Research Article

Tutorial in biostatistics: competing risks and multi-state models

  1. H. Putter1,†,*,
  2. M. Fiocco1,
  3. R. B. Geskus1,2,3,‡

Article first published online: 10 OCT 2006

DOI: 10.1002/sim.2712

Issue

Statistics in Medicine

Statistics in Medicine

Volume 26, Issue 11, pages 2389–2430, 20 May 2007

Additional Information

How to Cite

Putter, H., Fiocco, M. and Geskus, R. B. (2007), Tutorial in biostatistics: competing risks and multi-state models. Statist. Med., 26: 2389–2430. doi: 10.1002/sim.2712

Author Information

  1. 1

    Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands

  2. 2

    Amsterdam Health Service, Amsterdam, The Netherlands

  3. 3

    Academic Medical Center, Amsterdam, The Netherlands

  1. †

    Contributed equally to this tutorial.

  2. ‡

    Contributed equally to this tutorial.

*Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, P.O. Box 9604, 2300 RC, Leiden, The Netherlands

  1. †

    Contributed equally to this tutorial.

  2. ‡

    Contributed equally to this tutorial.

Publication History

  1. Issue published online: 4 APR 2007
  2. Article first published online: 10 OCT 2006
  3. Manuscript Accepted: 31 JUL 2006
  4. Manuscript Received: 26 OCT 2005

Funded by

  • Zon-MW. Grant Number: 0032-4633-2324

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Keywords:

  • competing risks;
  • multi-state model;
  • survival analysis;
  • prognostic factors;
  • prediction

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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