Identification and inference for subgroups with differential treatment efficacy from randomized controlled trials with survival outcomes through multiple testing.

With the uptake of targeted therapies, instead of the "one-fits-all" approach, modern randomized controlled trials (RCTs) often aim to develop treatments that target a subgroup of patients. Motivated by analyzing the Age-Related Eye Disease Study (AREDS) data, a large RCT to study the efficacy of nutritional supplements in delaying the progression of an eye disease, age-related macular degeneration (AMD), we develop a simultaneous inference procedure to identify and infer subgroups with differential treatment efficacy in RCTs with time-to-event outcomes. Specifically, we formulate the multiple testing problem through contrasts and construct their simultaneous confidence intervals, which appropriately control both within- and across-marker multiplicity. Realistic simulations are conducted using real genotype data to evaluate the method performance under various scenarios. The method is then applied to AREDS to assess the efficacy of antioxidants and zinc combination in delaying AMD progression. Multiple gene regions including ESRRB-VASH1 on chromosome 14 have been identified with subgroups showing differential efficacy. We further validate our findings in an independent subsequent RCT, AREDS2, by discovering consistent differential treatment responses in the targeted and non-targeted subgroups identified from AREDS. This multiple-testing-based simultaneous inference approach provides a step forward to confidently identify and infer subgroups in modern drug development.