Increasing power in randomized trials with right censored outcomes through covariate adjustment.

ABSTRACT

Targeted maximum likelihood methodology is applied to provide a test that makes use of the covariate data that are commonly collected in randomized trials, and does not require assumptions beyond those of the logrank test when censoring is uninformative. Under informative censoring, the logrank test is biased, whereas the test provided in this article is consistent under consistent estimation of the censoring mechanism or the conditional hazard for survival. Two approaches based on this methodology are provided (1) a substitution-based approach that targets treatment and time-specific survival from which the logrank parameter is estimated, and (2) directly targeting the logrank parameter.