Evaluating the ROC performance of markers for future events

Margaret S. Pepe, Yingye Zheng, Yuying Jin, Ying Huang, Chirag R. Parikh, Wayne C. Levy

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)86-113
Number of pages28
JournalLifetime Data Analysis
Issue number1
StatePublished - Mar 2008
Externally publishedYes


  • Diagnostic test
  • Prediction
  • Prognosis
  • Sensitivity
  • Specificity

ASJC Scopus subject areas

  • Applied Mathematics


Dive into the research topics of 'Evaluating the ROC performance of markers for future events'. Together they form a unique fingerprint.

Cite this