Identifying Exceptional Responders in Randomized Trials: An Optimization Approach

Abstract

In randomized clinical trials, there may be a benefit to identifying subgroups of the study population for which a treatment was exceptionally effective or ineffective. We present an efficient mixed-integer optimization formulation that can directly find an interpretable subset with maximum (or minimum) average treatment effect. Using both simulated and real data from randomized trials, we demonstrate the effectiveness and stability of the optimization approach in identifying subsets with exceptional response and verifying their statistical significance.