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Watch Dr. Anthony Fauci’s body language during this video.
He’s sitting on the famous White House sofa, and he’s on the edge of his seat. He’s speaking with a half-smile and exudes optimism. Typically, Fauci has been very reserved in his delivery, so there’s a palpable difference here. Clearly, he’s excited to share this big news coming out of his organization, the National Institute of Allergy and Infectious Diseases.
What’s the news? It’s about remdesivir, an antiviral drug first created to work against Ebola that works by preventing viruses from replicating themselves within the body. On Wednesday, we learned that remdesivir has shown some effectiveness against the virus that causes COVID-19 in a large-scale study.
In particular, the study was done on 1,063 patients with advanced COVID-19. Some of the patients randomly got a placebo, while some got remdesivir. Those who got the drug recovered in an average of 11 days, while those who got the placebo recovered in an average of 14 days.
Researchers determined that finding has a P-value of less than 0.001. What’s a P-value? I’m so glad you asked.
A P-value is the odds of the numerical differences of a study happening by random chance if, in reality, there were no difference in the two groups.
Let’s say you were conducting a study on weather. You wanted to know if Tuesdays were typically warmer than Mondays, cooler than Mondays, or about the same as Mondays. So one week, you go outside and measure the temperature on Monday, and it’s 68 degrees. On Tuesday, you go outside, and it’s 72 degrees.
Does that prove that Tuesdays are typically warmer than Mondays? No! You only have one test from each category. Even if you find this result for a whole month, you still don’t really know for sure: you could have just gotten a string of a few warm Tuesdays. The odds of randomness playing the key role are still too high, and so the P-value in your study would be high also.
But if you went outside on 1,063 consecutive Mondays and Tuesdays and found that Tuesdays were still consistently warmer, you’d probably be on to something significant. Over the course of 20 years of Mondays and Tuesdays, the chances that randomness is the major reason for the difference is low, so your P-value would be low also.
That the P-value in the remdesivir study is less than 0.001 makes it extremely unlikely that randomness alone is the reason that the study showed that patients treated with the drug get healthy faster than those on the placebo. That’s extremely good news and explains Fauci’s excitement.
In general, scientists have to decide what P-value is low enough to say that their hypothesis is probably true, or when they have to slow down and say “well, we just don’t know enough yet.” The industry standard is typically a P-value of 0.05 — then we feel pretty confident about it.
I bring all of this up because the remdesivir study had another goal besides finding out if remdesivir helped people recover faster. They also wanted to know if remdesivir saved people’s lives.
The news was good there, too. Of those who got remdesivir, 8% died. Of those who didn’t, 11.6% of people died.
That finding only had a p value of 0.059, though — just a little bigger than the 0.05 cut off. Reportedly, one reason was because once they found that remdesivir was working to some degree, they wanted to give it to some of the placebo people late in the trial to try to save their lives. That decreases the sample size. As a result, the study merely “suggested” that remdesivir saves some number of lives compared to a placebo. That’s terrific if true, but we’re less certain about it.
There are caveats here, though.
First: a smaller Chinese study of 237 patients did not find statistically significant differences with remdesivir in either category. While that study did find the patients recovered slightly faster on average (21 days vs. 23 days for these participants), it wasn’t enough to be statistically significant. And the death rates stayed nearly identical: 14% of people on remdesivir died, compared to 13% on placebo.
I’d probably trust the bigger American study more, but it shows just how difficult studying this can be. We’re going to get more and different kinds of studies on the effects of remdesivir in May.
Second: remdesivir is not an easy drug to administer or receive. It is delivered intravenously over the course of several days. It also has significant side-effect risk, including potentially gnarly liver damage.
We also don’t know whether it is more effective, less effective, or ineffective on people earlier on in the process. Given the side-effect profile, you may not want to give remdesivir to everyone who tests positive.
Third: it’s going to be difficult to produce a ton of it. It’s owned by the American biopharmaceutical company Gilead, so any other manufacturers would have to license it from them at likely an incredibly high cost. In January, Gilead only had enough remdesivir on hand to treat 5,000 people, and now is only up to 50,000. We’re at 3.2 million coronavirus cases worldwide so far. (One other study released Wednesday showed that it didn’t matter much if the patient received the drug for five days or 10 days, however, so that effectively doubles our number of doses.)
As Stat News explains, getting the raw materials for the drug can be complicated: most active ingredients come from India or China, so getting them in a pandemic when everyone knows those ingredients are critical is tough. Scaling up drug manufacturing is a slow process in general.
Remdesivir isn’t a super-complicated drug, but because it is owned by just one company, it’s also likely to be expensive — especially in America.
I should also note that 8% vs 11% mortality and 11 days vs. 14 days aren’t huge leaps, though obviously every bit helps.
More than anything, this study was proof-of-concept: for the first time, we have some drug that almost certainly does something useful against COVID-19. There’s also optimism that we can improve how we give people remdesivir, and perhaps mix it with other helpful drugs to boost the effect. Some of those studies are ongoing as well.
As Fauci put it, “When I was looking at the data with our team the other night, it was reminiscent of 34 years ago in 1986 when we were struggling for drugs for HIV. We did the first randomized, placebo-controlled trial with AZT. It turned out to have an effect that was modest — but that was not the endgame because, building on that, every year after, we did better and better."
Remember, Fauci built his reputation as perhaps the top researcher in the HIV/AIDS epidemic.
Is this remdesivir information an immediate game changer in the COVID-19 pandemic that we now face? Not a huge one. But it’s evidence that we’re beginning to tilt the playing field just a little, that something we’re doing is definitely working.
That in itself is a reason to get on the edge of your seat and smile.