Impact of informative censoring in randomized trials with delayed treatment effect

Oregon Convention Center 

Time-to-event endpoints like progression-free survival and overall survival in oncology randomized trials sometimes show differential censoring patterns between study arms which can be indicative of informative censoring, depending on censoring reasons. Informative censoring can bias treatment effect estimates but few simulation studies characterized the magnitude of its impact, particularly in the context of delayed treatment effects. We use copula methods to model dependent censoring data and assess the impact of informative censoring. To improve the understanding of copula models in this context, we propose a new measure of the strength of informative censoring, the probability of events being informatively censored. To guide the choice of copula, we further propose a visual tool for examining the underlying correlation pattern. We conduct simulation studies to assess the impact of informative censoring on estimation bias for hazard ratios, as well as on empirical power of unweighted, weighted log-rank tests, and the MaxCombo test.

Informative Censoring

Copula

Randomized clinical trials

Generalized log-rank tests 

Biopharmaceutical Section