COMMENTARY

Hydroxychloroquine RCTs: 'Ethically, the Choice Is Clear'

F. Perry Wilson, MD, MSCE

Disclosures

August 05, 2020

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This transcript has been edited for clarity.

Welcome to Impact Factor, your weekly dose of commentary on a new medical study. I'm Dr F. Perry Wilson, from the Yale School of Medicine.

This week, I am going against the advice of my loved ones who feel my pain as I read some pretty rough comments online to try to address the hydroxychloroquine issue.

I know, I know.

Whenever I discuss hydroxychloroquine (HCQ), people come out of the woodwork to tell me what a bad doctor I am. Even when I made a video simply demonstrating how searching pubmed.gov works, I got some pretty rough replies.

But I guess I'm a glutton for punishment, so I've set out today to collect — in one place — the randomized trials that have been conducted that form the centerpiece for why doctors like me and Anthony Fauci don't think HCQ works for COVID-19.

Now, before we get started:

I am not paid by any pharmaceutical company, nor do I hold a patent on any drug or device. My grant funding comes from the National Institutes of Health (NIH) and the Department of Defense (DOD). My NIH studies have nothing to do with drugs. My DOD study, in fact, is looking at repurposing an old, cheap, relatively safe drug (valproic acid) for the treatment of a certain type of kidney disease. I literally study whether old, cheap drugs can be repurposed for new benefit.

Which is to say that I am really, really interested in cheap, effective ways to fight COVID-19. Because — another thing I have to remind people — I'm not just a clinical researcher; I'm a medical doctor who has spent months caring for COVID-19 patients in the wards of Yale New Haven Hospital. I don't know what else to say. I'm really just trying to synthesize the data we have.

Now, when you look for HCQ studies in COVID-19, you will find a ton — roughly 900 published at last count. The vast majority of these are observational studies.

Why do people like me put so much more weight in randomized controlled trials (RCTs) than observational studies? It's simple.


 

In an observational study, the observed effect of the exposure of interest (HCQ) on the outcome of interest is due to both its true causal effect and the characteristics of who was selected for treatment.

In a randomized trial, because the selection is random, the observed effect is due solely to the true effect of the treatment.

That's why we put so much stock in RCTs. Before RCTs are available, observational data are okay; we can use them to generate hypotheses. But observational studies should be used to design RCTs, and RCTs should be used to guide therapy. Hence my focus today on the extant RCTs.

But to illustrate, I'll give one observational example, since I think 100 people have emailed it to me in the past week.

This is one of Didier Raoult's studies, appearing in Travel Medicine and Infectious Disease. They report on 3737 patients with COVID-19. These were mostly outpatients, and the study states that, barring contraindications, they were prescribed 200 mg of HCQ three times a day for 10 days, with 5 days of azithromycin. They then compared the 3119 people who took that regimen for at least 3 days with 618 who didn't.

In the observational setting like this, the key question is, why did they not take the medications? Looking at Table 1 in the paper, we can see that at baseline, these groups are quite different.


 

Those who took the standard therapy tended to be younger; 53% were under age 44 compared with 36.4% who got the other treatments. They had less cancer, less diabetes, less chronic heart disease, and lower NEWS scores, which is a measure of disease severity. In other words, this was a group poised to do well. The treatment wasn't assigned randomly; it was given to the healthiest. That's not unethical or anything, by the way. It's totally reasonable to be careful about who you give drugs to. It just makes it harder to interpret the results.

And the results were better in the group who got the HCQ regimen: 0.5% death rate compared with 3.1% death rate.

From Lagier JC, et al. Travel Med Infect Dis. 2020;36:101791. doi:10.1016/j.tmaid.2020.101791

Now, you can adjust for baseline differences. Here, they adjusted for that severity score and comorbidity score — not age or anything else — and still found significance. But let me highlight two issues with adjustment.

First, adjustment isn't magical. You have to adjust for all the factors that are different at baseline to get an unbiased estimate of treatment effect.

Second, you don't know all those factors. You can only adjust for what you measure. Unmeasured differences in the groups will always be present, with one exception.

You guessed it. If you randomize, you will balance not only measured differences but even unmeasured differences between the groups.

That's why clinical epidemiologists like me get so psyched about randomization.

Hopefully, I've convinced you that randomization is where it's at. And with that, I will present the five peer-reviewed randomized trials that (to date) have been published on HCQ and COVID-19. I'll also review one preprint, since it's by the same group that did the dexamethasone study. We'll do them in published chronological order, then the preprint.

Caveat: I may have missed a trial here or there, and more are coming. We are never done learning; we just let the evidence make our conclusions more or less firm.

Study number one: A study appearing in the BMJ.

One hundred and fifty hospitalized patients in three provinces in China were randomized to receive either 1200 mg of HCQ for 3 days followed by 800 mg daily for 2-3 weeks or usual care. There was no placebo in this study. The groups were well balanced because this was a randomized trial.

The primary outcome was absence of virus PCR on nasal swab at 28 days; 85.4% cleared the virus in the HCQ group compared with 81.3% in the usual-care group — not a statistically significant difference, with a P value of .34.

From Tang Wei, et al. BMJ. 2020;369:m1849

The adverse event rate was 30% in the HCQ group and 9% in the usual-care group.

Study number two: A study appearing in The New England Journal of Medicine.

Eight hundred twenty-one asymptomatic patients with a high-risk exposure to someone with COVID-19 were randomized to receive HCQ 800 mg once, followed by 600 mg 6-8 hours later, then 600 mg for 4 days vs placebo. The groups were well balanced because this was a randomized trial.

The primary outcome was the incidence of COVID-19 at 14 days: 11.8% of those receiving HCQ vs 14.3% of those receiving placebo hit the outcome, a nonsignificant difference with a P value of .35.

© The New England Journal of Medicine (2020)

The adverse event rate was 40% in the HCQ group and 17% in the placebo group.

Number three: a study appearing in the Annals of Internal Medicine.

Four hundred ninety-one nonhospitalized adults with COVID-19 or high-risk exposure were randomized to the same regimen from that New England Journal of Medicine trial or placebo. The groups were well balanced because this was a randomized trial. The primary outcome was change in symptom severity at 14 days.

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