When Averages Hide Individual Differences in Clinical Trials
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The development and approval of medical therapies today relies on a mid-20th-century invention called the randomized clinical trial. Patients are recruited for an experimental treatment; a random subsample gets a placebo or different approach; any difference in the aggregated outcomes of the groups is attributed to the effects of the treatment. But the risks and benefits of a treatment typically vary substantially from one patient to the next. A small minority of high-risk patients can manifest dramatic results that obscure the fact that the same treatment is barely beneficial or actually harmful to most patients. The authors advocate using risk-stratified analysis to better understand how treatments affect the individual.