Treatment Heterogeneity and Individual Qualitative Interaction
AIR FORCE FLIGHT TEST CENTER EDWARDS AFB CA
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Plausibility of high variability in treatment effects across individuals has been recognized as an important consideration in clinical studies. Surprisingly, little attention has been given to evaluating this variability in the design of clinical trials or analyses of resulting data. High variation in a treatments efficacy or safety across individuals referred to herein as treatment heterogeneity may have important consequences because the optimal treatment choice for an individual may be different from that suggested by a study of average effects. We call this an individual qualitative interaction IQI. Borrowing terminology from earlier work, we refer to a qualitative interaction QI being present when the optimal treatment varies across groups of individuals. At least three techniques have been proposed to investigate treatment heterogeneity techniques to detect a QI, use of measures such as the density overlap of two outcome variables under different treatments, and use of crossover designs to observe individual effects. We elucidate underlying connections among them, their limitations, and some assumptions that may be required. We do so under a potential outcomes framework that can add insights to results from usual data analyses and to study design features that improve the capability to more directly assess treatment heterogeneity.
- Medicine and Medical Research