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Time-Dependent AUC with Right-Censored Data: A Survey

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Risk Assessment and Evaluation of Predictions

Part of the book series: Lecture Notes in Statistics ((LNSP,volume 215))

Abstract

The ROC curve and the corresponding AUC are popular tools for the evaluation of diagnostic tests. They have been recently extended to assess prognostic markers and predictive models. However, due to the many particularities of time-to-event outcomes, various definitions and estimators have been proposed in the literature. This review article aims at presenting the ones that accommodate to right-censoring, which is common when evaluating such prognostic markers.

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Author information

Authors and Affiliations

  1. University of Bordeaux, ISPED and INSERM U897, Bordeaux, France

    Paul Blanche

  2. Conservatoire national des arts et métiers, Paris, France

    Aurélien Latouche

  3. UMRESTTE (Univ. Lyon 1 and IFSTTAR), Bron, France

    Vivian Viallon

Authors
  1. Paul Blanche
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  2. Aurélien Latouche
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  3. Vivian Viallon
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Corresponding author

Correspondence to Paul Blanche .

Editor information

Editors and Affiliations

  1. University of Maryland, College Park, Maryland, USA

    Mei-Ling Ting Lee

  2. National Cancer Institute Div. Cancer Epidemiology & Genetics, Bethesda, Maryland, USA

    Mitchell Gail

  3. National Cancer Institute, Bethesda, Maryland, USA

    Ruth Pfeiffer

  4. Centers for Disease Control and Prevention, Atlanta, Georgia, USA

    Glen Satten

  5. Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA

    Tianxi Cai

  6. Department of Mathematics, Imperial College London, London, United Kingdom

    Axel Gandy

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Blanche, P., Latouche, A., Viallon, V. (2013). Time-Dependent AUC with Right-Censored Data: A Survey. In: Lee, ML., Gail, M., Pfeiffer, R., Satten, G., Cai, T., Gandy, A. (eds) Risk Assessment and Evaluation of Predictions. Lecture Notes in Statistics, vol 215. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8981-8_11

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