Randomized clinical trial (RCT) results guide clinical decision-making, but trial results usually only offer information on mean treatment effects, overall or by large subgroups. For example, a trial showing the superiority of a surgery over noninvasive management may provide evidence that patients meeting the trial enrollment criteria, on average, benefit from surgery. However, no single patient may match the typical patient characteristics or outcome. Meanwhile, there is likely heterogeneity in experience, with some people more prone to experience worse outcomes with the therapy shown to produce a superior outcome.1 Traditional subgroup analysis is often underpowered, and evaluating one clinical characteristic at a time may not inform the likely outcome of any individual patient.
Mori M, Spertus JA, Krumholz HM. Data-Driven Individualized Surgical Decision-making: Beyond “Better on Average” Clinical Trial Results. JAMA Surg. 2022;157(2):93–94. doi:10.1001/jamasurg.2021.5614
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