Lies, Damned Lies, and Medical Science - 0 views
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or whatever reason, the appendices removed from patients with Albanian names in six Greek hospitals were more than three times as likely to be perfectly healthy as those removed from patients with Greek names.
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One of the researchers, a biostatistician named Georgia Salanti, fired up a laptop and projector and started to take the group through a study she and a few colleagues were completing that asked this question: were drug companies manipulating published research to make their drugs look good?
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Just as I was getting the sense that the data in drug studies were endlessly malleable, Ioannidis, who had mostly been listening, delivered what felt like a coup de grâce: wasn’t it possible, he asked, that drug companies were carefully selecting the topics of their studies—for example, comparing their new drugs against those already known to be inferior to others on the market—so that they were ahead of the game even before the data juggling began?
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Maybe sometimes it’s the questions that are biased, not the answers,” he said, flashing a friendly smile.
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That question has been central to Ioannidis’s career. He’s what’s known as a meta-researcher, and he’s become one of the world’s foremost experts on the credibility of medical research.
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He and his team have shown, again and again, and in many different ways, that much of what biomedical researchers conclude in published studies—conclusions that doctors keep in mind when they prescribe antibiotics or blood-pressure medication, or when they advise us to consume more fiber or less meat, or when they recommend surgery for heart disease or back pain—is misleading, exaggerated, and often flat-out wrong.
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He charges that as much as 90 percent of the published medical information that doctors rely on is flawed.
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“I take all the researchers who visit me here, and almost every single one of them asks the tree the same question,” Ioannidis tells me, as we contemplate the tree the day after the team’s meeting. “‘Will my research grant be approved?’” He chuckles, but Ioannidis (pronounced yo-NEE-dees) tends to laugh not so much in mirth as to soften the sting of his attack. And sure enough, he goes on to suggest that an obsession with winning funding has gone a long way toward weakening the reliability of medical research.
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“I assumed that everything we physicians did was basically right, but now I was going to help verify it,” he says. “All we’d have to do was systematically review the evidence, trust what it told us, and then everything would be perfect.” It didn’t turn out that way. In poring over medical journals, he was struck by how many findings of all types were refuted by later findings. Of course, medical-science “never minds” are hardly secret. And they sometimes make headlines, as when in recent years large studies or growing consensuses of researchers concluded that mammograms, colonoscopies, and PSA tests are far less useful cancer-detection tools than we had been told; or when widely prescribed antidepressants such as Prozac, Zoloft, and Paxil were revealed to be no more effective than a placebo for most cases of depression; or when we learned that staying out of the sun entirely can actually increase cancer risks; or when we were told that the advice to drink lots of water during intense exercise was potentially fatal; or when, last April, we were informed that taking fish oil, exercising, and doing puzzles doesn’t really help fend off Alzheimer’s disease, as long claimed. Peer-reviewed studies have come to opposite conclusions on whether using cell phones can cause brain cancer, whether sleeping more than eight hours a night is healthful or dangerous, whether taking aspirin every day is more likely to save your life or cut it short, and whether routine angioplasty works better than pills to unclog heart arteries.
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This array suggested a bigger, underlying dysfunction, and Ioannidis thought he knew what it was. “The studies were biased,” he says. “Sometimes they were overtly biased. Sometimes it was difficult to see the bias, but it was there.” Researchers headed into their studies wanting certain results—and, lo and behold, they were getting them. We think of the scientific process as being objective, rigorous, and even ruthless in separating out what is true from what we merely wish to be true, but in fact it’s easy to manipulate results, even unintentionally or unconsciously. “At every step in the process, there is room to distort results, a way to make a stronger claim or to select what is going to be concluded,” says Ioannidis. “There is an intellectual conflict of interest that pressures Researchers to find whatever it is that is most likely to get them funded.”
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Perhaps only a minority of researchers were succumbing to this bias, but their distorted findings were having an outsize effect on published research.
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He chose to publish one paper, fittingly, in the online journal PLoS Medicine, which is committed to running any methodologically sound article without regard to how “interesting” the results may be. In the paper, Ioannidis laid out a detailed mathematical proof that, assuming modest levels of researcher bias, typically imperfect research techniques, and the well-known tendency to focus on exciting rather than highly plausible theories, researchers will come up with wrong findings most of the time.
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The article spelled out his belief that researchers were frequently manipulating data analyses, chasing career-advancing findings rather than good science, and even using the peer-review process—in which journals ask researchers to help decide which studies to publish—to suppress opposing views.
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sure, a lot of dubious research makes it into journals, but we researchers and physicians know to ignore it and focus on the good stuff, so what’s the big deal? The other paper headed off that claim.
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Ioannidis was putting his contentions to the test not against run-of-the-mill research, or even merely well-accepted research, but against the absolute tip of the research pyramid. Of the 49 articles, 45 claimed to have uncovered effective interventions. Thirty-four of these claims had been retested, and 14 of these, or 41 percent, had been convincingly shown to be wrong or significantly exaggerated. If between a third and a half of the most acclaimed research in medicine was proving untrustworthy, the scope and impact of the problem were undeniable. That article was published in the Journal of the American Medical Association.
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When a five-year study of 10,000 people finds that those who take more vitamin X are less likely to get cancer Y, you’d think you have pretty good reason to take more vitamin X, and physicians routinely pass these recommendations on to patients. But these studies often sharply conflict with one another. Studies have gone back and forth on the cancer-preventing powers of vitamins A, D, and E; on the heart-health benefits of eating fat and carbs; and even on the question of whether being overweight is more likely to extend or shorten your life. How should we choose among these dueling, high-profile nutritional findings? Ioannidis suggests a simple approach: ignore them all.
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the odds are that in any large database of many nutritional and health factors, there will be a few apparent connections that are in fact merely flukes, not real health effects—it’s a bit like combing through long, random strings of letters and claiming there’s an important message in any words that happen to turn up.
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But even if a study managed to highlight a genuine health connection to some nutrient, you’re unlikely to benefit much from taking more of it, because we consume thousands of nutrients that act together as a sort of network, and changing intake of just one of them is bound to cause ripples throughout the network that are far too complex for these studies to detect, and that may be as likely to harm you as help you.
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nd these problems are aside from ubiquitous measurement errors (for example, people habitually misreport their diets in studies), routine misanalysis (researchers rely on complex software capable of juggling results in ways they don’t always understand), and the less common, but serious, problem of outright fraud (which has been revealed, in confidential surveys, to be much more widespread than scientists like to acknowledge).
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And so it goes for all medical studies, he says. Indeed, nutritional studies aren’t the worst. Drug studies have the added corruptive force of financial conflict of interest. The exciting links between genes and various diseases and traits that are relentlessly hyped in the press for heralding miraculous around-the-corner treatments for everything from colon cancer to schizophrenia have in the past proved so vulnerable to error and distortion, Ioannidis has found, that in some cases you’d have done about as well by throwing darts at a chart of the genome.
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Though scientists and science journalists are constantly talking up the value of the peer-review process, researchers admit among themselves that biased, erroneous, and even blatantly fraudulent studies easily slip through it.
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The ultimate protection against research error and bias is supposed to come from the way scientists constantly retest each other’s results—except they don’t. Only the most prominent findings are likely to be put to the test, because there’s likely to be publication payoff in firming up the proof, or contradicting it.
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Of those 45 super-cited studies that Ioannidis focused on, 11 had never been retested. Perhaps worse, Ioannidis found that even when a research error is outed, it typically persists for years or even decades. He looked at three prominent health studies from the 1980s and 1990s that were each later soundly refuted, and discovered that researchers continued to cite the original results as correct more often than as flawed—in one case for at least 12 years after the results were discredited.
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Medical research is not especially plagued with wrongness. Other meta-research experts have confirmed that similar issues distort research in all fields of science, from physics to economics (where the highly regarded economists J. Bradford DeLong and Kevin Lang once showed how a remarkably consistent paucity of strong evidence in published economics studies made it unlikely that any of them were right).
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Ioannidis initially thought the community might come out fighting. Instead, it seemed relieved, as if it had been guiltily waiting for someone to blow the whistle, and eager to hear more. David Gorski, a surgeon and researcher at Detroit’s Barbara Ann Karmanos Cancer Institute, noted in his prominent medical blog that when he presented Ioannidis’s paper on highly cited research at a professional meeting, “not a single one of my surgical colleagues was the least bit surprised or disturbed by its findings.” Ioannidis offers a theory for the relatively calm reception. “I think that people didn’t feel I was only trying to provoke them, because I showed that it was a community problem, instead of pointing fingers at individual examples of bad research,” he says. In a sense, he gave scientists an opportunity to cluck about the wrongness without having to acknowledge that they themselves succumb to it—it was something everyone else did.
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The irony of his having achieved this sort of success by accusing the medical-research community of chasing after success is not lost on him, and he notes that it ought to raise the question of whether he himself might be pumping up his findings.
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“If I did a study and the results showed that in fact there wasn’t really much bias in research, would I be willing to publish it?” he asks. “That would create a real psychological conflict for me.” But his bigger worry, he says, is that while his fellow researchers seem to be getting the message, he hasn’t necessarily forced anyone to do a better job. He fears he won’t in the end have done much to improve anyone’s health. “There may not be fierce objections to what I’m saying,” he explains. “But it’s difficult to change the way that everyday doctors, patients, and healthy people think and behave.”
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What they’re not trained to do is to go back and look at the research papers that helped make these drugs the standard of care.
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Tatsioni doesn’t so much fear that someone will carve out the man’s healthy appendix. Rather, she’s concerned that, like many patients, he’ll end up with prescriptions for multiple drugs that will do little to help him, and may well harm him. “Usually what happens is that the doctor will ask for a suite of biochemical tests—liver fat, pancreas function, and so on,” she tells me. “The tests could turn up something, but they’re probably irrelevant. Just having a good talk with the patient and getting a close history is much more likely to tell me what’s wrong.” Of course, the doctors have all been trained to order these tests, she notes, and doing so is a lot quicker than a long bedside chat. They’re also trained to ply the patient with whatever drugs might help whack any errant test numbers back into line.
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patients often don’t even like it when they’re taken off their drugs, she explains; they find their prescriptions reassuring.
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“Researchers and physicians often don’t understand each other; they speak different languages,” he says. Knowing that some of his Researchers are spending more than half their time seeing patients makes him feel the team is better positioned to bridge that gap; their experience informs the team’s Research with firsthand knowledge, and helps the team shape its papers in a way more likely to hit home with physicians.
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Already feeling that they’re fighting to keep patients from turning to alternative medical treatments such as homeopathy, or misdiagnosing themselves on the Internet, or simply neglecting medical treatment altogether, many researchers and physicians aren’t eager to provide even more reason to be skeptical of what doctors do—not to mention how public disenchantment with medicine could affect research funding.
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“If we don’t tell the public about these problems, then we’re no better than nonscientists who falsely claim they can heal,” he says. “If the drugs don’t work and we’re not sure how to treat something, why should we claim differently? Some fear that there may be less funding because we stop claiming we can prove we have miraculous treatments. But if we can’t really provide those miracles, how long will we be able to fool the public anyway? The scientific enterprise is probably the most fantastic achievement in human history, but that doesn’t mean we have a right to overstate what we’re accomplishing.”
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"Much of what medical researchers conclude in their studies is misleading, exaggerated, or flat-out wrong. So why are doctors-to a striking extent-still drawing upon misinformation in their everyday practice? Dr. John Ioannidis has spent his career challenging his peers by exposing their bad science." By David H. Freedman at The Atlantic on November 2010.