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DATA SHOW PANIC AND DISORGANIZATION DOMINATE THE STUDY OF COVID-19 DRUGS

By Matthew Herper @matthewherper and Erin Riglin

July 6, 2020

Reprints
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Molly Ferguson for STAT
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In a gigantic feat of scientific ambition, researchers have designed a
staggering 1,200 clinical trials aimed at testing treatment and prevention
strategies against Covid-19 since the start of January. But a new STAT analysis
shows the effort has been marked by disorder and disorganization, with huge
financial resources wasted.

The analysis, conducted in partnership with Applied XL, a Newlab Venture Studio
company, found that one in every six trials was designed to study the malaria
drugs hydroxychloroquine or chloroquine, which have been shown to have no
benefit in hospitalized patients.

“If the goal was to optimize the likelihood of figuring out the best treatment
options, the system is off course,” said Robert Califf, the head of clinical
policy and strategy at Verily Life Sciences and Google Health and a former
commissioner of the Food and Drug Administration.  The findings show, he said,
that too often studies are too small to answer questions, lack real control
groups, and put too much emphasis on a few potential treatments, as occurred
with hydroxychloroquine.

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Indeed, the analysis found many of the studies are so small — 39% are enrolling
or plan to enroll fewer than 100 patients — that they are unlikely to yield
clear results. About 38% of the studies have not actually begun enrolling
patients.



“It’s a huge amount of wasted effort and wasted energy when actually a bit of
coordination and collaboration could go a long way and answer a few questions,”
said Martin Landray, a professor of medicine at Oxford University and one of the
lead researchers on the RECOVERY study, a large trial of multiple treatments
being run by the U.K. government.

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Not all effort has been for naught. Three of the most important conclusions
about Covid-19 treatments so far have come from the RECOVERY trial. It has shown
that dexamethasone, an inexpensive steroid, reduced the death rate of Covid-19
patients on ventilators by a third. It has also demonstrated that neither
hydroxychloroquine nor a pair of HIV drugs, lopinavir and ritonavir — which had
shown some early promise in laboratory models of the disease — benefit
hospitalized patients with Covid-19.

Still, experts say the analysis shows that huge amounts of energy have been
expended on haphazard efforts, often without a clear strategy to improve the
odds that results would actually inform the care of patients. Faced with intense
pressure to develop drugs and vaccines at previously unimaginable speed to push
back a global pandemic, researchers may have actually slowed down the rate of
progress.


For instance, 237,000 patient volunteers were to be enrolled in studies of
hydroxychloroquine or chloroquine. That’s 35% of the 685,000 patient volunteers
whom researchers hoped would be enrolled in any study. Since patients willing to
enter studies are one of the scarcest resources in medicine, this means that
other potential treatments, such as ivermectin or favipiravir, were not studied.

That’s “excessive,” said Susan Desmond-Hellmann, former CEO of the Bill and
Melinda Gates Foundation. She noted that vaccines, in contrast, are being
developed in a more methodical way — and wished that research on new drugs had
been more organized, rather than simply trying whatever was available.

Related:


THE BIOTECH SCORECARD FOR THE THIRD QUARTER: 14 STOCK-MOVING EVENTS TO WATCH

The data for the new analysis come from clinicaltrials.gov, the U.S. government
database.

AppliedXL analyzed the data to identify trials that explicitly studied Covid-19
therapies and prevention strategies. The analysis focused only on interventional
clinical trials, which study potential treatments or preventatives for disease.
More than 880 observational studies have also been started, according to the
analysis. For trials that test multiple treatments, the entire study enrollment
was counted for each drug. (For more details on the methodology used in the
analysis, see here.) 

The analysis reflects the data as of June 24. In the days before this article
was published, approximately 20 Covid-19 studies were added to the database each
day.



The clinicaltrials.gov database is known to contain routine errors, oversights,
and omissions, and researchers in both industry and academia often fail to
update trial listings. As a result, the analysis itself involved some degree of
subjectivity. But the general conclusions — both about the scale of the research
and its limitations — seem indisputable.

Nahid Bhadelia, medical director of the Special Pathogens Unit at the Boston
University School of Medicine, called the data “a cry for greater global
collaboration during pandemics.”

America’s research infrastructure mobilized quickly when the pandemic began. In
January, 10 studies were to be started, followed by 43 in February and 99 in
March. In April, almost 400 studies for dozens of different treatments and
preventatives were to begin, according to the database.

The sheer speed with which the studies were started was remarkable. And experts
said the start of some small studies, particularly of new, experimental drugs
that were previously being tested in other diseases, makes sense as a way of
figuring out what might work. But such “phase 1” studies represented only 12% of
the total in the analysis.

Experts added that, because the prognosis for patients with Covid-19 varies so
dramatically — some patients have no symptoms, while others die on ventilators —
only large studies that randomly assign patients to a treatment or placebo can
deliver real insight into whether or not medicines are actually helping
patients. Otherwise, researchers are fooled into thinking that differences
between groups of patients with varying degrees of illness are caused by the
medicines they are testing.

The RECOVERY study took a unique approach. In order to run such a large study,
the researchers stripped down the amount of data collected on each patient —
focusing mainly on whether patients lived or died — so that frontline
researchers would be able to collect the data. More important, they got buy-in
from the U.K.’s National Health Service that such a study was a priority. 

Repeating that model, experts agree, would teach doctors more about how to treat
Covid-19, and do so much faster.

“If more people took the RECOVERY model, or something like it, did that for the
drugs they were interested in, in the patients they’re interested in, in their
part of the world … we make progress an awful lot quicker,” said Landray.

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Clinical trials can routinely cost $10 million or more, with some studies
costing hundreds of millions of dollars. But Landray says RECOVERY was funded by
a grant of about $2.5 million to the center coordinating the study, although
costs at hospitals could push the total higher.

In fact, of 1,200 studies, almost all the certain knowledge — and the proof that
two treatments are effective — has come from two: RECOVERY and a study conducted
by the U.S. National Institutes of Health that showed Gilead’s intravenous drug
remdesivir speeds the time it takes for hospitalized patients to recover from
Covid-19.

Data collected by AppliedXL and STAT show that researchers had little interest
in studying dexamethasone, the only medicine shown to save the lives of Covid-19
patients. There have been seven studies of the drug in all, enrolling 13,600
patients, 12,000 of whom were in RECOVERY. Two other steroid drugs, prednisone
and methylprednisolone, are being studied in another 2,500 patients.



The experience with hydroxychloroquine illustrates how the research enterprise
became so lopsided and unfocused. In February, hydroxychloroquine was one of
several medicines that showed promise in cell cultures as a potential antiviral
treatment for the virus. Although none of these medicines was designed
specifically to combat SARS-CoV-2, the coronavirus that causes Covid-19, there
was real reason to hope one might work as an antiviral treatment to either help
infected patients or prevent infection.

Early results from researchers in France ignited interest in the drug in March,
even though they were not drawn from a randomized trial. On March 19, President
Trump, at a press conference, said that hydroxychloroquine had “shown very
encouraging — very, very encouraging early results,” and promised “we’re going
to be able to make that drug available almost immediately.” The watchdog group
Media Matters said that between March 23 and April 6, guests and hosts on Fox
News mentioned the medicine nearly 300 times.


Huge donations of hydroxychloroquine and chloroquine were made by generic
pharmaceutical manufacturers to a national stockpile of the drugs, leading the
Food and Drug Administration to grant emergency use for its use in hospitals on
March 28.



By early April, 58% of patients hospitalized with Covid-19 were receiving the
drug, triple the level in February, according to CarePort Health, which collects
drug utilization data from electronic medical records. 

Instead of conducting studies that were large enough and well-designed enough to
find out if hydroxychloroquine or chloroquine could prevent or treat Covid-19,
many doses went to studies without control groups, essentially tracking the use
of the medicine in hospitals. 

On Saturday, the World Health Organization said its own large study had found no
benefit for either hydroxychloroquine or lopinavir-ritonavir. It’s still
possible that one of the ongoing studies of hydroxychloroquine will show a
benefit, perhaps earlier in the disease.

“The lack of leadership around a clinical trial agenda in the US is one of the
failures of the US’s pandemic response,” said Walid Gellad, director of the
Center for Pharmaceutical Policy and Prescribing at the University of
Pittsburgh. “If we had taken the U.K.’s strategy of a set of large pragmatic
trials, prioritizing recruitment in those trials, we could have all the answers
now that we’re waiting for.” 

U.S. researchers rushed quickly into the battle against Covid-19. What was
missing, it seems, was a general who could direct them in the fight.

Francesco Marconi contributed reporting. Joanna Lin Su contributed visuals.

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ABOUT THE AUTHORS REPRINTS


MATTHEW HERPER

Senior Writer, Medicine

Matthew covers medical innovation — both its promise and its perils.


matthew.herper@statnews.com

@matthewherper


ERIN RIGLIN


erin@newlab.com


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 * Siegfried Othmer says:
   July 6, 2020 at 1:50 pm
   
   Underlying this piece are certain assumptions about research design, making
   the case once again for targeted research that is sufficiently powered. The
   opposing case needs to be argued with equal vigor. We are in a complex
   variable space, and we are fighting exponential growth on three fronts:
   spread of the vector in the population; viral growth in the affected
   individual; and exponential growth of the counter-measures — the cytokine
   storm.
   
   All these call for early interventions, before each of these problems becomes
   unmanageable. Two of them fall in the realm of public health—the realm of
   prevention—and only one of them is in the class of medical remedies that
   should be subject to tightly specified research designs.
   
   For the other two, complexity is inherent in the situation. It must be
   confronted forthrightly, and it should be met with numerous independent small
   studies, just as is presently happening. The results are then distilled by
   way of data-mining across studies. Whether formally or informally, with
   respect to prevention strategies we find ourselves in a Bayesian universe.
   
   We should be focusing on prevention with almost paranoid intensity. This is
   where hydroxychloroquine fits (in combination with zinc), as well as
   ivermectin, each in combination with an antibiotic to ward off opportunistic
   infections. This is the place for bottom-up scientific discovery and early
   sifting through clinical pipelines.
   
   Reply
   * Happy Cow says:
     July 6, 2020 at 2:00 pm
     
     Why does hydroxychloroquine fit into a preventative strategy better than a
     vaccine (genuinely curious, not trying to argue)?
     
     It seems like the more prevantative a solution becomes, the larger the
     study needs to be to have correct power and prove benefits outweigh risks.
     This would seem to suggest larger, more expensive studies and good
     coordination would be needed for that.
     
     Also, I keep seeing people criticizing studies for not focusing on early
     treatments, where is the evidence that this is the correct approach?
   
     
   
 * Mark says:
   July 6, 2020 at 12:17 pm
   
   Yes, coordination would be better. However, there is money to be made in some
   instances, so the idea that national and commercial interests will not be a
   factor is not what happens in the real world. Also, randomization that is not
   based on known stages of the disease will arrive at the wrong conclusions.
   Stat keeps making this error too, just as the trials can.
   
   Reply
   * Siegfried Othmer says:
     July 6, 2020 at 4:41 pm
     
     Response to Happy Cow: HCQ and ivermectin are ‘bird-in-hand’, so that is
     better than a non-existent vaccine. We’ll have a dynamic situation for some
     time to come. As for preventive solutions calling for even larger studies,
     several responses: First of all, these old drugs are already well-known
     quantities in other contexts. Secondly, patients tend to respond quickly,
     so the clinician can discern whether the drug is actually helpful for a
     particular patient, and also whether the dose needs to be adjusted.
     Statistics of responding are then accumulated over time. Further, the
     criticality of timing and the diversity of clinical presentations makes
     this situation totally unsuitable for classical research designs.
     
     Where is the evidence that this strategy is actually being successful? This
     is how the death rate has been reduced in ICUs, for example. It did not
     happen because of any research. It happened by clinicians sharing their
     insights with each other, one clinical anecdote at a time. Trial-and-error
     learning is the appropriate response to the encounter with a complex
     system. Formal research designs cannot function on the timescale at which
     we actually have to solve our current problems.
     
     The large-scale outcome study in France put HCQ plus zinc plus Azithromycin
     firmly on the map. The results cannot be explained away with arguments
     about lack of controls with random assignment. But that also does not mean
     we have nothing better… the exploratory research continues.
     
     Prevention strategies are inherently handicapped when it comes to proof.
     Consider, for example, the Covid-19 disaster that is not happening in most
     of Africa. That could be for a number of reasons, but it could also be
     because chloroquine is already well established there.
   
     
   

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