Dr. Malcolm Kendrick has long been an outspoken skeptic with regard to the medical status quo. “It’s just not possible to believe much of the clinical research that’s published,” he says.
Just one week prior to this talk, delivered at CrossFit HQ during a CrossFit Health event on Dec. 15, 2018, Kendrick’s Wikipedia page was deleted because, as he explains, “I’m now considered dangerous enough to be removed from public consumption.” In this talk, he shares one thread of his “dangerous” thinking — a thread that follows the distortion of data pertaining to cholesterol and statin research, which he explores in greater detail in his second book, Doctoring Data.
Kendrick explains that he wrote the book to:
- show how data from clinical studies are distorted;
- allow people to make informed decisions about the interventions and drugs they receive;
- highlight some of the really bad advice we are given about fat and carbs;
- stop believing that “experts” know what they are doing or saying; and,
- reduce the fear and anxiety that now seems to stalk the land.
He describes several ways in which data become distorted and focuses in particular on the strategic use of relative and absolute risk factors in the data from the famous JUPITER trial, previously discussed on CrossFit.com.
He also highlights some of the reasons why data get distorted. While money is a contributing factor, he explains, a much more potent and insidious explanation relates to researchers’ attachment to ideas.
People become emotionally attached to ideas, he observes, and “facts have very little effect on what people believe.”
Read a transcription of the presentation here.
Comments on Dr. Malcolm Kendrick on Doctoring Data
Keep shouting the truth until the truth becomes heard. We need more and more Dr. Kendrick!
Dr Malcolm Kendrick’s entry in Wikipedia has been deleted. Hitler’s is still there, as are Stalin’s and Chairman Mao’s, but Kendrick’s has been deleted. He must, therefore, have done something very bad indeed–and he has. He has shown how drug companies manipulate data.
Consider Pfizer’s claim that Lipitor (atorvastatin) “reduces risk of heart attack by 36%.” How do Pfizer construct such a claim?
To reduce the story to its essence, imagine a trial in which, over a number of years, a thousand people take a placebo and another thousand people take Lipitor. Now imagine that, in the placebo group, 30 people develop heart attacks. So their risk of getting the disease over those years is 3%.
Now imagine that, in the Lipitor group, 19 people develop heart attacks. Ie, on Lipitor, someone’s chances of developing a heart attack has fallen to 1.9%. The risk has fallen by 1.1%.
If you’re trying to sell Lipitor, claiming a 1.1% fall in the risk of heart attacks is unexciting. If 97% of people are not going to develop heart attacks anyway, and if Lipitor has significant side effects, then an awful lot of folk will simply trust to Mother Nature and trust they’ll be one of the 97% and skip the drug. And your stockholders will be unhappy.
But if your company has a PR department, it’ll note that two numbers have emerged from the study, namely that the risk of developing a heart attack is 3% and that Lipitor has reduced it by 1.1%. From which a third number can be calculated, for 1.1 is 36% of 3. So an actual risk reduction of 1.1% can described as a *relative* risk reduction of 36%, and Lipitor “reduces risk of heart attack by 36%.” Which will make your stockholders happy, because which patient wouldn’t want to reduce their risk of a heart attack by a third?
But wait. Not all heart attacks are fatal, and people can die from an awful lot of things: so, what does Lipitor do to overall mortality? After all, the JUPITER study (the ‘Justification for the Use of statins in Prevention: an Intervention trial Evaluating Rosuvastatin’ study) found that Rosuvastin, like Lipitor, reduced the numbers of heart attack and strokes–but the heart attacks that did ensue were more dangerous. Consequently, cardiovascular mortality on Rosuvastin *did not fall.* Rosuvastin reduced cancer mortality, but as Kendrick notes, that finding has not been reproduced.
Equally, in the Lipitor study, the difference in overall mortality between the placebo and Lipitor groups failed to reach statistical significance (p=0.16, Sever et al, 2003, Lancet, 361: 1149-1158). So, Lipitor might have been advertised as reducing “the risk of heart attack by 36%,” but it didn’t extend life.
Which is another worry of Kendrick’s. We look to statins for extra years of life, but doctors do not tell their patients how many: doctors do not tell their patients how many extra years or even months of life they might expect on taking statins. Patients with cancer are routinely told how particular therapies might extend their lives by so many years or months, but patients on statins are not told this. Why not? Well, it seems that statins apparently provide only extra days–not years, let alone months–of life.
Statins do, however, generate side effects. Sometimes really quite unpleasant ones such as severe muscle pain and diabetes. But we don’t know how many side effects they generate, nor how severely they damage patients, because the Cholesterol Triallists Collaboration, which is based at Oxford University and which is the central repository of the findings from the 30 or so large statin trials, keeps those data secret: almost all statin clinical studies are funded by the companies that market them, and the companies oblige the Cholesterol Triallists Collaboration to not release the information.
Malcolm Kendrick has chronicled other misleading stratagems from the world of medical science. What about the trials that show that cancer screening saves lives? Well, screening–cervical screening, for example–will pick up cancers early. But if you define ‘cure’ as a five-year survival rate, a patient whose cancer is diagnosed early will, all other things being equal, more likely survive for five years than one whose cancer is diagnosed later. Screening, in short, can look great in statistics while actually saving no lives.
Ever since John Ioannidis at Stanford published his iconic 2005 paper ‘Why most published research findings are false,’ we’ve increasingly understood that most published research findings are indeed false. Their falsities can arise from an array of biases, one of which is funding bias, and–as Malcolm Kendrick has chronicled–almost all the clinical studies on cholesterol and statins have been funded by industry. Not surprisingly, therefore, they’ve looked at the products of industry and found them good.
Kendrick gives a good talk and he writes a good book (three actually) but he must be seen as the star witness for the prosecution rather than the judge. Between the drug companies’ assertion that up to 40% of adults should take statins, and Kendrick’s assertion that practically no-one should, must lie the optimal figure for statin use. How to find it?
We obviously can’t rely on the drug companies to tell us, but we can’t allow a solitary primary care physician, however brilliant, to tell us either. Public health science of this importance must be a collective process, and perhaps the government or (preferably) one of the major foundations such the Bill & Melinda Gates Foundation or the Wellcome Trust might take the lead on creating a disinterested, exhaustive but transparent trial or set of trials.
And they might call their program the KENDRICK program for Kalculating the ENDothelial RIsCK study. Which might put that name back in Wikipedia.
Great video. Dr Kendrick is a brave man and CrossFit has often backed/presented such voices going way back ... not because they are "contrarians" but because they provide valid arguments to the discourse about "the ills of modern medicine and the wilful abuse of the public’s trust in science" that is worthy of further study.
Having said that, hope to also see Dr. John Ioannidis (Stanford University) in a future CrossFit Health event lecture, whose gravitas is a given and who similarly identifies bias/problems in published researched findings.
Dr. Malcolm Kendrick on Doctoring Data
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