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Tutorial in biostatistics: competing risks and multi-state models

Authors

  • H. Putter,

    Corresponding author
    1. Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
    • Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, P.O. Box 9604, 2300 RC, Leiden, The Netherlands
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    • Contributed equally to this tutorial.

  • M. Fiocco,

    1. Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
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  • R. B. Geskus

    1. Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
    2. Amsterdam Health Service, Amsterdam, The Netherlands
    3. Academic Medical Center, Amsterdam, The Netherlands
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    • Contributed equally to this tutorial.


Abstract

Standard survival data measure the time span from some time origin until the occurrence of one type of event. If several types of events occur, a model describing progression to each of these competing risks is needed. Multi-state models generalize competing risks models by also describing transitions to intermediate events. Methods to analyze such models have been developed over the last two decades. Fortunately, most of the analyzes can be performed within the standard statistical packages, but may require some extra effort with respect to data preparation and programming. This tutorial aims to review statistical methods for the analysis of competing risks and multi-state models. Although some conceptual issues are covered, the emphasis is on practical issues like data preparation, estimation of the effect of covariates, and estimation of cumulative incidence functions and state and transition probabilities. Examples of analysis with standard software are shown. Copyright © 2006 John Wiley & Sons, Ltd.

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