14: Future-Dependent Event Definitions in Time-to-Event Analysis: Bias and an Analytic Approach

Thomas M. Menino Convention & Exhibition Center 

Some time-to-event analyses use future-dependent event definitions, in which event occurrence can only be determined using future information. For example, diagnosis of certain conditions may require two positive tests, with event times retrospectively assigned to the first test. Individuals with a single positive by the end of follow-up are typically censored, without accounting for the possibility of future confirmation, which leads to bias in Kaplan-Meier estimation. We propose a clone-based weighting approach to address this uncertainty. For individuals censored after a single event, the method generates clones representing alternative future event status and weights them by the probability of future event occurrence. Simulation studies assessed bias from future-dependent outcomes and evaluated the proposed approach. The results show that such outcomes can induce substantial bias in Kaplan–Meier estimation, while the proposed clone-weighting approach mitigates bias. Overall, these findings highlight the importance of avoiding time-to-event outcomes defined using future information and suggest clone-based weighting as an analytic approach when such definitions are unavoidable.

Survival Analysis

Time-to-event data 

Biometrics Section