Who forgot to give Peter Doshi the memo?

Smells like scientific integrity at the BMJ

Peter Doshi has been asking questions. In fact, he has been asking the same set of questions since the beginning of the vaccination campaign. As senior editor of the British Medical Journal, that is his job. Yet, Doshi is distinct from senior editors at other peer-reviewed journals; he has been asking the same questions as us.

As early as November 2020, Doshi called for caution in interpreting the vaccine trial data. He quickly noted that relative risk reduction is being reported, but absolute risk reduction, which was less than 1%, was being ignored. Doshi, in fact, went a step further when criticizing the available results, noting that:

“These results refer to the trials’ primary endpoint of covid-19 of essentially any severity, and importantly not the vaccine’s ability to save lives, nor the ability to prevent infection, nor the efficacy in important subgroups (e.g. frail elderly)”

This was, even at the time, a bold and against the grain criticism of the vaccine trials. Meanwhile, the Church of Fauci claimed the vaccine would stop COVID in its’ tracks, despite little evidence to that effect.

More importantly, however, Doshi expressed concern about the vaccine efficacy beyond the extremely short time-frame reviewed by Pfizer. Unfortunately, regulators, vaccines enthusiasts, and public health officials still do not understand that we need to evaluate outcomes holistically. If a vaccine only works for a short period of time, then even if the vaccine reduces the likelihood of getting the virus by 50%, say, in terms of cumulative days at risk for a given population, then the actual reduction for each individual person will be much lower. In other words, there are different personal and social benefits to vaccination, but given enough time, the social benefits end up being the summation of the personal benefits. I will write about this in a separate article with a more fleshed out example.

Doshi further noted that there was a high potential for unblinding in the trials through the observation of adverse events to the vaccine. This is always a concern with clinical trials and has been abused by pharmaceutical companies in the past; for example, sometimes these companies will unscrupulously use active placebos under the guise of preventing unblinding. Of course, this has the added benefit of blurring the safety profiles of drugs or vaccines. In terms of these vaccine trials, Pfizer and Moderna instead provided clinicians with a list of vaccine adverse events that matched many of the symptoms of the virus. They were then told to use their judgement in whether or not to test for the virus. Essentially, this facilitated the unblinding of participants in the RCT.

I can understand the fear of unblinding in this instance. One of the alternative hypothesis that I have posited to the immune suppression theory following the first 14 days of vaccination is that adverse events can change in testing frequency. Essentially, the adverse events are so severe and so common that they cause changes in the testing behavior of individuals receiving the vaccine. This is not a point in favor of the vaccines. In the real world this is likely muted somewhat by bidirectional changes in testing behavior, ie., recipients of the vaccine, instead of clinicians, are given a list of adverse events that are the same or similar to the symptoms of the virus and told to use their own discretion in getting tested. There are reasons to believe that this may lead to increased testing when participants are blinded in a randomized control trial.

However, there is an easy fix especially for a vaccine that is worth hundreds of billions of dollars. They could have tested everyone at set intervals, ie., once a week. The cost would be minimal proportionally as there were only ~40,000 participants and the trials were short. That was not done.

Likewise, Doshi also pointed out that the trials were not counting all cases of the virus, instead neglecting to count cases prior to 7 to 14 days past the second dose. Interestingly, every public health authority on the planet has used this metric to count COVID cases since then. If they did not want us to believe they are deeply in bed with big pharma, they should never have turned such a ridiculous obfuscation of the data in a clinical trial into public health policy. As Doshi notes, “In a proper trial, all cases of covid-19 should have been recorded, no matter which arm of the trial the case occurred in. (In epidemiology terms, there should be no ascertainment bias, or differential measurement error)”.

Finally, he noted that there was no data released on the use of prophylactic use among patients in the Pfizer or Moderna trial, but the Johnson and Johnson trial told individuals to use fever or pain reducers following vaccination if any fever, muscle aches, or headaches occur, which can bias the results for the vaccinated cohort. In fact, when later data came out, it appeared that the vaccinated cohort was 3-4 times more likely to take these medications than the placebo cohort, suggesting the patients were unblinded by adverse events. While Doshi notes that the confounding created by taking pain medications may be small, I would note that the confounding by unblinded participants in line with the failure to test suspected COVID cases is large.

A few months later, as more data came in, Doshi highlighted the bizarre discrepancy in confirmed versus suspected cases of the virus in the Pfizer trial. As we know, there were twenty times more suspected than confirmed cases, and Doshi noted that the true vaccine efficacy may be closer to 19-29% under the assumption that the endpoint should be covid-19 symptoms with or without confirmation by a PCR test (29% was even after taking out the suspected cases in the first 7 days of vaccination). Of course, some of them may not have been real cases, but Pfizer thought it apt not to confirm this fact, which means we have to make assumptions. 19-29% efficacy would have meant the trial endpoints were missed completely.

Doshi, furthermore, pointed to other discrepancies in the data including the fact that 84% of “protocol deviations” occurred in the vaccinated cohort — with no reference to what these deviations actually were, and the fact that a disproportionate amount of reinfections in the trials. As he points out,

“With only around four to 31 reinfections documented globally, how, in trials of tens of thousands, with median follow-up of two months, could there be nine confirmed covid-19 cases among those with SARS-CoV-2 infection at baseline? Is this representative of meaningful vaccine efficacy, as CDC seems to have endorsed? Or could it be something else, like prevention of covid-19 symptoms, possibly by the vaccine or by the use of medicines which suppress symptoms, and nothing to do with reinfection?”

At other times, Doshi has showed himself to be an ardent defender of the truth. When the unvaccinated were first declared public enemy number one, including painfully uninformed politicians calling it a “pandemic of the unvaccinated”, Doshi pushed back against the notion. He questioned the safety profiles of the vaccines, questioned why the vaccinated would need boosters, and questioned why the UK data showed most cases and deaths being in the vaccinated.

And in December 2021, Doshi published a paper calling for more independent review of drugs, citing the COVID vaccinations in particular. This echoed his call for access to the raw data from the January 2021 article. A few days ago, as the vaccines failed, he again called for access to the data — now. Even going so far as to note that the pharmaceutical industry has reaped vast profits without independent scrutiny.

Throughout the vaccine rollout, Doshi has been consistent and adamant that we need the data. He has questioned the vaccines and poignantly said what we have all been screaming from rooftops: “Something’s not right”. So, why Doshi and not others? I suspect it has to do with his previous experience with Tamiflu and the last pandemic response. I recommend listening to his explanation of Tamiflu in his own words:

In short, the case for mass stockpiling of Tamiflu across the world rested on studies that did not exist in the public sphere. The authors of papers cited in favor of using Tamiflu had never seen the underlying data, and once only a tiny amount of the data came to light, it changed the entire basis for pandemic response across the world. Being involved in uncovering this particular instance of scientific malfeasance, Doshi has been a transparency hawk ever since and remains one of the few that I can honestly say has kept their scientific integrity intact throughout the last two years.