
Ray
KK
,
Pencina
MJ
,
Rizzo
M
,
Rysz
J
,
Abdollahi
M
,
Nicholls
SJ
,
Banach
M
; Lipid and Blood Pressure Meta-Analysis Collaboration Group.
Statins decrease all-cause mortality only in CKD patients not requiring dialysis
therapy--a meta-analysis of 11 randomized controlled trials involving 21,295
participants
.
Pharmacol Res
2013
;
72
:
35
–
44
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
496

Palmer
SC
,
Navaneethan
SD
,
Craig
JC
,
Johnson
DW
,
Perkovic
V
,
Hegbrant
J
,
Strippoli
GF.
HMG CoA reductase inhibitors (statins) for people with chronic kidney disease
not requiring dialysis
.
Cochrane Database Syst Rev
2014
;
5
:
CD007784
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
497

Agarwal
A
,
Prasad
GV.
Post-transplant dyslipidemia: mechanisms, diagnosis and management
.
World J Transplant
2016
;
6
:
125
–
134
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
498

Bamgbola
O.
Metabolic consequences of modern immunosuppressive agents in solid organ
transplantation
.
Ther Adv Endocrinol Metab
2016
;
7
:
110
–
127
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
499

Numakura
K
,
Kagaya
H
,
Yamamoto
R
,
Komine
N
,
Saito
M
,
Hiroshi
T
,
Akihama
S
,
Inoue
T
,
Narita
S
,
Tsuchiya
N
,
Habuchi
T
,
Niioka
T
,
Miura
M
,
Satoh
S.
Characterization of clinical and genetic risk factors associated with
dyslipidemia after kidney transplantation
.
Dis Markers
2015
;
2015
:
179434
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
500

Pinto
AS
,
Chedid
MF
,
Guerra
LT
,
Cabeleira
DD
,
Kruel
CD.
Dietary management for dyslipidemia in liver transplant recipients
.
Arq Bras Cir Dig
2016
;
29
:
246
–
251
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
501

Riella
LV
,
Gabardi
S
,
Chandraker
A.
Dyslipidemia and its therapeutic challenges in renal transplantation
.
Am J Transplant
2012
;
12
:
1975
–
1982
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
502

Claes
K
,
Meier-Kriesche
HU
,
Schold
JD
,
Vanrenterghem
Y
,
Halloran
PF
,
Ekberg
H.
Effect of different immunosuppressive regimens on the evolution of distinct
metabolic parameters: evidence from the Symphony study
.
Nephrol Dial Transplant
2012
;
27
:
850
–
857
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
503

Deleuze
S
,
Garrigue
V
,
Delmas
S
,
Chong
G
,
Swarcz
I
,
Cristol
JP
,
Mourad
G.
New onset dyslipidemia after renal transplantation: is there a difference
between tacrolimus and cyclosporine?
Transplant Proc
2006
;
38
:
2311
–
2313
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
504

Kasiske
BL
,
de Mattos
A
,
Flechner
SM
,
Gallon
L
,
Meier-Kriesche
HU
,
Weir
MR
,
Wilkinson
A.
Mammalian target of rapamycin inhibitor dyslipidemia in kidney transplant
recipients
.
Am J Transplant
2008
;
8
:
1384
–
1392
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
505

Li
HY
,
Li
B
,
Wei
YG
,
Yan
LN
,
Wen
TF
,
Zhao
JC
,
Xu
MQ
,
Wang
WT
,
Ma
YK
,
Yang
JY.
Higher tacrolimus blood concentration is related to hyperlipidemia in living
donor liver transplantation recipients
.
Dig Dis Sci
2012
;
57
:
204
–
209
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
506

Morrisett
JD
,
Abdel-Fattah
G
,
Hoogeveen
R
,
Mitchell
E
,
Ballantyne
CM
,
Pownall
HJ
,
Opekun
AR
,
Jaffe
JS
,
Oppermann
S
,
Kahan
BD.
Effects of sirolimus on plasma lipids, lipoprotein levels, and fatty acid
metabolism in renal transplant patients
.
J Lipid Res
2002
;
43
:
1170
–
1180
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
507

Page
RL II
,
Miller
GG
,
Lindenfeld
J.
Drug therapy in the heart transplant recipient: part IV: drug-drug interactions
.
Circulation
2005
;
111
:
230
–
239
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
508

Almutairi
F
,
Peterson
TC
,
Molinari
M
,
Walsh
MJ
,
Alwayn
I
,
Peltekian
KM.
Safety and effectiveness of ezetimibe in liver transplant recipients with
hypercholesterolemia
.
Liver Transpl
2009
;
15
:
504
–
508
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
509

Shaw
SM
,
Chaggar
P
,
Ritchie
J
,
Shah
MK
,
Baynes
AC
,
O'Neill
N
,
Fildes
JE
,
Yonan
N
,
Williams
SG.
The efficacy and tolerability of ezetimibe in cardiac transplant recipients
taking cyclosporin
.
Transplantation
2009
;
87
:
771
–
775
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
510

European Stroke Organisation

Tendera
M
,
Aboyans
V
,
Bartelink
ML
,
Baumgartner
I
,
Clement
D
,
Collet
JP
,
Cremonesi
A
,
De Carlo
M
,
Erbel
R
,
Fowkes
FG
,
Heras
M
,
Kownator
S
,
Minar
E
,
Ostergren
J
,
Poldermans
D
,
Riambau
V
,
Roffi
M
,
Rother
J
,
Sievert
H
,
van Sambeek
M
,
Zeller
T
;
ESC Committee for Practice Guidelines. ESC Guidelines on the diagnosis and
treatment of peripheral artery diseases: Document covering atherosclerotic
disease of extracranial carotid and vertebral, mesenteric, renal, upper and
lower extremity arteries: the Task Force on the Diagnosis and Treatment of
Peripheral Artery Diseases of the European Society of Cardiology (ESC)
.
Eur Heart J
2011
;
32
:
2851
–
2906
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
511

McDermott
MM
,
Mandapat
AL
,
Moates
A
,
Albay
M
,
Chiou
E
,
Celic
L
,
Greenland
P.
Knowledge and attitudes regarding cardiovascular disease risk and prevention in
patients with coronary or peripheral arterial disease
.
Arch Intern Med
2003
;
163
:
2157
–
2162
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
512

Aung
PP
,
Maxwell
HG
,
Jepson
RG
,
Price
JF
,
Leng
GC.
Lipid-lowering for peripheral arterial disease of the lower limb
.
Cochrane Database Syst Rev
2007
;
4
:
CD000123
.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
513

Collins
R
,
Armitage
J
,
Parish
S
,
Sleigh
P
,
Peto
R
;
Heart Protection Study Collaborative Group. MRC/BHF Heart Protection Study of
cholesterol-lowering with simvastatin in 5963 people with diabetes: a randomised
placebo-controlled trial
.
Lancet
2003
;
361
:
2005
–
2016
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
514

Bonaca
MP
,
Nault
P
,
Giugliano
RP
,
Keech
AC
,
Pineda
AL
,
Kanevsky
E
,
Kuder
J
,
Murphy
SA
,
Jukema
JW
,
Lewis
BS
,
Tokgozoglu
L
,
Somaratne
R
,
Sever
PS
,
Pedersen
TR
,
Sabatine
MS.
Low-density lipoprotein cholesterol lowering with evolocumab and outcomes in
patients with peripheral artery disease: insights from the FOURIER trial
(Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With
Elevated Risk)
.
Circulation
2018
;
137
:
338
–
350
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
515

Rajamani
K
,
Colman
PG
,
Li
LP
,
Best
JD
,
Voysey
M
,
D'Emden
MC
,
Laakso
M
,
Baker
JR
,
Keech
AC
; FIELD study investigators.
Effect of fenofibrate on amputation events in people with type 2 diabetes
mellitus (FIELD study): a prespecified analysis of a randomised controlled trial
.
Lancet
2009
;
373
:
1780
–
1788
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
516

Tedeschi-Reiner
E
,
Strozzi
M
,
Skoric
B
,
Reiner
Z.
Relation of atherosclerotic changes in retinal arteries to the extent of
coronary artery disease
.
Am J Cardiol
2005
;
96
:
1107
–
1109
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
517

Accord Study Group, Accord Eye Study Group,

Chew
EY
,
Ambrosius
WT
,
Davis
MD
,
Danis
RP
,
Gangaputra
S
,
Greven
CM
,
Hubbard
L
,
Esser
BA
,
Lovato
JF
,
Perdue
LH
,
Goff
DC
Jr,
Cushman
WC
,
Ginsberg
HN
,
Elam
MB
,
Genuth
S
,
Gerstein
HC
,
Schubart
U
,
Fine
LJ.
Effects of medical therapies on retinopathy progression in type 2 diabetes
.
N Engl J Med
2010
;
363
:
233
–
244
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
518

Keech
AC
,
Mitchell
P
,
Summanen
PA
,
O'Day
J
,
Davis
TM
,
Moffitt
MS
,
Taskinen
MR
,
Simes
RJ
,
Tse
D
,
Williamson
E
,
Merrifield
A
,
Laatikainen
LT
,
d'Emden
MC
,
Crimet
DC
,
O'Connell
RL
,
Colman
PG
; FIELD study investigators.
Effect of fenofibrate on the need for laser treatment for diabetic retinopathy
(FIELD study): a randomised controlled trial
.
Lancet
2007
;
370
:
1687
–
1697
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
519

Golledge
J
,
Muller
J
,
Daugherty
A
,
Norman
P.
Abdominal aortic aneurysm: pathogenesis and implications for management
.
Arterioscler Thromb Vasc Biol
2006
;
26
:
2605
–
2613
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
520

Paraskevas
KI
,
Liapis
CD
,
Hamilton
G
,
Mikhailidis
DP.
Can statins reduce perioperative morbidity and mortality in patients undergoing
non-cardiac vascular surgery?
Eur J Vasc Endovasc Surg
2006
;
32
:
286
–
293
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
521

Durazzo
AE
,
Machado
FS
,
Ikeoka
DT
,
De Bernoche
C
,
Monachini
MC
,
Puech-Leao
P
,
Caramelli
B.
Reduction in cardiovascular events after vascular surgery with atorvastatin: a
randomized trial
.
J Vasc Surg
2004
;
39
:
967
–
975; discussion 975
–976.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
522

Schouten
O
,
Boersma
E
,
Hoeks
SE
,
Benner
R
,
van Urk
H
,
van Sambeek
MR
,
Verhagen
HJ
,
Khan
NA
,
Dunkelgrun
M
,
Bax
JJ
,
Poldermans
D
; Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress
Echocardiography Study Group.
Fluvastatin and perioperative events in patients undergoing vascular surgery
.
N Engl J Med
2009
;
361
:
980
–
989
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
523

Hackam
DG
,
Wu
F
,
Li
P
,
Austin
PC
,
Tobe
SW
,
Mamdani
MM
,
Garg
AX.
Statins and renovascular disease in the elderly: a population-based cohort study
.
Eur Heart J
2011
;
32
:
598
–
610
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
524

Subherwal
S
,
Patel
MR
,
Kober
L
,
Peterson
ED
,
Bhatt
DL
,
Gislason
GH
,
Olsen
AM
,
Jones
WS
,
Torp-Pedersen
C
,
Fosbol
EL.
Peripheral artery disease is a coronary heart disease risk equivalent among both
men and women: results from a nationwide study
.
Eur J Prev Cardiol
2015
;
22
:
317
–
325
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
525

Ross
R.
Atherosclerosis--an inflammatory disease
.
N Engl J Med
1999
;
340
:
115
–
126
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
526

Tabas
I
,
Lichtman
AH.
Monocyte-macrophages and T cells in atherosclerosis
.
Immunity
2017
;
47
:
621
–
634
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
527

Emini Veseli
B
,
Perrotta
P
,
De Meyer
GRA
,
Roth
L
,
Van der Donckt
C
,
Martinet
W
,
De Meyer
GRY.
Animal models of atherosclerosis
.
Eur J Pharmacol
2017
;
816
:
3
–
13
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
528

Tillett
WS
,
Francis
T.
Serological reactions in pneumonia with a non-protein somatic fraction of
Pneumococcus
.
J Exp Med
1930
;
52
:
561
–
571
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
529

Sabatine
MS
,
Morrow
DA
,
Jablonski
KA
,
Rice
MM
,
Warnica
JW
,
Domanski
MJ
,
Hsia
J
,
Gersh
BJ
,
Rifai
N
,
Ridker
PM
,
Pfeffer
MA
,
Braunwald
E
; PEACE Investigators.
Prognostic significance of the Centers for Disease Control/American Heart
Association high-sensitivity C-reactive protein cut points for cardiovascular
and other outcomes in patients with stable coronary artery disease
.
Circulation
2007
;
115
:
1528
–
1536
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
530

Ridker
PM
,
Cushman
M
,
Stampfer
MJ
,
Tracy
RP
,
Hennekens
CH.
Inflammation, aspirin, and the risk of cardiovascular disease in apparently
healthy men
.
N Engl J Med
1997
;
336
:
973
–
979
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
531

Ridker
PM
,
Hennekens
CH
,
Buring
JE
,
Rifai
N.
C-reactive protein and other markers of inflammation in the prediction of
cardiovascular disease in women
.
N Engl J Med
2000
;
342
:
836
–
843
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
532

Danesh
J
,
Wheeler
JG
,
Hirschfield
GM
,
Eda
S
,
Eiriksdottir
G
,
Rumley
A
,
Lowe
GD
,
Pepys
MB
,
Gudnason
V.
C-reactive protein and other circulating markers of inflammation in the
prediction of coronary heart disease
.
N Engl J Med
2004
;
350
:
1387
–
1397
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
533

Elliott
P
,
Chambers
JC
,
Zhang
W
,
Clarke
R
,
Hopewell
JC
,
Peden
JF
,
Erdmann
J
,
Braund
P
,
Engert
JC
,
Bennett
D
,
Coin
L
,
Ashby
D
,
Tzoulaki
I
,
Brown
IJ
,
Mt-Isa
S
,
McCarthy
MI
,
Peltonen
L
,
Freimer
NB
,
Farrall
M
,
Ruokonen
A
,
Hamsten
A
,
Lim
N
,
Froguel
P
,
Waterworth
DM
,
Vollenweider
P
,
Waeber
G
,
Jarvelin
MR
,
Mooser
V
,
Scott
J
,
Hall
AS
,
Schunkert
H
,
Anand
SS
,
Collins
R
,
Samani
NJ
,
Watkins
H
,
Kooner
JS.
Genetic loci associated with C-reactive protein levels and risk of coronary
heart disease
.
JAMA
2009
;
302
:
37
–
48
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
534

Emerging Risk Factors Collaboration,

Kaptoge
S
,
Di Angelantonio
E
,
Pennells
L
,
Wood
AM
,
White
IR
,
Gao
P
,
Walker
M
,
Thompson
A
,
Sarwar
N
,
Caslake
M
,
Butterworth
AS
,
Amouyel
P
,
Assmann
G
,
Bakker
SJ
,
Barr
EL
,
Barrett-Connor
E
,
Benjamin
EJ
,
Bjorkelund
C
,
Brenner
H
,
Brunner
E
,
Clarke
R
,
Cooper
JA
,
Cremer
P
,
Cushman
M
,
Dagenais
GR
,
D'Agostino
RB
Sr,
Dankner
R
,
Davey-Smith
G
,
Deeg
D
,
Dekker
JM
,
Engstrom
G
,
Folsom
AR
,
Fowkes
FG
,
Gallacher
J
,
Gaziano
JM
,
Giampaoli
S
,
Gillum
RF
,
Hofman
A
,
Howard
BV
,
Ingelsson
E
,
Iso
H
,
Jorgensen
T
,
Kiechl
S
,
Kitamura
A
,
Kiyohara
Y
,
Koenig
W
,
Kromhout
D
,
Kuller
LH
,
Lawlor
DA
,
Meade
TW
,
Nissinen
A
,
Nordestgaard
BG
,
Onat
A
,
Panagiotakos
DB
,
Psaty
BM
,
Rodriguez
B
,
Rosengren
A
,
Salomaa
V
,
Kauhanen
J
,
Salonen
JT
,
Shaffer
JA
,
Shea
S
,
Ford
I
,
Stehouwer
CD
,
Strandberg
TE
,
Tipping
RW
,
Tosetto
A
,
Wassertheil-Smoller
S
,
Wennberg
P
,
Westendorp
RG
,
Whincup
PH
,
Wilhelmsen
L
,
Woodward
M
,
Lowe
GD
,
Wareham
NJ
,
Khaw
KT
,
Sattar
N
,
Packard
CJ
,
Gudnason
V
,
Ridker
PM
,
Pepys
MB
,
Thompson
SG
,
Danesh
J.
C-reactive protein, fibrinogen, and cardiovascular disease prediction
.
N Engl J Med
2012
;
367
:
1310
–
1320
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
535

Zacho
J
,
Tybjaerg-Hansen
A
,
Jensen
JS
,
Grande
P
,
Sillesen
H
,
Nordestgaard
BG.
Genetically elevated C-reactive protein and ischemic vascular disease
.
N Engl J Med
2008
;
359
:
1897
–
1908
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
536

Miller
DT
,
Zee
RY
,
Suk Danik
J
,
Kozlowski
P
,
Chasman
DI
,
Lazarus
R
,
Cook
NR
,
Ridker
PM
,
Kwiatkowski
DJ.
Association of common CRP gene variants with CRP levels and cardiovascular
events
.
Ann Hum Genet
2005
;
69
:
623
–
638
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
537

Koenig
W.
High-sensitivity C-reactive protein and atherosclerotic disease: from improved
risk prediction to risk-guided therapy
.
Int J Cardiol
2013
;
168
:
5126
–
5134
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
538

Grundy
SM
,
Stone
NJ
,
Bailey
AL
,
Beam
C
,
Birtcher
KK
,
Blumenthal
RS
,
Braun
LT
,
Braun
LT
,
de Ferranti
S
,
Faiella-Tommasino
J
,
Forman
DE
,
Goldberg
R
,
Heidenreich
PA
,
Hlatky
MA
,
Jones
DW
,
Lloyd-Jones
D
,
Lopez-Pajares
N
,
Ndumele
CE
,
Orringer
CE
,
Peralta
CA
,
Saseen
JJ
,
Smith
SC
Jr,
Sperling
L
,
Virani
SS
,
Yeboah
J.
2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the
management of blood cholesterol: executive summary: a report of the American
College of Cardiology/American Heart Association Task Force on Clinical Practice
Guidelines
.
J Am Coll Cardiol
2018
:
S0735
–
1097
:39033–39038.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
539

Arnaud
C
,
Burger
F
,
Steffens
S
,
Veillard
NR
,
Nguyen
TH
,
Trono
D
,
Mach
F.
Statins reduce interleukin-6-induced C-reactive protein in human hepatocytes:
new evidence for direct antiinflammatory effects of statins
.
Arterioscler Thromb Vasc Biol
2005
;
25
:
1231
–
1236
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
540

Bohula
EA
,
Giugliano
RP
,
Cannon
CP
,
Zhou
J
,
Murphy
SA
,
White
JA
,
Tershakovec
AM
,
Blazing
MA
,
Braunwald
E.
Achievement of dual low-density lipoprotein cholesterol and high-sensitivity
C-reactive protein targets more frequent with the addition of ezetimibe to
simvastatin and associated with better outcomes in IMPROVE-IT
.
Circulation
2015
;
132
:
1224
–
1233
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
541

Ridker
PM
,
Cannon
CP
,
Morrow
D
,
Rifai
N
,
Rose
LM
,
McCabe
CH
,
Pfeffer
MA
,
Braunwald
E
; Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in
Myocardial Infarction 22 (PROVE IT-TIMI 22) Investigators.
C-reactive protein levels and outcomes after statin therapy
.
N Engl J Med
2005
;
352
:
20
–
28
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
542

Ridker
PM
,
Danielson
E
,
Fonseca
FA
,
Genest
J
,
Gotto
AM
Jr,
Kastelein
JJ
,
Koenig
W
,
Libby
P
,
Lorenzatti
AJ
,
MacFadyen
JG
,
Nordestgaard
BG
,
Shepherd
J
,
Willerson
JT
,
Glynn
RJ
; JUPITER Study Group.
Rosuvastatin to prevent vascular events in men and women with elevated
C-reactive protein
.
N Engl J Med
2008
;
359
:
2195
–
2207
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
543

Ridker
PM
,
Rifai
N
,
Clearfield
M
,
Downs
JR
,
Weis
SE
,
Miles
JS
,
Gotto
AM
Jr; Air Force/Texas Coronary Atherosclerosis Prevention Study Investigators.
Measurement of C-reactive protein for the targeting of statin therapy in the
primary prevention of acute coronary events
.
N Engl J Med
2001
;
344
:
1959
–
1965
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
544

Ridker
PM
,
Rifai
N
,
Pfeffer
MA
,
Sacks
FM
,
Moye
LA
,
Goldman
S
,
Flaker
GC
,
Braunwald
E.
Inflammation, pravastatin, and the risk of coronary events after myocardial
infarction in patients with average cholesterol levels. Cholesterol and
Recurrent Events (CARE) Investigators
.
Circulation
1998
;
98
:
839
–
844
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
545

Ridker
PM
,
Danielson
E
,
Fonseca
FA
,
Genest
J
,
Gotto
AM
Jr,
Kastelein
JJ
,
Koenig
W
,
Libby
P
,
Lorenzatti
AJ
,
Macfadyen
JG
,
Nordestgaard
BG
,
Shepherd
J
,
Willerson
JT
,
Glynn
RJ
; JUPITER Trial Study Group.
Reduction in C-reactive protein and LDL cholesterol and cardiovascular event
rates after initiation of rosuvastatin: a prospective study of the JUPITER trial
.
Lancet
2009
;
373
:
1175
–
1182
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
546

Barbosa
SP
,
Lins
LC
,
Fonseca
FA
,
Matos
LN
,
Aguirre
AC
,
Bianco
HT
,
Amaral
JB
,
Franca
CN
,
Santana
JM
,
Izar
MC.
Effects of ezetimibe on markers of synthesis and absorption of cholesterol in
high-risk patients with elevated C-reactive protein
.
Life Sci
2013
;
92
:
845
–
851
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
547

Sahebkar
A
,
Di Giosia
P
,
Stamerra
CA
,
Grassi
D
,
Pedone
C
,
Ferretti
G
,
Bacchetti
T
,
Ferri
C
,
Giorgini
P.
Effect of monoclonal antibodies to PCSK9 on high-sensitivity C-reactive protein
levels: a meta-analysis of 16 randomized controlled treatment arms
.
Br J Clin Pharmacol
2016
;
81
:
1175
–
1190
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
548

Ridker
PM
,
Everett
BM
,
Thuren
T
,
MacFadyen
JG
,
Chang
WH
,
Ballantyne
C
,
Fonseca
F
,
Nicolau
J
,
Koenig
W
,
Anker
SD
,
Kastelein
JJP
,
Cornel
JH
,
Pais
P
,
Pella
D
,
Genest
J
,
Cifkova
R
,
Lorenzatti
A
,
Forster
T
,
Kobalava
Z
,
Vida-Simiti
L
,
Flather
M
,
Shimokawa
H
,
Ogawa
H
,
Dellborg
M
,
Rossi
PRF
,
Troquay
RPT
,
Libby
P
,
Glynn
RJ
; CANTOS Trial Group.
Antiinflammatory therapy with canakinumab for atherosclerotic disease
.
N Engl J Med
2017
;
377
:
1119
–
1131
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
549

Ridker
PM.
Testing the inflammatory hypothesis of atherothrombosis: scientific rationale
for the cardiovascular inflammation reduction trial (CIRT)
.
J Thromb Haemost
2009
;
7
:
332
–
339
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
550

Ridker
PM
,
Everett
BM
,
Pradhan
A
,
MacFadyen
JG
,
Solomon
DH
,
Zaharris
E
,
Mam
V
,
Hasan
A
,
Rosenberg
Y
,
Iturriaga
E
,
Gupta
M
,
Tsigoulis
M
,
Verma
S
,
Clearfield
M
,
Libby
P
,
Goldhaber
SZ
,
Seagle
R
,
Ofori
C
,
Saklayen
M
,
Butman
S
,
Singh
N
,
Le May
M
,
Bertrand
O
,
Johnston
J
,
Paynter
NP
,
Glynn
RJ
; CIRT Investigators.
Low-dose methotrexate for the prevention of atherosclerotic events
.
N Engl J Med
2019
;
380
:
752
–
762
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
551

Weber
C
,
Badimon
L
,
Mach
F
,
van der Vorst
EPC.
Therapeutic strategies for atherosclerosis and atherothrombosis: past, present
and future
.
Thromb Haemost
2017
;
117
:
1258
–
1264
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
552

Newman
C
,
Tsai
J
,
Szarek
M
,
Luo
D
,
Gibson
E.
Comparative safety of atorvastatin 80 mg versus 10 mg derived from analysis of
49 completed trials in 14,236 patients
.
Am J Cardiol
2006
;
97
:
61
–
67
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
553

Bays
H
,
Cohen
DE
,
Chalasani
N
,
Harrison
SA
,
The National Lipid Association's Statin Safety Task Force. An assessment by the
Statin Liver Safety Task Force: 2014 update
.
J Clin Lipidol
2014
;
8
:
S47
–
S57
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
554

Bjornsson
E
,
Jacobsen
EI
,
Kalaitzakis
E.
Hepatotoxicity associated with statins: reports of idiosyncratic liver injury
post-marketing
.
J Hepatol
2012
;
56
:
374
–
380
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
555

Clarke
AT
,
Johnson
PC
,
Hall
GC
,
Ford
I
,
Mills
PR.
High dose atorvastatin associated with increased risk of significant
hepatotoxicity in comparison to simvastatin in UK GPRD cohort
.
PLoS One
2016
;
11
:
e0151587
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
556

Cederberg
H
,
Stancakova
A
,
Yaluri
N
,
Modi
S
,
Kuusisto
J
,
Laakso
M.
Increased risk of diabetes with statin treatment is associated with impaired
insulin sensitivity and insulin secretion: a 6 year follow-up study of the
METSIM cohort
.
Diabetologia
2015
;
58
:
1109
–
1117
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
557

Mora
S
,
Glynn
RJ
,
Hsia
J
,
MacFadyen
JG
,
Genest
J
,
Ridker
PM.
Statins for the primary prevention of cardiovascular events in women with
elevated high-sensitivity C-reactive protein or dyslipidemia: results from the
Justification for the Use of Statins in Prevention: An Intervention Trial
Evaluating Rosuvastatin (JUPITER) and meta-analysis of women from primary
prevention trials
.
Circulation
2010
;
121
:
1069
–
1077
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
558

Atlas Writing Group

Timmis
A
,
Townsend
N
,
Gale
C
,
Grobbee
R
,
Maniadakis
N
,
Flather
M
,
Wilkins
E
,
Wright
L
,
Vos
R
,
Bax
J
,
Blum
M
,
Pinto
F
,
Vardas
P.
European Society of Cardiology: cardiovascular disease statistics 2017
.
Eur Heart J
2018
;
39
:
508
–
579
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
559

Roth
GA
,
Forouzanfar
MH
,
Moran
AE
,
Barber
R
,
Nguyen
G
,
Feigin
VL
,
Naghavi
M
,
Mensah
GA
,
Murray
CJ.
Demographic and epidemiologic drivers of global cardiovascular mortality
.
N Engl J Med
2015
;
372
:
1333
–
1341
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
560

Aspelund
T
,
Gudnason
V
,
Magnusdottir
BT
,
Andersen
K
,
Sigurdsson
G
,
Thorsson
B
,
Steingrimsdottir
L
,
Critchley
J
,
Bennett
K
,
O'Flaherty
M
,
Capewell
S.
Analysing the large decline in coronary heart disease mortality in the Icelandic
population aged 25-74 between the years 1981 and 2006
.
PLoS One
2010
;
5
:
e13957
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
561

Bjorck
L
,
Rosengren
A
,
Bennett
K
,
Lappas
G
,
Capewell
S.
Modelling the decreasing coronary heart disease mortality in Sweden between 1986
and 2002
.
Eur Heart J
2009
;
30
:
1046
–
1056
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
562

Pereira
M
,
Azevedo
A
,
Lunet
N
,
Carreira
H
,
O'Flaherty
M
,
Capewell
S
,
Bennett
K.
Explaining the decline in coronary heart disease mortality in Portugal between
1995 and 2008
.
Circ Cardiovasc Qual Outcomes
2013
;
6
:
634
–
642
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
563

Unal
B
,
Sozmen
K
,
Arik
H
,
Gerceklioglu
G
,
Altun
DU
,
Simsek
H
,
Doganay
S
,
Demiral
Y
,
Aslan
O
,
Bennett
K
,
O'Flaherty
M
,
Capewell
S
,
Critchley
J.
Explaining the decline in coronary heart disease mortality in Turkey between
1995 and 2008
.
BMC Public Health
2013
;
13
:
1135
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
564

EunetHta Joint Action
2
,
Work Package
7
,
Subgroup
3
,
Heintz
E
,
Gerber-Grote
A
,
Ghabri
S
,
Hamers
FF
,
Rupel
VP
,
Slabe-Erker
R
,
Davidson
T.
Is there a European view on health economic evaluations? Results from a synopsis
of methodological guidelines used in the EUnetHTA partner countries
.
Pharmacoeconomics
2016
;
34
:
59
–
76
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
565

Drummond
M
,
Barbieri
M
,
Cook
J
,
Glick
HA
,
Lis
J
,
Malik
F
,
Reed
SD
,
Rutten
F
,
Sculpher
M
,
Severens
J.
Transferability of economic evaluations across jurisdictions: ISPOR Good
Research Practices Task Force report
.
Value Health
2009
;
12
:
409
–
418
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
566

Frieden
TR.
A framework for public health action: the health impact pyramid
.
Am J Public Health
2010
;
100
:
590
–
595
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
567

Hotchkiss
JW
,
Davies
CA
,
Dundas
R
,
Hawkins
N
,
Jhund
PS
,
Scholes
S
,
Bajekal
M
,
O'Flaherty
M
,
Critchley
J
,
Leyland
AH
,
Capewell
S.
Explaining trends in Scottish coronary heart disease mortality between 2000 and
2010 using IMPACTSEC model: retrospective analysis using routine data
.
BMJ
2014
;
348
:
g1088
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
568

Cobiac
LJ
,
Magnus
A
,
Lim
S
,
Barendregt
JJ
,
Carter
R
,
Vos
T.
Which interventions offer best value for money in primary prevention of
cardiovascular disease?
PLoS One
2012
;
7
:
e41842
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
569

Collins
M
,
Mason
H
,
O'Flaherty
M
,
Guzman-Castillo
M
,
Critchley
J
,
Capewell
S.
An economic evaluation of salt reduction policies to reduce coronary heart
disease in England: a policy modeling study
.
Value Health
2014
;
17
:
517
–
524
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
570

Mason
H
,
Shoaibi
A
,
Ghandour
R
,
O'Flaherty
M
,
Capewell
S
,
Khatib
R
,
Jabr
S
,
Unal
B
,
Sozmen
K
,
Arfa
C
,
Aissi
W
,
Ben Romdhane
H
,
Fouad
F
,
Al-Ali
R
,
Husseini
A
; MedCHAMPS project team.
A cost effectiveness analysis of salt reduction policies to reduce coronary
heart disease in four Eastern Mediterranean countries
.
PLoS One
2014
;
9
:
e84445
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
571

Moreira
PV
,
Baraldi
LG
,
Moubarac
JC
,
Monteiro
CA
,
Newton
A
,
Capewell
S
,
O'Flaherty
M.
Comparing different policy scenarios to reduce the consumption of
ultra-processed foods in UK: impact on cardiovascular disease mortality using a
modelling approach
.
PLoS One
2015
;
10
:
e0118353
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
572

O'Keeffe
C
,
Kabir
Z
,
O'Flaherty
M
,
Walton
J
,
Capewell
S
,
Perry
IJ.
Modelling the impact of specific food policy options on coronary heart disease
and stroke deaths in Ireland
.
BMJ Open
2013
;
3
:
e002837
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
573

Barton
P
,
Andronis
L
,
Briggs
A
,
McPherson
K
,
Capewell
S.
Effectiveness and cost effectiveness of cardiovascular disease prevention in
whole populations: modelling study
.
BMJ
2011
;
343
:
d4044
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
574

Muennig
PA
,
Epstein
M
,
Li
G
,
DiMaggio
C.
The cost-effectiveness of New York City's Safe Routes to School Program
.
Am J Public Health
2014
;
104
:
1294
–
1299
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
575

Roux
L
,
Pratt
M
,
Tengs
TO
,
Yore
MM
,
Yanagawa
TL
,
Van Den Bos
J
,
Rutt
C
,
Brownson
RC
,
Powell
KE
,
Heath
G
,
Kohl
HW III
,
Teutsch
S
,
Cawley
J
,
Lee
IM
,
West
L
,
Buchner
DM.
Cost effectiveness of community-based physical activity interventions
.
Am J Prev Med
2008
;
35
:
578
–
588
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
576

Jørgensen
T
,
Capewell
S
,
Prescott
E
,
Allender
S
,
Sans
S
,
Zdrojewski
T
,
De Bacquer
D
,
de Sutter
J
,
Franco
OH
,
Løgstrup
S
,
Volpe
M
,
Malyutina
S
,
Marques-Vidal
P
,
Reiner
Z
,
Tell
GS
,
Verschuren
WM
,
Vanuzzo
D
; PEP section of EACPR.
Population-level changes to promote cardiovascular health
.
Eur J Prev Cardiol
2013
;
20
:
409
–
421
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
577

Mozaffarian
D
,
Appel
LJ
,
Van Horn
L.
Components of a cardioprotective diet: new insights
.
Circulation
2011
;
123
:
2870
–
2891
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
578

Dalziel
K
,
Segal
L.
Time to give nutrition interventions a higher profile: cost-effectiveness of 10
nutrition interventions
.
Health Promot Int
2007
;
22
:
271
–
283
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
579

Ahern
AL
,
Wheeler
GM
,
Aveyard
P
,
Boyland
EJ
,
Halford
JCG
,
Mander
AP
,
Woolston
J
,
Thomson
AM
,
Tsiountsioura
M
,
Cole
D
,
Mead
BR
,
Irvine
L
,
Turner
D
,
Suhrcke
M
,
Pimpin
L
,
Retat
L
,
Jaccard
A
,
Webber
L
,
Cohn
SR
,
Jebb
SA.
Extended and standard duration weight-loss programme referrals for adults in
primary care (WRAP): a randomised controlled trial
.
Lancet
2017
;
389
:
2214
–
2225
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
580

Neumann
A
,
Lindholm
L
,
Norberg
M
,
Schoffer
O
,
Klug
SJ
,
Norstrom
F.
The cost-effectiveness of interventions targeting lifestyle change for the
prevention of diabetes in a Swedish primary care and community based prevention
program
.
Eur J Health Econ
2017
;
18
:
905
–
919
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
581

Hoogendoorn
M
,
Feenstra
TL
,
Hoogenveen
RT
,
Rutten-van Molken
MP.
Long-term effectiveness and cost-effectiveness of smoking cessation
interventions in patients with COPD
.
Thorax
2010
;
65
:
711
–
718
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
582

Forster
M
,
Veerman
JL
,
Barendregt
JJ
,
Vos
T.
Cost-effectiveness of diet and exercise interventions to reduce overweight and
obesity
.
Int J Obes (Lond)
2011
;
35
:
1071
–
1078
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
583

Chow
CK
,
Jolly
S
,
Rao-Melacini
P
,
Fox
KA
,
Anand
SS
,
Yusuf
S.
Association of diet, exercise, and smoking modification with risk of early
cardiovascular events after acute coronary syndromes
.
Circulation
2010
;
121
:
750
–
758
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
584

Loveman
E
,
Frampton
GK
,
Shepherd
J
,
Picot
J
,
Cooper
K
,
Bryant
J
,
Welch
K
,
Clegg
A.
The clinical effectiveness and cost-effectiveness of long-term weight management
schemes for adults: a systematic review
.
Health Technol Assess
2011
;
15
:
1
–
182
.





Google Scholar

Crossref
Search ADS


WorldCat

 
585

Guerriero
C
,
Cairns
J
,
Roberts
I
,
Rodgers
A
,
Whittaker
R
,
Free
C.
The cost-effectiveness of smoking cessation support delivered by mobile phone
text messaging: Txt2stop
.
Eur J Health Econ
2013
;
14
:
789
–
797
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
586

McConnachie
A
,
Walker
A
,
Robertson
M
,
Marchbank
L
,
Peacock
J
,
Packard
CJ
,
Cobbe
SM
,
Ford
I.
Long-term impact on healthcare resource utilization of statin treatment, and its
cost effectiveness in the primary prevention of cardiovascular disease: a record
linkage study
.
Eur Heart J
2014
;
35
:
290
–
298
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
587

Peura
P
,
Martikainen
J
,
Soini
E
,
Hallinen
T
,
Niskanen
L.
Cost-effectiveness of statins in the prevention of coronary heart disease events
in middle-aged Finnish men
.
Curr Med Res Opin
2008
;
24
:
1823
–
1832
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
588

Heller
DJ
,
Coxson
PG
,
Penko
J
,
Pletcher
MJ
,
Goldman
L
,
Odden
MC
,
Kazi
DS
,
Bibbins-Domingo
K.
Evaluating the impact and cost-effectiveness of statin use guidelines for
primary prevention of coronary heart disease and stroke
.
Circulation
2017
;
136
:
1087
–
1098
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
589

Pandya
A
,
Sy
S
,
Cho
S
,
Weinstein
MC
,
Gaziano
TA.
Cost-effectiveness of 10-year risk thresholds for initiation of statin therapy
for primary prevention of cardiovascular disease
.
JAMA
2015
;
314
:
142
–
150
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
590

Heart Protection Study C,

Mihaylova
B
,
Briggs
A
,
Armitage
J
,
Parish
S
,
Gray
A
,
Collins
R.
Lifetime cost effectiveness of simvastatin in a range of risk groups and age
groups derived from a randomised trial of 20,536 people
.
BMJ
2006
;
333
:
1145
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
591

Ward
S
,
Lloyd Jones
M
,
Pandor
A
,
Holmes
M
,
Ara
R
,
Ryan
A
,
Yeo
W
,
Payne
N.
A systematic review and economic evaluation of statins for the prevention of
coronary events
.
Health Technol Assess
2007
;
11
:
1
–
160
, iii–iv.



Google Scholar

OpenURL Placeholder Text

WorldCat

 
592

Davies
GM
,
Vyas
A
,
Baxter
CA.
Economic evaluation of ezetimibe treatment in combination with statin therapy in
the United States
.
J Med Econ
2017
;
20
:
723
–
731
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
593

Lindgren
P
,
Graff
J
,
Olsson
AG
,
Pedersen
TJ
,
Jonsson
B
; IDEAL Trial Investigators.
Cost-effectiveness of high-dose atorvastatin compared with regular dose
simvastatin
.
Eur Heart J
2007
;
28
:
1448
–
1453
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
594

Stam-Slob
MC
,
van der Graaf
Y
,
Greving
JP
,
Dorresteijn
JA
,
Visseren
FL.
Cost-effectiveness of intensifying lipid-lowering therapy with statins based on
individual absolute benefit in coronary artery disease patients
.
J Am Heart Assoc
2017
;
6
;
e004648
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
595

Kotseva
K
,
De Bacquer
D
,
De Backer
G
,
Ryden
L
,
Jennings
C
,
Gyberg
V
,
Abreu
A
,
Aguiar
C
,
Conde
AC
,
Davletov
K
,
Dilic
M
,
Dolzhenko
M
,
Gaita
D
,
Georgiev
B
,
Gotcheva
N
,
Lalic
N
,
Laucevicius
A
,
Lovic
D
,
Mancas
S
,
Milicic
D
,
Oganov
R
,
Pajak
A
,
Pogosova
N
,
Reiner
Z
,
Vulic
D
,
Wood
D
,
On Behalf Of The Euroaspire Investigators. Lifestyle and risk factor management
in people at high risk of cardiovascular disease. A report from the European
Society of Cardiology European Action on Secondary and Primary Prevention by
Intervention to Reduce Events (EUROASPIRE) IV cross-sectional survey in 14
European regions
.
Eur J Prev Cardiol
2016
;
23
:
2007
–
2018
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
596

Cherry
SB
,
Benner
JS
,
Hussein
MA
,
Tang
SS
,
Nichol
MB.
The clinical and economic burden of nonadherence with antihypertensive and
lipid-lowering therapy in hypertensive patients
.
Value Health
2009
;
12
:
489
–
497
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
597

Vonbank
A
,
Agewall
S
,
Kjeldsen
KP
,
Lewis
BS
,
Torp-Pedersen
C
,
Ceconi
C
,
Funck-Brentano
C
,
Kaski
JC
,
Niessner
A
,
Tamargo
J
,
Walther
T
,
Wassmann
S
,
Rosano
G
,
Schmidt
H
,
Saely
CH
,
Drexel
H.
Comprehensive efforts to increase adherence to statin therapy
.
Eur Heart J
2017
;
38
:
2473
–
2479
.





Google Scholar

PubMed
OpenURL Placeholder Text

WorldCat

 
598

Corrao
G
,
Scotti
L
,
Zambon
A
,
Baio
G
,
Nicotra
F
,
Conti
V
,
Capri
S
,
Tragni
E
,
Merlino
L
,
Catapano
AL
,
Mancia
G.
Cost-effectiveness of enhancing adherence to therapy with statins in the setting
of primary cardiovascular prevention. Evidence from an empirical approach based
on administrative databases
.
Atherosclerosis
2011
;
217
:
479
–
485
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
599

Chapman
RH
,
Kowal
SL
,
Cherry
SB
,
Ferrufino
CP
,
Roberts
CS
,
Chen
L.
The modeled lifetime cost-effectiveness of published adherence-improving
interventions for antihypertensive and lipid-lowering medications
.
Value Health
2010
;
13
:
685
–
694
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
600

Brown
MT
,
Bussell
JK.
Medication adherence: WHO cares?
Mayo Clin Proc
2011
;
86
:
304
–
314
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
601

Bonow
RO
,
Harrington
RA
,
Yancy
CW.
Cost-effectiveness of PCSK9 inhibitors: proof in the modeling
.
JAMA Cardiol
2017
;
2
:
1298
–
1299
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
602

Arrieta
A
,
Hong
JC
,
Khera
R
,
Virani
SS
,
Krumholz
HM
,
Nasir
K.
Updated cost-effectiveness assessments of PCSK9 inhibitors from the perspectives
of the health system and private payers: insights derived from the FOURIER trial
.
JAMA Cardiol
2017
;
2
:
1369
–
1374
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
603

Fonarow
GC
,
Keech
AC
,
Pedersen
TR
,
Giugliano
RP
,
Sever
PS
,
Lindgren
P
,
van Hout
B
,
Villa
G
,
Qian
Y
,
Somaratne
R
,
Sabatine
MS.
Cost-effectiveness of evolocumab therapy for reducing cardiovascular events in
patients with atherosclerotic cardiovascular disease
.
JAMA Cardiol
2017
;
2
:
1069
–
1078
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
604

Korman
M
,
Wisloff
T.
Modelling the cost-effectiveness of PCSK9 inhibitors vs. ezetimibe through LDL-C
reductions in a Norwegian setting
.
Eur Heart J Cardiovasc Pharmacother
2018
;
4
:
15
–
22
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
605

Annemans
L
,
Packard
CJ
,
Briggs
A
,
Ray
KK.
‘Highest risk-highest benefit’ strategy: a pragmatic, cost-effective approach to
targeting use of PCSK9 inhibitor therapies
.
Eur Heart J
2018
;
39
:
2546
–
2550
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
606

Robinson
JG
,
Huijgen
R
,
Ray
K
,
Persons
J
,
Kastelein
JJ
,
Pencina
MJ.
Determining when to add nonstatin therapy: a quantitative approach
.
J Am Coll Cardiol
2016
;
68
:
2412
–
2421
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
607

Kazi
DS
,
Penko
J
,
Coxson
PG
,
Moran
AE
,
Ollendorf
DA
,
Tice
JA
,
Bibbins-Domingo
K.
Updated cost-effectiveness analysis of PCSK9 inhibitors based on the results of
the FOURIER trial
.
JAMA
2017
;
318
:
748
–
750
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 
608

Wood
DA
,
Kotseva
K
,
Connolly
S
,
Jennings
C
,
Mead
A
,
Jones
J
,
Holden
A
,
De Bacquer
D
,
Collier
T
,
De Backer
G
,
Faergeman
O
;
EUROACTION Study Group. Nurse-coordinated multidisciplinary, family-based
cardiovascular disease prevention programme (EUROACTION) for patients with
coronary heart disease and asymptomatic individuals at high risk of
cardiovascular disease: a paired, cluster-randomised controlled trial
.
Lancet
2008
;
371
:
1999
–
2012
.





Google Scholar

Crossref
Search ADS

PubMed

WorldCat

 



AUTHOR NOTES

François Mach, Colin Baigent and Alberico L. Catapano chairpersons contributed
equally to the document.

Alberico L. Catapano, Manuela Casula, Gabriele Riccardi, Marja-Riitta Taskinen,
Lale Tokgozoglu, Olov Wiklund, Alberto Corsini, Meral Kayikcioglu, Philippe
Moulin, Xavier Pintó, Kausik K. Ray, Željko Reiner, Erik Stroes, Alexandros D.
Tselepis, Margus Viigimaa and Michal Vrablik: representing the EAS.

© The European Society of Cardiology and the European Atherosclerosis
Association 2019. All rights reserved. For permissions please email:
journals.permissions@oup.com.
This article is published and distributed under the terms of the Oxford
University Press, Standard Journals Publication Model
(https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
© The European Society of Cardiology and the European Atherosclerosis
Association 2019. All rights reserved. For permissions please email:
journals.permissions@oup.com.





Download all slides


SUPPLEMENTARY DATA

ehz455_Supplementary_Data - pdf file


Advertisement


CITATIONS

3.2k
CITATIONS


VIEWS

991,083


ALTMETRIC


More metrics information
×


EMAIL ALERTS

Article activity alert
Advance article alerts
New issue alert
Receive exclusive offers and updates from Oxford Academic



SEE ALSO

 * COMPANION ARTICLE
   
   * Corrigendum to: 2019 ESC/EAS Guidelines for the management of
     dyslipidaemias: lipid modification to reduce cardiovascular risk


RECOMMENDED

 1. The year in cardiovascular medicine 2021: dyslipidaemia
    Lale Tokgozoglu et al., European Heart Journal
 2. Cholesteryl ester transfer protein inhibitors: from high-density lipoprotein
    cholesterol to low-density lipoprotein cholesterol lowering agents?
    Nick S Nurmohamed et al., Cardiovascular Research

 1. Extreme cardiovascular risk—do we need a new risk category?
    Krzysztof Dyrbuś et al., European Heart Journal
 2. 2021 ESC Guidelines on cardiovascular disease prevention in clinical
    practiceDeveloped by the Task Force for cardiovascular disease prevention in
    clinical practice with representatives of the European Society of Cardiology
    and 12 medical societies With the special contribution of the European
    Association of Preventive Cardiology (EAPC)
    Frank L J Visseren et al., European Heart Journal

Powered by
 * Privacy policy
 * Do not sell my personal information
 * Google Analytics settings


I consent to the use of Google Analytics and related cookies across the TrendMD
network (widget, website, blog). Learn more
Yes No



MORE ON THIS TOPIC

New therapeutic principles in dyslipidaemia: focus on LDL and Lp(a) lowering
drugs
Visit-to-visit cholesterol variability correlates with coronary atheroma
progression and clinical outcomes
Genes and dyslipoproteinaemias
Do systemic risk factors impact invasive findings from virtual histology?
Insights from the international virtual histology registry


RELATED ARTICLES IN

 * Web of Science
 * Google Scholar


RELATED ARTICLES IN PUBMED

Study of common hypertriglyceridaemia genetic variants and subclinical
atherosclerosis in a group of women with SLE and a control group.
Role of collagen in vascular calcification.
Mechanisms of Chinese Medicine in Gastroesophageal Reflux Disease Treatment:
Data Mining and Systematic Pharmacology Study.
CEMIP (HYBID, KIAA1199): Structure, function and expression in health and
disease.


CITING ARTICLES VIA

Web of Science (1586)
Google Scholar
Crossref


 * LATEST


 * MOST READ


 * MOST CITED

The promise and pitfalls of novel cuffless blood pressure devices

Long-term use of proton pump inhibitors and risk of diabetes mellitus: the
totality of the evidence does not support a change in practice

Left bundle branch area pacing in perspective

Phenotypical differences in the characteristics of a population affects both the
mortality and the performance of a risk-scoring model

Refitting the predictor variables included in a model in a new cohort usually
exaggerates its calibration performance



More from Oxford Academic
Cardiovascular Medicine
Clinical Medicine
Medicine and Health
Books
Journals


LOOKING FOR YOUR NEXT OPPORTUNITY?

University of Rochester Infectious Diseases Division Faculty position: HIV
vaccine clinical trials
Rochester, New York
Infectious Disease Physician
Brisbane, Other / Non US
POSTDOCTORAL FELLOWSHIP
Houston, Texas
Open Positions - Faculty and Director
College Station, Texas
View all jobs

Advertisement

Advertisement
 * Twitter
 * YouTube
 * LinkedIn


 * Online ISSN 1522-9645
 * Print ISSN 0195-668X
 * Copyright © 2022 European Society of Cardiology

 * About Oxford Academic
 * Publish journals with us
 * University press partners
 * What we publish
 * New features 

 * Authoring
 * Open access
 * Purchasing
 * Get help with access
 * Institutional account management

 * Accessibility
 * Contact us
 * Advertising
 * Media enquiries
 * Legal and policy

 * Oxford University Press
 * News
 * Oxford Languages
 * Epigeum
 * University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers
the University's objective of excellence in research, scholarship, and education
by publishing worldwide

 * Copyright © 2022 Oxford University Press
 * Cookie policy
 * Privacy policy
 * Legal notice



Close

Close


THIS FEATURE IS AVAILABLE TO SUBSCRIBERS ONLY

Sign In or Create an Account

Close

This PDF is available to Subscribers Only

View Article Abstract & Purchase Options

For full access to this pdf, sign in to an existing account, or purchase an
annual subscription.

Close