Time-to-Event Surrogate Endpoint Predicting Overall Survival

• Activity Number: 175
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Susan Halabi*+ and Chen-Yen Lin
• Companies: Duke University and Duke University
• Keywords: survival ; Cox proportional hazards ; Prentice criteria ; surrogate ; clinical trials ; cancer

Abstract

Prentice developed formal criteria for testing surrogacy of the true endpoint. Prentice's criteria require that the treatment is prognostic of the true clinical outcome; and the surrogate endpoint be associated with, and fully capture the net effect of treatment on (third criterion), clinical outcome. We are interested in testing whether progression-free survival is a surrogate of overall survival. We consider the surrogate marker to be a time-to-event endpoint. When the covariate in the Cox proportional hazards model is subject to censoring, Lee proposed replacing the censored observation by a weighted average from uncensored observations. Their method, only considered a single covariate, however, we extend their method to allow for multiple covariates. In our simulations, with high proportion, the proposed method successfully identifies if the biomarker is truly surrogate using Prentice's third criterion. Simulation results suggest that the proposed method estimates the regression parameters more accurately than the naïve method that only uses complete observations to fit a Cox model. We illustrate this method by applying it to a phase III clinical trial in prostate cancer.