Evaluating the ROC performance of markers for future events.
Receiver operating characteristic (ROC) curves play a central role in the evaluation of biomarkers and tests for disease diagnosis. Predictors for event time outcomes can also be evaluated with ROC curves, but the time lag between marker measurement and event time must be acknowledged. We discuss different definitions of time-dependent ROC curves in the context of real applications. Several approaches have been proposed for estimation. We contrast retrospective versus prospective methods in regards to assumptions and flexibility, including their capacities to incorporate censored data, competing risks and different sampling schemes. Applications to two datasets are presented.
Pepe
Margaret S
MS
Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., M2-B500, Seattle, WA 98109, USA. mspepe@u.washington.edu
Zheng
Yingye
Y
Jin
Yuying
Y
Huang
Ying
Y
Parikh
Chirag R
CR
Levy
Wayne C
WC
D015415:Biomarkers / Q000032:analysis*; D005544:Forecasting; D011379:Prognosis; D011446:Prospective Studies; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity
D015415:Biomarkers