That heading is the title of a book (1) which presents comprehensive, soundly sourced documentation that 11 common beliefs about medical matters are wrong: about aspirin, low-carb diets, cholesterol, blood pressure, alcohol, exercise, radiation, mammograms, fluoridation, cancer treatment, and chelation therapy. The book was self-published, but the author publicized it at many medical meetings and told me that sales exceeded 20,000. That author had been a valued friend, an organic chemist who worked for a long time at the former University of the (Health) Sciences in Philadelphia.
I find the book’s conclusions convincing on all but a few of these “myths”. That I do not agree on some of them illustrates that certainty on medical matters is rarely if ever achievable. Controlled experimentation is almost never possible in medicine. Evidence is gleaned by observation, the accumulation of anecdotes, and in some cases by clinical trials. Such trials are often regarded as the gold standard for medical evidence, but it needs to be understood that interpretation of the results can be no more than probabilistic because the data are statistical, and statistical analysis can never yield certainty in medical matters. As well as the fundamental axiom of statistical analysis — that correlations never prove causation — all clinical trials involve further fundamental uncertainties because all variables cannot be controlled for — or perhaps even known — and sampling of the pertinent population inevitably introduces further uncertainties.
Moreover, the protocols used in clinical trials are sometimes — or even quite often — deliberately biased in order to favor a particular outcome. Formally independent research labs usually carry out clinical trials at the behest of pharmaceutical companies. Labs with records of favorable results are likely to prosper by getting repeat contracts. Among the devices commonly used is the adjusting of dosages when comparing two potential drugs: use high doses of the one not to be favored and low doses of the one to be favored, so that the latter looks better in terms of negative “side” (2) effects.
Volunteers are routinely recruited to participate in “Phase I” clinical trials that look for possibly damaging unforeseen “side” effects. Volunteers who are particularly healthy and least likely to suffer negative “side” effects of new drugs are most in demand and become accepted most frequently for these trials, and some number of individuals are perpetual volunteers who get free board and lodging during the trials. That may seem a farfetched speculation, but it actually happens, as I learned at first hand, during a seminar, from a young lady who had spent years as an assistant in arranging such clinical trials.
Unavoidable uncertainties also come about because not all possibilities can be covered in sampling. When I inquired many years ago at Eli Lilly whether they always test potential new drugs for interactions with such commonly used medications as aspirin, tranquilizers, antidepressants, blood-pressure drugs, and so forth, the answer was in the negative; understandably so, since clinical trials are quite expensive and time-consuming.
From a potential consumer’s point of view, a useful rule of thumb is to avoid, if possible, medications or medical devices (3) that have been on the market for less than half-a-dozen years.
Everyone exposed to advertisements, not only those from drug companies, would be well served by learning of the innumerable ways in which statistics can be used to mislead deliberately (4).
One common way in drug advertising is to cite relative rather than absolute data: it can seem very convincing when a medication is said to reduce mortality by more than 50%, say; but if that means reducing mortality from one in 10,000 to 1 in 20,000, that might not be a worthwhile bargain if harmful “side” effects are worse for the supposedly more effective drug. The numbers that would be most meaningful for consumers are very rarely available, namely, the number of patients needed to be treated to produce one favorable outcome compared to the number of patients treated for one to show an unfavorable “side” effect (5).
Percentages are a common device for misleading. Little spectacle/binoculars called “Zooms” are advertised as having “300%!!” magnification; but 3x is very moderate magnification characteristic of what used to be called “opera glasses”, while decent binoculars give at least 4x magnification.
My cat-litter boasts that it is “99.9% dust free”, but it does not say to what it is being compared or what magical technique brings an accuracy of 1 in 1000.
Dozens of books by well-informed insiders in the medical and medical-research communities have detailed deficiencies and dangers in our contemporary health-care systems; see my representative bibliography (6). Greene’s Prescribing by Numbers (7) offers important insights. As medicine became supposedly more scientifically based, diagnosing by symptoms shared by patients with their doctors has been progressively replaced by diagnosis based on measurements of blood pressure, chemical composition of urine and blood, electrocardiograms, and other so-called “biomarkers” that are taken to be indicative of some specific medical condition. As the official reports on biomarkers cited in my bibliography make plain, however, the purported relationship between biomarkers and specific conditions is far from well-established in many cases.
Greene’s history also reveals how the preoccupation with numbers conspired with the mistaken presumption that statistical correlations can be mis-interpreted in terms of causation, to mislead and mis-guide common practice. The correlation between mortality and blood pressure originated in data accumulated by insurance companies, which naturally wish to set their premiums according to level of risk. But in reality, mountains of data agree that blood pressure increases normally with increasing age. Since mortality also increases with age, the apparent correlation between blood pressure and mortality could be entirely spurious. To establish an actually causative correlation, one would need data comparing people at the same age. A recent meta-analysis along those lines (8) does not offer particularly convincing conclusions, although it does note that the recommended levels of blood pressure for administering medications are significantly less stringent in Europe than in the United States. The lack of certainty on these matters is underscored by a report finding that systolic blood pressure around 140 minimized risk factors compared to both lower as well as higher pressures (9).
Individual decisions will depend on what one knows, what one believes, what and who one trusts, and one's relationship with one's physician and the health-care system overall. For my part:
I'm sure that no form or level of cholesterol causes heart or vascular disease. Personal experience with angioplasty in 1981 and quintuple-heart-bypass surgery 10 years later is consistent with reports that vascular disease is caused by physical damage or inflammation at the inside of artery walls. A convincing explanation of the role of cholesterol in plaques is given by Malcolm Kendrick (10). But I cannot understand what caused the build-up in my carotid arteries making surgery necessary a couple of decades after the heart bypass.
I am quite sure that statins cause considerable harm and offer no benefit. They interfere with the body's synthesis of coenzyme Q10, which is needed for the energy production in every cell of the body. One of my friends believes that she needs assistance in walking as a result of statin treatments. Another friend became periodically confused while taking Lipitor, would stop taking it until his mind cleared, and cycled like that for years. Yet another friend taking statin experienced periodic mental confusion, became physically considerably weaker, had a pacemaker installed, and died shortly afterwards. Merck took out a couple of patents about the benefit of CoQ10 supplements when taking statin (11).
I take the absolute minimum prescriptions that allow my doctor To keep me as a patient, but I take a great number of supplements.
Caution is properly called for with official statements. For example, a Cochrane Collaboration meta-analysis concluded that there was insufficient evidence as to whether masks or PN95 Respirators had a detectable effect on the spread of respiratory viruses (12). The common paraphrase, “Masks don't work”, Is not what the Report says and has been directly and specifically disowned by Cochrane (13). Nevertheless, Anthony Fauci, in an interview with Michael Smerconish (CNN TV, 2 September 2023), said that the Report doe state that masks do not work to prevent spreading of infection in the population; but that nevertheless an individual might be prevented from being infected by wearing a mask. I find that conjunction of statements puzzling.
Then again, we are being continually urged to take our annual flu shot, and to get vaccinated and boosted against COVID in order to be safeguarded against getting infected; yet a technical article with Fauci as a co-author describes the need for better vaccines against respiratory viruses because the vaccines against flu and COVID are ineffective in preventing infection, albeit they seem to make symptoms after infection less onerous (14).
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(1) Joel Kauffman, Malignant Medical Myths, Infinity Publishing Company, 2006; ISBN 0-7414-2909-8
(2) Scare quotes are always appropriate for “side” effects, as the late Felix Ofner, M.D., insisted: “Side effects are main effects that doctors don’t like to talk about”. Drugs are chemicals that do what they do without regard to what we wish they did.
(3) Jeanne Lenzer, The Danger Within Us: America’s Untested, Unregulated Medical Device Industry and One Man’s Battle to Survive It, Little, Brown, 2017
(4) D. Huff, How to Lie with Statistics, W. W. Norton, 1954; J. Best, Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists, University of California Press, 2001; More Damned Lies and Statistics: How Numbers Confuse Public Issues, University of California Press, 2004
(5) “How (not) to measure the efficacy of drugs”, https://scimedskeptic.wordpress.com/2015/02/19/how-not-to-measure-the-efficacy-of-drugs
(6) “What’s wrong with present-day medicine”, https://mega.nz/file/gWoCWTgK#1gwxo995AyYAcMTuwpvP40aaB3DuA5cvYjK11k3KKSU
(7) Jeremy Greene, Prescribing by Numbers: Drugs and the Definition of Disease, Johns Hopkins University Press, 2007
(8) The Blood Pressure Lowering Treatment Trialists' Collaboration, “Age-stratified and blood-pressure-stratified effects of blood-pressure-lowering pharmacotherapy for the prevention of cardiovascular disease and death: an individual participant-level data meta-analysis”, published online, www.thelancet.com, August 26, 2021, DOI: https://doi.org/10.1016/S0140-6736(21)01921-8
(9) A. Gutiérrez-Misis et al., “Association between blood pressure and mortality in a Spanish cohort of persons aged 65 years or over: A ”, Revista Española de Cardiología, 66 (2013) 464-71
(10) Malcolm Kendrick, The Clot Thickens: The enduring mystery of heart disease, Columbus Publishing, 2021; ISBN 978-1907797767
(11) US Patent 4,929,437, May 29, 1990; US patent 4,933,165,,Jun. 12, 1990
(12) Tom Jefferson et al., “Physical interventions to interrupt or reduce the spread of respiratory viruses” https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD006207.pub6/full?utm_source=substack&utm_medium=email&cookiesEnabled
(14) David M. Morens, Jeffery K. Taubenberger & Anthony S. Fauci, “Rethinking next-generation vaccines for coronaviruses, influenza viruses, and other respiratory viruses”, Cell Host & Microbe, 31 (2023) 146-157
I think the significant fact about masking was the fact that mask mandates were a gigantic and expensive effort for something that could not be shown to be of benefit and with lots of anecdotal reports that they were ineffective at stopping the spread of respiratory viruses. One could not help but believe that the true purpose was not disease prevention but anxiety production to facilitate vaccine uptake. One of the biggest medical myths of all time is the utility and safety of vaccines, especially those given to children. The book "Turtles All the Way Down: Vaccine Science and Myth" is a thorough demolition of that myth. One of the most shocking facts is that none of the vaccines on the childhood schedule has ever been tested against a true placebo, therefore, the actual risks of the vaccines are unknown. Nor has the effect of the whole vaccine schedule ever been tested with a vaxxed vs. unvaxxed study by the government authorities. There have been several small scale retrospective studies by non-government investigators that have uniformly shown significant statistical associations between vaccination and chronic disease, which is likely the reason no government agency will do such a study (or, if done, will not publicize the results).