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[Competitive risks and multi-state models in epidemiology].

D Commenges1

  • 1INSERM U. 330, Université de Bordeaux 2, 146, rue Léo Saignat, 33076 Bordeaux Cedex, France. daniel.commenges@bordeaux.inserm.fr

Revue D'Epidemiologie Et De Sante Publique
|February 16, 2000
PubMed
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Multi-state models offer advanced survival analysis by incorporating competing risks and chronic disease progression. Careful interpretation of survival functions is crucial for accurate cause-specific mortality rate estimation.

Area of Science:

  • Biostatistics
  • Epidemiology
  • Survival Analysis

Context:

  • Survival models are foundational in biostatistics.
  • Competing risks models extend survival analysis to multiple causes of mortality.
  • Chronic disease progression often involves multiple health states.

Purpose:

  • To introduce multi-state models for survival analysis.
  • To explain the application of multi-state models in competing risks and chronic disease studies.
  • To highlight methods for estimating transition intensities and interpreting survival functions.

Summary:

  • Multi-state models generalize survival analysis, accommodating complex transitions between states.
  • Competing risks models within this framework allow for cause-specific mortality rate estimation.

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  • The illness-death model is a key application for studying chronic diseases, with transition intensities estimable via Cox models in continuous time.

    • Impact:

    • Provides a framework for more nuanced survival analyses.
    • Enhances understanding of disease progression and mortality causes.
    • Offers guidance on avoiding common interpretation pitfalls in survival functions.