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Evaluating the ROC performance of markers for future events |
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| Authors: | Margaret S. Pepe Yingye Zheng Yuying Jin Ying Huang Chirag R. Parikh Wayne C. Levy |
| Affiliation: | (1) Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., M2-B500, Seattle, WA 98109, USA;(2) Department of Biostatistics, University of Washington, Box 357232, F-600 HSB, Seattle, WA 98195, USA;(3) Section of Nephrology, Department of Internal Medicine, Yale University School of Medicine, P.O. Box 208029, New Haven, CT 06520-8029, USA;(4) University of Washington Medical Center, 1959 N.E. Pacific Street, Campus Box 356422, Seattle, WA 98195-6422, USA |
| Abstract: | 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. |
| Keywords: | Prediction Diagnostic test Prognosis Sensitivity Specificity |
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