Medical journals and textbooks are clear that the only way to accurately determine the life-or-death impacts of medical treatments is by measuring “all-cause mortality” in “randomized controlled trials.” Clinical lingo aside, this is simply the number of deaths in studies where people are randomly assigned to receive or not receive a certain treatment.
Though widely ignored in media coverage of Covid-19 vaccines, medical journals describe all-cause mortality in randomized controlled trials (RCTs) as:
- “the most objective outcome” (Journal of Critical Care)
- “the most relevant outcome” (The Lancet Respiratory Medicine)
- “the most significant outcome” (JAMA Internal Medicine)
- “the most important outcome” (PLoS Medicine)
- “the most important outcome” (Journal of the National Medical Association)
- “the most important outcome” (International Journal of Cardiology)
Beyond the fact that death is the most severe and clearest health outcome, the reason why this measure is more vital than any other is because RCTs control for every possible confounding factor, including those that are not obvious. Thus, a clinical research methods guide states that RCTs are the “gold standard” for research because they provide “a rigorous tool to examine cause–effect,” which “is not possible with any other study design.”
Combined with the use of a placebo so that people don’t alter their mindsets or behaviors as a result of knowing they received the treatment, quality RCTs ensure that any significant difference in the total number of deaths among the people who receive and don’t receive a treatment is, in fact, caused by the treatment. This eliminates subjective judgments about the root causes of death, which is a major point of contention with C-19 vaccines.
Unlike other data which can be easily manipulated through statistical tampering, all-cause mortality in RCTs is straightforward and solid. If an RCT is large enough and properly conducted, a simple tally of all deaths among people who receive and don’t receive a treatment proves whether the treatment saves more lives than it takes.
Underscoring all of the above facts, medical textbooks and journals explain that:
- RCTs are “the pinnacle in clinical design.”
- RCTs are “the best way to study the safety and efficacy of new treatments.”
- “the act of randomisation in a large” RCT “balances participant characteristics (both observed and unobserved) between the groups, allowing attribution of any differences in outcome to the intervention.”
In this case, the “intervention” is FDA-approved Covid vaccines, and the “outcome” is death. That vital data was gathered in RCTs involving 72,663 adults and older children for the Moderna and Pfizer vaccines. However, the FDA presented these results in a place and manner likely to be overlooked, and no major media outlet has covered them.
The results reveal that 70 people died during the Moderna and Pfizer trials, including 37 who received Covid vaccines and 33 who did not. Combined with the fact that half of the study participants were given vaccinations and the other half were given placebos, these crucial results provide no indication that the vaccines save more lives than they take.
Accounting for sampling margins of error—as is common for medical journals and uncommon for the media—the results demonstrate with 95% confidence that:
- neither of the vaccines decreased or increased the absolute risk of death by any more than 0.08% over the course of the trials.
- the vaccines could prevent up to two deaths or cause up to three deaths per year among every 1,000 people.
Importantly, those results:
- apply to adults and older children averaged as a group, and the vaccines’ benefits and risks can vary considerably for each individual.
- don’t apply beyond the timeframes of the studies, which were limited to several months.
- don’t apply to people who were excluded from the studies, including those who are severely ill, previously had Covid-19, or have an immune disorder like HIV.
- don’t apply to the currently dominant SARS-CoV-2 variant (Omicron).
Just Facts asked four Ph.D. scholars with contrasting views about Covid vaccines and who specialize in the disciplines addressed in this research to critically review it. Among those who did so, they assessed it as follows:
- Jessica Rose, Ph.D. in Computational Biology, Postdoctorate in Molecular Biology, Postdoctorate in Biochemistry: “I rarely have nothing to say when I read something with regard to corrections, but this is accurate and well written.”
- Rodney Sturdivant, Ph.D. in Biostatistics, Director of the Statistical Consulting Center at Baylor University: “The facts, so well laid out in this article, are a call for a very careful review and more study before future shots are recommended. All statisticians and scientists should be demanding better from the FDA.”
The FDA’s Diversion
Despite the import of all-cause mortality, the FDA completely ignored this measure in its press releases announcing approvals of the Pfizer and Moderna vaccines. Moreover, the FDA presented the all-cause mortality figures 20+ pages into technical documents alongside the following statements that distract from their implications:
- Pfizer: “From Dose 1 through the March 13, 2021 data cutoff date, there were a total of 38 deaths, 21 in the Comirnaty [vaccine] group and 17 in the placebo group. None of the deaths were considered related to vaccination.” (Emphasis added.)
- Moderna: “There were 32 deaths during the blinded phase of the study: 16 deaths in the vaccine group, and 16 in the placebo group. None of the unsolicited AEs [adverse events] leading to death were considered vaccine-related.” (Emphasis added.)
Those statements are highly subjective and divert naive readers from the fact that only the total number of deaths in each group can determine whether the vaccines save more lives than they take. This is precisely why medical journals call all-cause mortality the most “objective,” “relevant,” “significant,” and “important” outcome—not deaths considered related to the treatment.
Again, RCTs eliminate the need for subjective judgments like the FDA made in those statements. This is especially important for vaccines since there are untold ways in which they can alter the risk of death beyond direct effects like preventing Covid-19 or causing cardiac events, embolisms, fevers, and seizures.
For example, many fatal car accidents are triggered by fatigue, and the Pfizer and Moderna RCTs found that 70–72% of subjects under the age of 55 reported “fatigue” after receiving the vaccine. There is no objective way to account for all such risks and benefits except by measuring all-cause mortality in RCTs.
Even with direct connections, determining whether a vaccine contributed to a death is often inconclusive. As explained in the International Journal of Vaccine Theory, Practice, and Research, “when diseases and deaths occur shortly after vaccination with an mRNA vaccine, it can never be definitively determined, even with a full investigation, that the vaccine reaction was not a proximal cause.”
Likewise, the British Medical Journal reported in January 2021 that the Norwegian Medicines Agency investigated the deaths of 13 “very frail elderly patients” which occurred “shortly after receiving” the Pfizer C-19 vaccine and “concluded that common adverse reactions of mRNA vaccines, such as fever, nausea, and diarrhea, may have contributed to fatal outcomes in some of the frail patients.” Yet, the medical director of the agency stated, “There is no certain connection between these deaths and the vaccine.”
Measuring all-cause mortality in RCTs removes that uncertainty, which makes the FDA’s diversion and the media’s failure to report these results all-the-more troublesome.
While downplaying and ignoring the most objective data, media outlets, government agencies, and large corporations have touted studies that are rife with assumptions and plagued by fatal flaws. For a prime example, more than 100 such entities publicized the results of a study from the Commonwealth Fund which estimated that C-19 vaccinations prevented about 279,000 deaths and 1.25 million hospitalizations in the U.S. by the end of June 2021.
Those figures were calculated by comparing “observed” Covid-19 trends to a “model,” a type of study design that “rests upon a host of simplifying assumptions” and “cannot be fully” representative of the real world, as admitted by a medical journal that published a similar study.
Another class of subpar study results uncritically parroted by the media comes from “observational studies.” These are studies which observe the outcomes of people “in the wild” who have not been randomly assigned a certain treatment. As a medical journal explains, such studies can “rarely” determine the effects of a treatment because a host of other factors are at play.
For instance, observing the death rates of people who are vaccinated and unvaccinated against C-19 cannot prove whether the vaccines are more helpful than harmful because the odds of death are impacted by numerous factors like these:
- People who are deathly ill or even temporarily ill tend not to get vaccinated, a phenomenon described in medical journals as “healthy vaccinee bias.”
- Older people—who are more likely to die than younger people—have much higher C-19 vaccination rates than younger people.
- Immunocompromised people—who have conditions like cancer and HIV that increase their risk of death—are “plausibly more likely to be offered and seek vaccination” because they are very vulnerable to C-19.
Researchers commonly use statistical techniques to “control” for such variables, but these methods cannot rule out the possibility that other factors are at play. Also, the techniques used to perform such analyses are prone to pitfalls.
The root weakness of observational studies is that they can only measure associations, and association does not prove causation. Although commonly taught in high school math, this vital fact of medical and social science is routinely ignored by commentators, journalists, Ph.D.’s, and government agencies like the CDC.
Highlighting the necessity of measuring all-cause mortality and the fact that observational studies cannot match the reliability of RCTs:
- a 2013 article in JAMA Internal Medicine documents that 80% of “traditional RCTs” measure “mortality, a hard and important end point.”
- a 2018 paper in the European Heart Journal compares RCT and non-RCT studies on drugs to prevent heart failure and finds that:
- the observational studies routinely conflict with the RCTs.
- “it is not possible to make reliable therapeutic inferences from observational associations.”
- RCTs “clearly remain the best guide to the treatment of patients.”
- a 2005 paper in JAMA Internal Medicine presents a “systematic review of randomized controlled trials” on treatments for people hospitalized with uncommon types of pneumonia and reports, “Although mortality is the most significant outcome in a potentially lethal infection, all studies chose clinical failure as their primary outcome. This end point is subjective and should be studied with care. Our review clearly demonstrates its potential for bias.”
- the medical book Principles and Practice of Clinical Research documents that:
- “while consistency in the findings of a large number of observational studies can lead to the belief that the associations are causal, this belief is a fallacy.”
- “a well-designed” RCT “overcomes the major weaknesses of all other types of study designs….”
- a commentary published by the British Medical Journal in October 2020 explains:
- “Sixty years after influenza vaccination became routinely recommended for people aged 65 or older in the US, we still don’t know if vaccination lowers mortality” because “randomised trials with this outcome have never been done.”
- “Observational studies with results in both directions can be cited, and without definitive randomised evidence the debate will go on.”
- “Unless we act now, we risk repeating this sorry state of affairs with Covid-19 vaccines.”
None of this means that models and observational studies are clinically useless. They can illuminate paths for additional research, and in rare cases where their results are mathematically and logically overwhelming, they can estimate the effects of a treatment. However, their results should be taken with a grain of salt, especially if there are RCTs to the contrary.
Some may argue that the Moderna and Pfizer RCTs were “underpowered,” a medical term for clinical trials that don’t enroll enough participants to detect an effect. However, Moderna enrolled more than 30,000 people in its RCT, Pfizer enrolled more than 40,000, and an additional 10 deaths in the Pfizer vaccine group—or only 0.05% of the vaccinees—would have shown with 95% confidence that the vaccine costs lives on net.
Moderna and Pfizer could have made their RCTs larger, leaving little doubt as to whether the vaccines save more lives than they take, but the companies chose not to do this. In September 2020 after months of people “campaigning for greater openness,” Covid vaccine manufacturers released important information about the designs of their RCTs. Summarizing these plans, the British Medical Journal reported that the studies were not designed to “determine whether they can interrupt transmission of the virus” or “detect a reduction in any serious outcome such as hospital admissions, use of intensive care, or deaths.”
Explaining why Moderna chose to construct a study that couldn’t determine if its vaccine saves lives, Tal Zaks, the company’s chief medical officer claimed that “too many would die waiting for the results before we ever knew” if the vaccine “prevents mortality.” He also declared that it would cost $5–10 billion dollars to conduct a trial big enough to measure the impact on death and said:
I think the public purse and operational capabilities and capacities we have are rightly spent not betting the farm on one vaccine, but, as Operation Warp is trying to do, making sure that we’re funding several vaccines in parallel.
The first of those excuses is transparently false, as Moderna could have included more participants in the study at the same time. It is also self-contradicting, as Zaks can’t know if “too many would die waiting” if he doesn’t know that the vaccine “prevents mortality.” Furthermore, C-19 vaccine study results are reviewed on a rolling basis, allowing people to act on the available data without waiting for the final results.
Zak’s second excuse is belied by the fact that the U.S. government has enacted six “Covid relief” laws with a total cost of about $5.3 trillion, or 530 times Zaks’ upper-end estimate. Including the money spent by other nations, a handful of $10 billion studies is a relative drop in the bucket.
Larger studies would have narrowed the sampling margins of error and provided more resolution about whether the vaccines save more lives than they cost, but even the current studies are large enough to show with 95% confidence that the Moderna and Pfizer vaccines did not decrease or increase the absolute risk of death by any more than 0.08% over the course of the trials.
All studies have their limitations, and a major one of the Moderna and Pfizer RCTs is that most of the participants were enrolled for only several months after their second dose of the vaccine. For Moderna, this period was a median of four months, and for Pfizer, it was an average of 3.3 months.
Here again, this weakness of the studies is a direct result of choices made by the vaccine manufacturers. That’s because Pfizer and Moderna began removing people from their RCTs through a process called “unblinding” as they became eligible to receive the vaccines under “local recommendations.”
Those decisions were made in defiance of guidance issued by a global association of 24 healthcare regulatory agencies called the International Coalition of Medicines Regulatory Authorities. This group includes the FDA and its counterparts in Canada, Australia, China, France, Germany, Mexico, Japan, Nigeria, India, and other nations.
In a statement released in November 2020, this international coalition of government agencies made the following points (and others) about why longer-term RCTs are necessary for C-19 vaccines:
- “To determine that the benefit of a vaccine outweighs its potential risk, regulators need robust and convincing evidence of the safety and efficacy that is obtained from well-designed randomised and controlled trials.”
- “Thus, continued evaluation of the vaccinated and the unvaccinated” participants “for as long as feasible will provide invaluable information.”
- Such information includes but is not limited to “additional and more precise information on longer-term safety,” “potential risks of vaccine-induced enhanced disease,” and “whether protection against Covid-19 disease wanes over time.”
- “Therefore, unless maintaining participants in their randomised treatment groups (vaccinated or control) after a vaccine is approved is clearly infeasible, we recommend that clinical trials should proceed as initially planned with a follow-up of at least one year or more from completion of assigned doses.”
Pfizer and Moderna flouted that guidance, and the journal BMJ Evidence-Based Medicine reported in July 2021 that “placebo controlled follow-up, originally planned for 2 years in many trials, was eliminated after a few months, when manufacturers began offering vaccine to placebo recipients within weeks of receiving emergency use authorisations.”
Decisions to hastily end the RCTs also:
- hindered their ability to detect any effects of herd immunity as the broader society became vaccinated.
- prevent everyone from knowing with certainty how the vaccines protect against recent SARS-CoV-2 variants because the trials ended before Delta became common and before Omicron emerged.
- have proven to be ill-advised given that a wide range of studies are finding that the immunity conferred by the current C-19 vaccines wanes over time, such as:
Since all of those are observational studies, they don’t have the surety of RCTs and are therefore tentative. This is precisely why Dr. Doran Fink, Deputy Director of the FDA’s Division of Vaccines and Related Products Applications, warned at an FDA committee meeting in October 2020:
Once a decision is made to unblind an ongoing placebo-controlled trial, that decision cannot be walked back. And that controlled follow-up is lost forever.
Medical ethics require that RCTs be barred or ended if they would undoubtedly harm people. Thus, some allege that the RCTs should have been shortened based on their findings that the vaccines have large and statistically significant effects on reducing the risk of severe Covid-19. The Pfizer RCT, for example, found that the vaccine decreases the incidence of severe Covid-19 among people aged 16 and older by 70.9% to 100.0% (with 95% confidence).
However, those results don’t account for any side effects of the vaccines or whether their benefits wane over time. Moreover, the all-cause mortality data provided no indication that the vaccines were saving more lives than they cost.
What the RCTs Can’t Reveal
One of the most dangerous errors in medicine is interpreting the results of studies more broadly than the evidence warrants. This is called “overgeneralizing,” and academic works on applied statistics warn that “researchers in the behavioral and social sciences almost always want to make inferences beyond their samples,” but this practice “is always risky,” especially when the study subjects are “drastically different” from the people to whom the results are applied.
Media outlets often foster such deadly misinterpretations by failing to report the limits and caveats of studies. A prime example is the main Pfizer and Moderna RCTs that yielded the all-cause mortality data and the widely trumpeted results that the vaccines are more than 90% effective in preventing Covid-19. Beyond the fact that the RCTs were limited to several months, both of them excluded people:
- who are very vulnerable to C-19, like those who are severely ill or have certain immune disorders.
- who are highly resistant to Covid-19 because they previously had the disease and now have natural acquired immunity to it.
Thus, it is extremely important to realize that even though the Covid vaccines did not decrease or increase the absolute risk of death by any more than 0.08% over the course of the RCTs, this only applies to the pre-Omicron era and generally healthy adults who don’t yet have naturally acquired immunity.
Moreover, that result is merely an average, and the benefits and risks of the vaccines could vary widely depending upon factors like weight, age, sex, and a host of other variables. For instance, the risk of being harmed by Covid-19 greatly declines at younger ages, while the major known risks of the vaccine increase.
On February 5, 2020, President Biden tweeted, “Here’s the deal: Unvaccinated individuals are 97 times more likely to die compared to those who are boosted.” This claim—which Biden did not support but seems to be a gross distortion of a bogus statistic from CDC director Rochelle Walensky—clashes with the most objective, relevant, and important evidence on this matter.
That evidence consists of two large RCTs for the Pfizer and Moderna vaccines, which were the FDA’s main basis for approving them. These studies involved 72,663 generally healthy adults and older children in the pre-Delta/Omicron era who didn’t yet have naturally acquired immunity to C-19. After half of the subjects were randomly given a vaccine and the other half a placebo, 37 people died who received a vaccine, and 33 died who received a placebo.
On a superficial basis, these figures suggest that the vaccines increased the relative risk of death by 13%. However, the death rate in both groups was so small (0.1%) that the difference between them is statistically insignificant. More specifically, the results demonstrate with 95% confidence that:
- neither of the vaccines decreased or increased the absolute risk of death by any more than 0.08%.
- the vaccines could prevent up to two deaths or cause up to three deaths per year among every 1,000 people.
In short, the strongest available evidence shows no indication that the mRNA Covid vaccines save more lives than they take. However, the benefits and risks of the vaccines can vary greatly for each individual.
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