Primary Submission Category: Randomized Designs and Analyses
Beyond Fixed Restriction Time: Adaptive RMST Methods for Non-Proportional Hazards in Clinical Trials
Authors: Jinghao Sun, Eric Tchetgen Tchetgen, Douglas Schaubel,
Presenting Author: Jinghao Sun*
Restricted mean survival time (RMST) offers a compelling nonparametric alternative to hazard ratios for right-censored time-to-event data, particularly when the proportional hazards assumption is violated. By capturing the total event-free time over a specified horizon, RMST provides an intuitive and clinically meaningful measure of absolute treatment benefit. Nonetheless, selecting the restriction time L poses challenges: choosing a small L can overlook late-emerging benefits, whereas a large L may inflate variance and undermine power. We propose a novel data-driven, adaptive procedure that identifies the optimal restriction time L* from a continuous range by maximizing a criterion balancing effect size and estimation precision. Consequently, our procedure is particularly useful when the pattern of the treatment effect is unknown at the design stage. We provide a rigorous theoretical foundation that accounts for variability introduced by adaptively choosing L*. To address nonregular estimation under the null, we develop two complementary strategies: a convex-hull-based estimator, and a penalized approach that further enhances power. When restriction time candidates are defined on a discrete grid, our procedure surprisingly incurs no asymptotic penalty for selection, thus achieving near-oracle performance. In a phase III pancreatic cancer trial with transient treatment effects, our procedure uncovers clinically meaningful benefits that standard methods overlook.