Dealing with the high quantity of scientific error in medicine

Okay, but don't make the mistake of the guy who says "The mainstream media is all lies - so I'll only trust what I read on shady Internet conspiracy sites". Saying that there are likely flaws in mainstream medical research doesn't license you to discount any specific medical finding unless you have particular reason to believe that finding is false. And it certainly doesn't license you to place more credibility in small, poorly performed studies that contradict large, well-performed studies, or in fringe theories that contradict mainstream theories. Unless you hold your favorite theory, be it anti-vax, paleo-diet, or whatever, to the same high standard you hold the medical mainstream, every true fact you learn about flaws in medical research makes you stupider.

The study mentioned above looks at exciting cutting-edge research over the past decade. It says that 40% or so was proven wrong. This is good and to the credit of medical science! It means the system is working as it should in retesting things and getting the false stuff out. The basis of science isn't getting everything right the first time, it's making sure everyone's work gets checked and double-checked until only the truth survives. An unreplicated study in almost any area is an intriguing possibility and nothing more; medicine is no exception. If the media makes a big deal about a new study and publishes "VITAMIN B CURES BREAST CANCER!!!" in 72 point font in the newspapers, that is an interesting fact about the media and the people who believe it, but not an interesting fact about medical science.

Good doctors are both conservative and utilitarian. They stick to older, well-proven treatments unless the advantage of a new treatment is so great that it outweighs the uncertainty and risks involved. IMHO the medical consensus has been right on the important things a surprising amount of the time.

I would strongly discourage people from bewaring statins overly much. I don't see anything by Ioannidis saying the studies surrounding statins are particularly bad. Ioannidis says research is less likely to be true if it has low sample sizes, low effect sizes, bias, and a wide net. There have been several statin trials with sample sizes in the thousands to tens of thousands (see: JUPITER, SSSS, etc.) They've found that death rate from heart attacks in people correctly prescribed statin goes down by 30%, which is not at all a small effect size. Many such trials have not been linked to statin manufacturers or anyone with an axe to grind. And because people already know statins are supposed to reduce cholesterol, there is much less of a wide net than if you were to give a bunch of people statins and, say, see if any diseases became less common - the studies had a clearly designated endpoint, which they achieved.

Are there people who suggest the side effects of statins are worse than everyone else thinks? A few, and based off of very little evidence (I believe the idea that statins cause memory dysfunction is based mostly off isolated case reports, and there are only 60 out of many years of hundreds of thousands of people on statins - basically background noise). I haven't investigated this thoroughly, but the side effects would have to be pretty darned bad and pretty darned robust to stop prescribing a drug with an NNT in the two digits (ie it takes under 100 statin prescriptions to prevent one heart attack), and I treat people trying to exaggerate drug side effects as just as real a failure mode as doctors trying to exaggerate drug benefits, and use just as much caution.

The advice in the third-to-last paragraph, except perhaps the specific singling out of statins, remains excellent.

I read David Freedman's book Wrong a while ago. The article (which I have not read yet) appears to be a condensation of the book. I highlighted a few passages while I read. Here they are.

Quotes about the problem of groupthink from the chapter The Idiocy of Crowds:

…the notion that individuals tend to outthink, outdecide, and outperform groups is so well established that it isn’t even studied much anymore. “The average person certainly believes teamwork trumps individual work, but the evidence says otherwise,” says Natalie Allen, an organizational psychologist at the University of Western Ontario who has studied what she calls the “romance of teams.” …

Nearly four decades of research have exquisitely detailed the ineffectiveness of groups. The problems with collaborative and community thinking have been repeatedly highlighted by a stream of studies, starting with the Yale psychology researcher Irving Janis’s classic examination of “groupthink” back in 1972, which showed how groups could reach terrible decisions that none of the individuals in the group ever would have made on his own. As Janis and many others have shown—and as most of us know all too well—groups are frequently dominated not by people who are most likely to be right but rather by people who are belligerent, persuasive, persistent, manipulative, or forceful. Those who are even mildly adept at getting people to go along with them can quickly form small alliances of viewpoint that may in turn convince others to join in, eventually swaying even those with doubts—most of us don’t want to be the odd man out. …

Once a majority opinion is formed, even highly competent, confident people are reluctant to voice opinions that go against it…

…of the ten deadliest plane crashes in history, cockpit tapes reveal that six of them—killing a total of some 2,400 people—took place with at least one crew member being fully aware of the mistake that was about to bring the plane down but staying mostly quiet because the rest of the crew thought differently. …

Academic, financial, and clinical researchers submit to a pack mentality at least as easily as most sorts of groups or communities. “They go off together in the wrong direction, following one another like any collection of humans,” says Peter Sheridan Dodds, a University of Vermont mathematician who also does work in sociology and biology, among other fields. Herd thinking can keep the community trudging along in one direction for years, resistant to all kinds of contrary evidence …

There is almost no replication in science, and even when there is, the replication is ignored:

Okay, so lousy research can slip past peer review into journals. But surely as soon as other researchers put the published results to the test, the truth will out, right? Possibly—except that the vast majority of published research is never replicated or validated, or if it is, there is no record of it in research journals. All but the most prominent research tends to enter the records and forever persist as apparently legitimate by default. Martinson estimates that more than 95 percent of medical research findings aren’t replicated. No wonder: replication is more or less unfundable, and if someone does it on his own nickel, the results probably won’t come to light. Even a study that fails to replicate a published result, stated Nature in an editorial, “is unlikely ever to be published, or even submitted for publication.” In 2006 Nature reporter Jim Giles dug up the fact that two out of the four stories plastered on the cover of a 2002 issue of the journal—that is, half of the biggest stories in the world of science that week—had failed replication, without all that much notice being taken of it. …

Ioannidis, too, found evidence of the persistence of bad findings. He looked at studies reporting the cardiovascular benefits of vitamin E, anticancer benefits of beta-carotene, and anti-Alzheimer’s benefits of estrogen—important studies that were published in 1993, 1981, and 1996, respectively, and that were each convincingly and prominently refuted in one or more larger studies around 1999, 1994, and 2004, respectively. In 2005, the most recent year Ioannidis checked, half of the researchers who cited the original study of vitamin E did so in the context of accepting the original results, and through 2006 a little more than 60 percent cited the original beta-carotene and estrogen studies, though the results had been solidly refuted—thirteen years earlier in the case of beta-carotene.

Scientists have a substantial motive to fudge research or commit outright fraud:

What could motivate such surprisingly nontrivial apparent levels of dishonesty? The answer turns out to be pretty simple: researchers need to publish impressive findings to keep their careers alive, and some seem unable to come up with those findings via honest work. Bear in mind that researchers who don’t publish well-regarded work typically don’t get tenure and are forced out of their institutions. …

So researchers are pressured to come up with study results that are both interesting and positive. But Ioannidis, among many others, is quick to note a problem: the more surprising, novel, and exciting an idea, the less likely it is to be right.† An idea that seems highly likely to be true, that is utterly plausible, is probably not going to seem exciting—it’s the implausibility that often provides most of the novelty and enthusiasm. …

In other words, researchers are essentially highly incentivized to test exciting ideas that are likely to be wrong—and far more likely to be published. Back in 1989 economists at Harvard and the National Bureau of Economic Research estimated that virtually all published economic papers are wrong, attributing this astoundingly dismal assessment to the effects of publication bias. …

And therein lies the motivation to fudge research. If a study’s results don’t clearly support an interesting hypothesis, a researcher is free to stick it in a file drawer and possibly kiss his career or funding good-bye—or, alternatively, he can imagine salvaging the situation by fabricating data, or by doctoring the way the study is conducted in order to produce more attractive data, or by manipulating the analysis of the data, in order to come out with a dubious positive result.

Whistle-blowing is strongly discouraged:

Baltimore would later publicly apologize to O’Toole for the way she was treated, but she lost her job at MIT. The message sent to young researchers everywhere was clear: the science community isn’t a lot friendlier to whistle-blowers than are police departments and tobacco companies. There’s plenty of evidence that O’Toole’s experience accurately reflects the research culture. In a 1993 study, 53 percent of graduate students said they would expect reprisals for reporting a faculty member’s misconduct, and 26 percent of faculty members said they “probably or definitely” would expect retaliation for reporting a colleague—where retaliation can include blocking promotion or sending unflattering reviews of research to journals and funding committees.20 Only 18 percent of assistant professors stated they “definitely” could report conduct and not expect retaliation.

Publication bias, with the help of incompetence or by itself, can produce the same effect as fraud:

…most researchers can get highly publishable and utterly wrong findings simply as a matter of carelessness or oversight, perhaps goosed by a little bit of subtle gamesmanship, even if unconsciously. …

Now let’s imagine there’s interest among twenty teams of scientists in testing a novel scientific theory, bearing in mind that, as we’ve discussed, most novel theories are likely to be wrong. If they all end up with “significant” findings, then we can reasonably propose that nineteen of them will have failed to confirm the theory, quite correctly, and one team will suffer a data fluke that will have led it to mistakenly conclude its work has confirmed the theory. Guess whose study is most likely to be published?

Peer review has much less value in selecting valid science than is popularly believed:

After the Schön scandal, Nature quoted the Princeton professor, Nobel laureate, and former Bell Labs researcher Philip Anderson as saying, “Nature’s editorial and refereeing policy seems to be influenced by the newsworthiness of the work, not necessarily its quality. And Science seems to be caught up in a similar syndrome.” …

It’s peer review that, more than anything else, [in the popular imagination] is supposed to separate the genuine, reliable science served up in research journals from the apparently frequently junky stuff we get in the mass media. Unfortunately, anecdotal evidence that the peer-review process is an effective way of picking out lousy and even fraudulent work is not encouraging. A panel of researchers and editors assembled to advise Science magazine after the Hwang scandal issued a statement noting that reviewers don’t even look for fraud. …

In fact, it is typically science journalists and other outside observers who imagine peer review to be an assurance of study reliability, and less so scientists. “Scientists understand that peer review per se provides only a minimal assurance of quality, and that the public conception of peer review as a stamp of authentication is far from the truth,” Jennings has written.

By capturing the process of peer review, bad scientists can suppress refutation of their own results:

“Prestigious investigators may suppress via the peer-review process the appearance and dissemination of findings that refute their findings, thus condemning their field to perpetuate false dogma,” states Ioannidis.

Sorry to nitpick on typos, but the researcher's name is spelled in four different ways in the post: Ionnides, Ioannidis, Ioannidde and Ioannides. I suppose not all can be correct.

I first read Ioannidis' paper several months ago and enjoyed it immensely. The Atlantic article is also good and I hope that it gets some much-needed conversation energized.

A couple of remarks.

I do not like the title. Ioannidis has shown that most published medical research is wrong and the title of his paper why most published research findings are false is misleading to me. Many of the pitfalls which he describes are specific to the limits of experimenting on human subjects which is not transferable across the entire universe of experimental science. Some of the pitfalls are general and all scientists should pay attention to them; it would have been a smoother rhetorical move to reflect this in his title.

The biggest issues amongst my friends and co-workers are diet and neurological nutritional supplements. My experience is that both of these areas are currently a quicksand swamp where it seems like a study of some sort can be found to support many positions that are in contradiction; the most obvious example is the thing with low fat diets, Atkins diets, paleo diets, and the list is far too long to include them all. I have a book Sports Nutrition published by The American Dietetic Association, which is a compilation from Track people, Football people, Swimming people, &c--there are fifty separate articles. The advice is all over the map. The most interesting thing in that book was the people who said that protein powders are useless. I have my own ideas on diet but I find my social life is less complicated if I keep them to myself.

There is some interesting information and (some complete nonsense) in the book by Doctor Daniel Amen Making a good brain great. It may just be blowback to his enterprising attitude, but Amen attracted enough detractor attention to get himself an entry on the quackwatch web page. He supplies medical journal citations for nearly all the claims in his book. Some of his recommended supplements I had heard of before, such as ginko biloba. Some of his recommended supplements I had never heard of, such as coenzyme Q. Amen takes twenty-five brain supplements daily. It was reading his book, and seeing his claims, and seeing his citations, which convinced me of the Ioannidis claim long before I read the Ioannidis paper. It seems impossible that all of the Amen claims and citations could be valid; it seems far more likely that most of the Amen claims and citations are false.

There is one fascinating item in Amen's book which I will share as an aside. He is big on brain scanning (SPECT is his favorite protocol). He reported one research project where they were going to scan a large random sample of normal people. They preselected with a questionnaire to reject addicts, diagnosed mentally-ill, people with family history of Alzheimer's and Parkinson's, people with a memory of severe concussion, &c. Then they winnowed their population again with a preliminary brain scan. Of the first selected set, only ten percent of the people measured normal on their first brain scans and were kept in the study group!

This is an anecdotal data point for the contention that "normal" may be a dubious concept. This may be the single biggest flaw in medical research. People vary widely and they will necessarily vary widely in how they behave under experimental study. The normal distribution may be highly unusual for many practical applications.

And there are false negatives as well as false positives.

See also: What's In Your Placebo?

I've often worried about medical research because human trials are necessarily so small. And they're expensive to run, so there seems to be an incentive only to conduct an experiment only when it will win acclaim for the experimenter.

I wonder if medicine needs to be supplemented with things that are not clinical trials -- simulation runs or Brin-style big-but-sloppy survey-data studies. These are not a replacement for medical science, but they are at the very least a sanity check. And sanity checks are cheap and quick, so it's easier to ask researchers to do a sanity check than to spend lots of time and money replicating another clinical trial.

While a small study is more likely to be wrong, there are two corollaries to that. The first is the second point raised - effect size. If (to take the extreme case) you have a study of three people who are all eighty years old and in a persistent vegetative state, and you give them Wundadrug, and they all wake up and suddenly look thirty years old, then you don't need a much larger trial to see that Wundadrug is almost certainly doing something interesting.

More importantly in this context, they're easier to replicate. If a study involves a hundred thousand patients over a thirty year period, then realistically nobody is ever going to check to see if they can get the same results. If, on the other hand, it involves ten patients for two weeks, anyone who is interested enough can try to replicate it with minimal effort.

Related: Reliability of ‘new drug target’ claims called into question:

Bayer halts nearly two-thirds of its target-validation projects because in-house experimental findings fail to match up with published literature claims, finds a first-of-a-kind analysis on data irreproducibility.

Related reading: http://www.gwern.net/DNB%20FAQ#flaws-in-mainstream-science-and-psychology

• Why Most Published Research Findings Are False, 2005
• Potential pitfalls in the use of p-values and in interpretation of significance levels: http://dx.doi.org/10.1016/0167-8140(94)90072-8, 1994

Hans-Peter Beck-Bornholdt and Hans-Hermann Dubben are writing books and papers on this problem (most medical research is wrong, see "Is the pope an alien?" Nature 381: 730, 1996) for decades. I've even got a popular science book on probability by them. Sadly most stuff is only available in German.

Do dead salmon dream of electric sheep? (Related article)

The people I've read who gave advice based on Ioannidis article strongly recommended eating paleo.

Incidentally, something like the paleo diet works incredibly well for me. I discovered the right details for me about 4 months ago and have quickly lost weight to a point near my optimal weight and I don't have dizzy or tired spells anymore with blood sugar fluctuations. However, calling it the 'paleo' diet begs a question I don't have enough background in evolutionary biology to ask, but I can pose a related question, because it is more concrete:

My father-in-law is on some kind of fruit diet, and he raves about how healthy fruits are, especially if they are fresh and eaten with the peel. Apples, for example, have all these different healthy things in them.

I wonder why an apple should be healthy. Wouldn't any animal be satisfied with a fruit that just had calories? Enough, in any case, to come back for more and scatter the seeds? Why should an apple -- or anything 'natural' -- be so especially healthy for humans?

More on self-experimentation: http://www.quantifiedself.com/

The people I've read who gave advice based on Ioannidis article strongly recommended eating paleo.

And they're wrong. Modern diet is a lot more paleo than diet before metabolic syndrome epidemic.

Strong correlation pointing the wrong way is a pretty good evidence for lack of causation.