Censoring-robust time-dependent receiver operating characteristic curve estimators

Stat Med. 2021 Dec 30;40(30):6885-6899. doi: 10.1002/sim.9216. Epub 2021 Oct 17.

Abstract

Time-dependent receiver operating characteristic curves are often used to evaluate the classification performance of continuous measures when considering time-to-event data. When one is interested in evaluating the predictive performance of multiple covariates, it is common to use the Cox proportional hazards model to obtain risk scores; however, previous work has shown that when the model is mis-specified, the estimand corresponding to the partial likelihood estimator depends on the censoring distribution. In this manuscript, we show that when the risk score model is mis-specified, the AUC will also depend on the censoring distribution, leading to either over- or under-estimation of the risk score's predictive performance. We propose the use of censoring-robust estimators to remove the dependence on the censoring distribution and provide empirical results supporting the use of censoring-robust risk scores.

Keywords: area under the curve; model mis-specification; predictive performance; survival analysis; time-dependent receive operating characteristic curves.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Humans
  • Probability
  • Proportional Hazards Models
  • ROC Curve*