Impact of Informative Censoring on Statistics Used in the Validation of Surrogate Endpoints in Oncology

Abstract

In the past few years, biomarkers such as progression free survival (PFS) and time to progression (TTP), have been increasingly used as surrogate endpoints for overall survival (OS) in clinical trials in oncology. An issue occurs when clinical trials which demonstrated statistically significant treatment effect for the surrogate marker, shows no significant effect on the true outcome of interest, OS. It is possible that this lack of concordant results was due to informative censoring. Although it is known that informative censoring may bias the observed results, it is not clear what impact informative censoring has on the surrogacy of one marker in relation to a true outcome. In this thesis, we investigated how informative censoring could affect the results of a surrogate endpoint, and how would that affect the surrogacy of that endpoint. A simulation study was conducted to evaluate the impact of informative censoring on the treatment effect on TTP and the outcomes of the surrogate validation methods relative effect (RE), surrogate threshold effect (STE), and the difference between the treatment effect on TTP and on OS (IRE). The results of the simulation showed that having informative censoring for TTP will indeed bias the treatment effect on TTP as well as the results for the validation methods, RE, STE, and IRE. Hence, we conclude that the effect of informative censoring can greatly influence the ability to validate a surrogate marker, and additionally can bias the ability to determine the efficacy of a new therapy from a clinical trial using a surrogate marker as the primary outcome.