title: Nonparametric inference for assessing treatment efficacy in randomized clinical trials with a time-to-event outcome and all-or-none compliance.
abstract: To evaluate the biological efficacy of a treatment in a randomized clinical trial, one needs to compare patients in the treatment arm who actually received treatment with the subgroup of patients in the control arm who would have received treatment had they been randomized into the treatment arm. In practice, subgroup membership in the control arm is usually unobservable. This paper develops a nonparametric inference procedure to compare subgroup probabilities with right-censored time-to-event data and unobservable subgroup membership in the control arm. We also present a procedure to estimate the onset and duration of treatment effect. The performance of our method is evaluated by simulation. An illustration is given using a randomized clinical trial for melanoma.
authors.affiliation: Department of Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, California 90095, U.S.A. , relashof@biomath.ucla.edu.
authors.forename: Robert M
authors.initials: RM
authors.lastname: Elashoff
authors.forename: Gang
authors.initials: G
authors.lastname: Li
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhou
keywords: Biological efficacy; Censoring; Counting process; Martingale; Noncompliance; Survival probability