Remdesivir in adults with severe Covid-19: random, double-blind, placebo trial
thelancet.com
thelancet.com
That said, this morning Gilead reported that in their own pivotal trial that the drug met it's primary endpoint.[1] What we don't know is how big of an effect it was.
[1]https://endpts.com/gilead-pivotal-covid-19-study-of-remdesiv...
“Not statistically significant” does not mean the effect does not exist. It means that the study provides weak evidence, but weak evidence ≠ no evidence. It tags things for further study.
This is one of those cases where people get too hung up on P values. You have to look at the bigger picture; look at the entire scientific process.
It may provide evidence of other hypotheses.
So you're right, but you're also wrong, without making yourself more clear.
Poor precision in the use of language around clinical data has been a major problem in all of this, in the press especially, where for the most part they clearly don't give a damn and just have an agenda to spin in most cases. Because of this, scientists publishing ought to try to use language that ensures their work cannot be misinterpreted. The notes in the results section here about non-statistically significant aspects to the data fail that test, since an average reader would likely walk away with a false mental model of what the data is showing.
edit: my comment is wrong, i'm tired and haven't had enough coffee. the criticisms below are valid. i do have a point, but won't jam it in here.
Again, this is incorrect. It provides weak evidence, not no evidence. You talk about precise language here but you are conflating “not statistically significant” with “no evidence”. You can’t just handwave the difference between these two things.
It does provide some evidence: we are more likely to see this result in a world where the hypothesis is true than a world where it is false.
This is a heuristic which helps things stay within our limited reasoning capacity, cuts down on the noise level from all the activity in the scientific community to focus on what's important, and helps with inherently binary organizational decisions (e.g. should this experiment be published in a journal or not? Should we give this medicine to patients or not?)
A better approximation of optimal Bayesian reasoning would be continuous updating of your prior with no cutoff. Even a study with a very weak p-value in the right direction should in theory slightly tweak your priors in favor of the hypothesis. (But you also have to tweak slightly against the hypothesis for studies with very weak p-values in the wrong direction, and compensate for selection effects, e.g. if experiments with underwhelming or wrong-direction p-values are underpublished.)
Even weak p-values below the binary decision threshold contain information. It's just that effectively denoising and acting on that information is more difficult and fraught with pitfalls than binary decisions based on strict thresholds. So science mostly standardizes on the safer approach, although there are some people who try to wring precious drops of information out of experiments that fall below the usual statistical cutoffs (often by so-called meta-analysis that combines results of multiple studies).
But the binary decision “let’s use drug X to treat condition Y”, and the binary decision “let’s investigate the efficacy of drug X on condition Y” each come with radically different tolerances for type I and type II errors.
In general, when less data is available, larger p values are considered more interesting, while when more data is available, p must be smaller to be interesting. In particle physics, p < 0.001 means almost nothing. In the particular quoted line, p = 0.07ish which is above the human-defined, conventional threshold of 0.05 but in this case there are almost no other useful data and so the phenomenon is interesting.
For example, statistically chocolate doesnt cause acne. Yet I 100% get acne from chocolate.
There is enough variance in people that many things that work anecdotally cannot be proven statistically.
My barely informed interpretation and resulting take here is that:
1) This really only shows any efficacy when given shortly after the onset of symptoms
2) Remdesivir is an expensive and IV only drug that is difficult to produce in high quantities
3) The combination of the above makes this not particularly useful for treating the general population - we do not want everyone that shows mild symptoms to be rushing to the doctor for a treatment that has to be provided by a professional, and by the time we know if the symptoms will be severe and life threatening it is too late for remdesivir to be useful
4) That would seem to make it most useful for people that have known risk factors and co-morbidities to be candidates for remdesivir use. I do not know if the results are similarly promising for people that have those criteria, however.
If these results hold up it's good news, but I don't know if it's great news - it seems like the factors involved here make it impractical for the large scale treatment of cv19
My take: sounds like great news for a product, since everyone would want this on hand to catch infections early. Unfortunately it is an IV treatment and very difficult to manufacture, and is therefore unlikely to be able to fill that role. I bought a few shares anyway.
Both the Raoult protocol and remdesivir appear to help if used earlier in the disease progression; neither seem to do anything if the disease has progressed past a certain point.
If early use is the key to efficacy (and if both demonstrate the same degree of efficacy, as it seems currently), the Raoult protocol is the only one that makes sense to scale up. The ingredients for the Raoult protocol are much more easily mass-produced and administered, whereas remdesivir is proprietary, very expensive, and IV-only (as other posters have noted).
Does remdesivir work on coronavirus in a similar fashion?
Tamiflu blocks influenza viruses from being released from its host cell (https://en.wikipedia.org/wiki/Neuraminidase_inhibitor)
Remdesivir interferes with viral replication itself (https://en.wikipedia.org/wiki/Remdesivir)
For those versed in organic chemistry: looks pretty complicated. Maybe someone with industry experience can guess how difficult this is to productionize on a global scale?
https://en.m.wikipedia.org/wiki/File:Synthesis_of_Remdesivir...
https://www.acsh.org/news/2020/03/26/problem-remdesivir-maki...
[1] https://www.fiercepharma.com/manufacturing/gilead-to-donate-...
There is newer, positive data coming out today from the ongoing study of advanced covid: https://www.niaid.nih.gov/news-events/nih-clinical-trial-sho...
"In this study of adult patients admitted to hospital for severe COVID-19, remdesivir was not associated with statistically significant clinical benefits. However, the numerical reduction in time to clinical improvement in those treated earlier requires confirmation in larger studies."
From the findings section: Although not statistically significant, patients receiving remdesivir had a numerically faster time to clinical improvement than those receiving placebo among patients with symptom duration of 10 days or less (hazard ratio 1·52 [0·95–2·43])
In other words, the patients that were going to get better, got better regardless of if they got the drug or not. However, those that got the drug got better faster than those who got the placebo (but as gfodor points out, not a statistically significant change, but a trend).
This was the trial with patients with severe disease, so there is still a decent amount to be learned about potential for effects earlier in treatment. But there are other ongoing studies for earlier timepoints.
https://www.gilead.com/purpose/advancing-global-health/covid...
This is actually quite well known when treating the flu with anti-virals. My doctor has said in previous years, if I wake up with full body ache and feel like it's the flu, come in immediately and he'll prescribe anti-virals. He said if I wait, there's no point, though.
Makes sense the anti-virals might only be enough to stop viral replication if given early on before it's all over the place.
Edit: Also it looks like they didn’t find an effect overall, but if they slice the data to just those who were treated early, they’re closer to having something stat sig. Hopefully that was a pre-planned cut of the data, but either way the interpretation is still probably “Somewhat promising but needs more data.”
This happens a lot with covid drug research. Many times treatments given too late have no effect on improving outcomes. That is, if you give it too late, it cannot save you. However, there does appear to be some drugs that improve outcomes when given early in disease progression. Think of it like tamiflu. If you take it 2-3 days post onset, it works. If you take it past that timeframe, it does not work.
However they found exploratory results in the data that they think deserve further study.
Antiviral drugs won't reverse damage that's already done.
That's something.
People want to talk about this stuff because it feels like a magic bullet. Viral infections don't have magic bullets[1], they just don't. We have to beat this with elbow great: huge amounts of testing and tracing once the outbreak is at a manageable baseline, and high uptake of mitigation strategies like social distancing until it gets there. And yes, that costs a lot of money.
[1] Rather: they do, but they're called vaccines and take time.
So, by definition, we will only have unproven drugs to use for the foreseeable future.
But in the legal sense, my impression is that FDA never approves anything in under 2 years. Happy to be proven wrong!
They do. Consider HIV/AIDS. Nowadays, someone who gets HIV-positive at the age of 20 can expect to live to 70. It's quite astounding what modern combination therapy can do.
That is, I believe the prior indication was fairly low to null that antiviral drugs would significantly help the treatment of a severe respiratory infection -- in the first place. You don't give someone Tamiflu when they have a sufficiently severe flu pneumonia and fever to be hospitalized, do you?
Antivirals are usually indicated for treatment when an infection is still in its early, mild, pre-hospitalization stages. I understand that it's easier to recruit study subjects with severe COVID-19 than mild at this stage, but still, doesn't this study amount to looking for one's keys under the lamp-post because it's brighter there?
> White House health advisor Dr. Anthony Fauci said Wednesday that data from a coronavirus drug trial testing Gilead Sciences’ antiviral drug remdesivir showed “quite good news” and sets a new standard of care for Covid-19 patients.
> Speaking to reporters from the White House, Fauci said he was told data from the trial showed a “clear cut positive effect in diminishing time to recover.”
[1] https://www.cnbc.com/2020/04/29/dr-anthony-fauci-says-data-f...
It also means this isn't any sort of "miracle" drug though.
I hope other viable treatments emerge from the other trials on drugs set to close by June.
My wife became symptomatic with COVID-19 about a month ago. For the first ~8 days, she was in pretty rough shape, although happily she didn't need hospitalization. But the pace of recovery is slower than I've seen with any flu. She still needs to significantly limit her activity or else her pulse gets high and she gets short of breath. (The effect is much greater than you'd expect from someone being bedridden for 8 days.)
Each day is a little better, so hopefully she'll make a full recovery. But if I had to spitball a linear extrapolation of when she'll be back to 100%, I'd say another few weeks at the soonest.
Obviously we'd rather have a drug that saves lives and/or prevents long-term disability. But if remdesivir could have hastened my wife's recovery by several weeks, our kids and my professional work would have been much better off.