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Registered Clinical Trials Make Positive Findings Vanish

schwit1 writes: The requirement that medical researchers register in detail the methods they intend to use in their clinical trials, both to record their data as well as document their outcomes, caused a significant drop in trials producing positive results. From Nature: "The study found that in a sample of 55 large trials testing heart-disease treatments, 57% of those published before 2000 reported positive effects from the treatments. But that figure plunged to just 8% in studies that were conducted after 2000. Study author Veronica Irvin, a health scientist at Oregon State University in Corvallis, says this suggests that registering clinical studies is leading to more rigorous research. Writing on his NeuroLogica Blog, neurologist Steven Novella of Yale University in New Haven, Connecticut, called the study "encouraging" but also "a bit frightening" because it casts doubt on previous positive results."

In other words, before they were required to document their methods, research into new drugs or treatments would prove the success of those drugs or treatment more than half the time. Once they had to document their research methods, however, the drugs or treatments being tested almost never worked. The article also reveals a failure of the medical research community to confirm their earlier positive results. It appears the medical research field has forgotten this basic tenet of science: A result has to be proven by a second independent study before you can take it seriously. Instead, they would do one study, get the results they wanted, and then declare success.

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  1. Re:Not even wrong by JoshuaZ · · Score: 5, Insightful

    No, it is a pretty accurate summary of what is happening. You focus post-hoc on where you got a good result. Say for example you want to test a new anti-diabetes drug. Does the drug work in the general population? Well, data doesn't support that. So then you look at subgroups. Does your data show success in say just men or just women? What about black men? Black women? White women? Etc. This isn't the only serious problem, sometimes one can choose which statistical tests to do or how to compensate for complicating factors. If you have enough choices you can make anything looks successful.