Fluvoxamine

https://lockdownsceptics.org/tag/fluvoxamine/

Do the NIH and WHO COVID treatment recommendations need to be fixed?

The case for fluvoxamine

The WHO is so out of touch with the latest research that fluvoxamine hasn’t even made it on to its list of potential drugs to treat COVID:

Go to c19early.com and look at the chart. Fluvoxamine is the #1 approved drug on the list. It’s cheap, safe, widely available, and effective. But it doesn’t even merit inclusion on the WHO list. I tried to bring this omission to their attention, but they requested I stop bothering them.

The NIH is better; it is listed on the NIH’s COVID Treatment Guidelines, and the NIH  knows that there have been two quality randomized trials done by top US researchers (one trial was a DB-RCT, the other was quasi-randomized which the NIH categorizes as “observational” but that’s a debate for another op-ed), both were published in peer-reviewed journals, and both papers were given a prestigious “Editor’s Choice” designation.

In other words, fluvoxamine has something that ivermectin and HCQ both lack: two quality studies, done by highly respected researchers associated with top-quality institutions, published in top peer-reviewed journals, both studies had statistically significant results on a critical clinical endpoint (hospitalization), both were an interventional trial, both were randomized, and both studies were highlighted by the editors. It is for these reasons that the mainstream scientific community believes that the case for fluvoxamine is superior to the case for ivermectin and HCQ. 

Of the most respected scientists I know, 100% would choose fluvoxamine in a heartbeat over the other two drugs if they got COVID and had to pick a treatment based on the evidence available today. A top medical school looked at fluvoxamine and other options and the consensus was that the case for fluvoxamine was clearly the strongest. I also know of a DB-RCT study, not yet published, which compared the efficacy of fluvoxamine against ivermectin and fluvoxamine had the greater benefit by far.

The consistent superior rating by mainstream scientific experts is important because if a country adds ivermectin and/or HCQ to their treatment recommendations, then adding fluvoxamine should be a “no brainer.” Unfortunately, this isn’t the case today, anywhere in the world. However, the FLCCC did add fluvoxamine to their early outpatient treatment guidelines based on the evidence and the experience with doctors all over the world with the combination.

The first fluvoxamine study (Lenze), published in JAMA, had 100% effect size in protecting against hospitalization criteria defined as respiratory distress (since that’s what most people get hospitalized for and they didn’t want to count it if you got hit by a truck and got hospitalized). None of the 80 patients on fluvoxamine met the clinical endpoint vs 8.3% of the 72 that got the placebo. That’s an effect size of 100%, i.e., impossible to beat.

But, the numbers were small and the study was deemed as “hypothesis generating.”

One professor noted that “the authors of that study concluded that their results were more hypothesis-generating than a clear call that this is an effective treatment.” Well of course! If you don’t say that in your paper, you can’t get it published in JAMA. Do the authors really believe that? Of course not. But you’ll have to take my word on that part because if you ask them publicly, they will toe the party line and say exactly what they are expected to say.

The JAMA paper didn’t generate a hypothesis that fluvoxamine might work for COVID. The hypotheses were generated by many independent researchers who looked at the SSRI data and noticed that these people had a remarkably lower rate of hospitalization and death than their matched peers. And the Washington University study itself was based on a University of Virginia study demonstrating that fluvoxamine reduces inflammation in sepsis. Dr. Reiersen speculated that it might work in COVID. She generated the hypothesis and she created the study that confirmed her hypothesis. So we didn’t just get lucky here… the JAMA study confirmed hypotheses made by others from three different countries using different studies.

What is even more remarkable is that, in the fluvoxamine confirmation study by Dr. Seftel at Golden Gate Fields which started the day after the JAMA paper was published, patients were able to choose whether they were treated with the drug or not and the sicker patients opted for the drug. Also, there were eight patients who initially rejected treatment, developed symptoms, and then asked to be placed in the treatment group. So this trial wasn’t random: it was WORSE than random; we should have expected that the treatment group would have really bad outcomes because of this bias. 

But the opposite happened: 100% of the 77 patients who received the drug recovered to normal in an average of 3 days and demanded to get back to work vs. a 12.5% hospitalization rate of the patients who refused treatment. That’s a p-value of .0026. 

Therefore, anyone who dismisses this study by saying “it wasn’t randomized” is missing the point. The results of this trial are stronger than the JAMA results: the p-value is stronger, the randomization was more “challenging”, and the physician had direct access to every patient. Also, the drug was administered promptly after the PCR test came back positive, a key factor in the 100% success of the trial.

So now we have two studies with 100% effect size, each with p value <.01. What do you think the chances are that it won’t be confirmed in a phase 3 trial? I’d say there are basically only two chances it won’t be confirmed: slim and none.

But here’s the more impressive observation that was noted in the Seftel paper that NOBODY looked at is that none of the 77 patients treated with fluvoxamine developed any long-haul COVID symptoms compared to 60% of the patients in the no-treatment group. Nobody has yet stepped forward to successfully explain, if the drug doesn’t work, how this could occur. It certainly wasn’t likely to happen by chance. The odds  of it happening by chance is 1 in 1014, i.e., next to impossible. There is no statistical fragility here. This is an impossible result if the drug doesn’t work. 

Lastly, Dr. Seftel used a dosage of the drug, 50mg BID x 14d, that is one-third of the FDA authorized dose (and the maximum dose used in the Lenze study). Even with such a small dose, patients uniformly were better in 24 hours and most were back to normal in 3 days. The lower dosing was extremely well tolerated with no reported side effects from the drug. Zero.

So to summarize so far, we have an inexpensive drug with a 37-year safety record, given at 1/3 the FDA authorized dose that has no side effects (for the vast majority of patients), that was 100% effective in preventing hospitalization, death, and any long-haul COVID symptoms. What’s not to like about that? If there is an approved drug that has multiple high quality studies, all statistically significant clinical endpoints with better results, we should use that. If not, why shouldn’t we be giving people fluvoxamine now? 

And then there is the data from docs who have been prescribing it. They uniformly say it works like magic. Not a single doctor who starts prescribing it stops (and I’ve seen them stop other drugs that they try and don’t work so I know they are tough to persuade). For example, Dr. Amol Kothalkar, a physician in the Buldhana district of Maharashtra, India has been using fluvoxamine in his practice for months and he swears by it and has told me on more than one occasion it is unethical for doctors not to prescribe this medication for COVID. Dr. Kothalkar is unusual because he gets regular blood work on his COVID patients so he can see the cause-and-effect between the start of fluvoxamine treatment and the rapid normalization of CRP. He knows that if can treat patients sufficiently early in the virus, all recover quickly, none are hospitalized or end up with long-haul COVID.

There is no evidence at all fluvoxamine makes COVID worse, and no doc has reported it doesn’t work. There are no neutral or negative anecdotes. There is no data you get better results by waiting. There is no data the drug benefit/risk ratio is <1 for younger patients. Indeed, all the evidence we have so far shows it helps kids very quickly kick the virus; doctors are stunned by the effect.

My favorite story involves  the workers at the racetrack who at first didn’t opt in for the fluvoxamine… only about 40% followed the doctor’s advice to take the drug. But two weeks later, when the employees could see the stark contrast between the two cohorts, 100% of the employees who later got sick demanded they be put on the drug. Even the track management, who weren’t sick, asked for fluvoxamine prescriptions so in case they got sick, they could start treatment immediately. So the effect was so large, it was crystal clear to these non-experts whether the drug was working. They were not swayed by any particular analysis or study indicating a lack of bias or p-values. The reason this is significant is that because it was clear to everyone, even those not involved in the study at all (the track management), that the drug worked, it means that there wasn’t bias on behalf of the doctor.

So my question is, how can this be obvious to 100% of the workers at the racetrack that the drug works, yet the experts at NIH–with access to all the data–simply cannot figure out whether the drug is likely to work or not?

Of course the NIH would argue that they are being careful because these results could happen by chance. 

Sure, all of these positive results could happen by chance… I acknowledge that there is a 1 chance in 1014 this outcome occurred by chance, but for all practical purposes, it is impossible for this to happen “by chance.”

My point is that the statistical certainty that the drug works is well beyond that required by scientists in any normal conditions. We effectively have two randomized studies with p<.01, which is more than adequate for a positive recommendation and we have an extra gift: the symptom data with p<10-14.

I’ve discussed these results with data scientists who tell me “it’s IMPOSSIBLE that the drug doesn’t work” (and then they quickly clarify that “impossible” means the chance it doesn’t work is extremely small). So to me, it is more than ridiculous that fluvoxamine has a NEUTRAL recommendation from the NIH (and not even mentioned by WHO).

I will happily retract my claim that the NIH got it wrong here if anyone at the NIH can come up with a bias or confounder that can explain the results that Seftel observed if it wasn’t the drug. It wasn’t observer bias since everyone saw the same miraculous difference and reacted the same way. And it wasn’t because the drug is anxiolytic because, when you remove anxiety from the list of symptoms, it doesn’t change the numbers. And the patients couldn’t know who was not going to be sick because if they knew that those patients would have chosen no treatment! And it wasn’t a placebo effect because there isn’t one for COVID that can eliminate all hospitalization risk and long-haul symptoms (think about it: if there was one, then everyone who enrolled in any arm of a DB-RCT would recover in 3 days and nobody would get long-haul symptoms). And finally, it couldn’t be anything about the drug itself reducing symptoms during the study because 4 months after they stopped using the drug, the treated patients still had no long haul COVID and the group that refused the drug was still suffering. All of this is verifiable but nobody has been interested in checking it out even after I offered $1M to anyone who could prove that the effect was caused by something other than the drug

When the Covid Early Treatment Fund applied for an EUA we got rejected by the FDA saying our evidence was insufficient to get an EUA (which is a very low bar because it only requires that the FDA believes that there is evidence that the benefits outweigh the risks). So how do they explain how the Seftel study got such an amazing result? They don’t. They just totally dismissed it with a hand-waving argument that there could be observer bias or randomization issues. That’s just not plausible, but you don’t get to argue with them.

Since the world is desperately looking for a magic pill that treats COVID infections, you’d think the entire world (especially India and Brazil) would be focused on verifying whether Seftel’s study was valid or not, because if it was, we’d already have the answer: a cheap, safe pill with remarkable efficacy. So when this “miracle at the racetrack” happened, why didn’t world governments and the mainstream press get all over this either to confirm or disprove it? If they confirmed it, it would be the story of the decade. Other than 60 Minutes, nobody in the mainstream media has bothered to look into it (and we even enlisted the aid of multiple PR and media experts, including an Emmy award winning reporter, to do the outreach to the press). I note that 60 Minutes didn’t discover anything amiss or it would have been a very different story. Is investigative journalism dead? The response we got was that people were too busy to look into it and they would prefer to wait for the Phase 3 trial which will likely take another six months to complete enrollment. For an investigation that could be completed in a few days, waiting six months seems like the wrong tradeoff. Lives are lost because you don’t have a day or two to check out the story to verify its legitimacy? 

So we are simply left with no other rational explanation that can fit the facts other than the drug really works. Saying it is NEUTRAL is completely unjustifiable; it doesn’t fit the facts. If it was NEUTRAL, someone would be knocking on my door to claim their $1M prize money for explaining how we were all fooled into thinking that the drug works. They would be able to explain away not just the Seftel trial, but the Lenze trial, the two observational studies in France, the one in Germany, and the two in the US (at TriNetX and Stanford/UCSF), as well as explain how doctors in multiple countries using the drug on hundreds of patients were misled into the thinking the drug was working when it was actually doing nothing. We’d have to believe that everyone who used the drug just “got lucky.”

My final point is that I’m hardly alone in believing the evidence is compelling. Any doctor who has ever prescribed fluvoxamine for COVID is a believer. A key opinion leader panel of 30 infectious disease experts from NIH, CDC, and academia met via zoom on Jan 22, 2021, to review the fluvoxamine data. They voted by more than a 2:1 margin that doctors should talk to their patients about using fluvoxamine for COVID. 

Lastly, Vikas Sukhatme, Dean of the School of Medicine at Emory University and a world expert on repurposed drugs, also has called publicly for the use in fluvoxamine, most recently in an op-ed he co-authored with his wife Vidula in the Times of India.