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Semi-Markov Models for Quality of Life Data with Censoring

  • Natacha Heutte
  • Catherine Huber-Carol

Abstract

We present a semi-parametric, semi-Markov, multi-state model for quality of life data measured in continuous time with right censoring. The model is based on the same principles as the Cox proportional hazards model. The states are defined by categorizing a quality of life score as measured using a standard instrument. Death is considered as a separate state in the model. Transitions between the states represent changes in quality of life (or death) and follow a competing risk framework. We describe the model and derive relevant estimators. We illustrate the methodology using data from a cancer clinical trial comparing quality of life for two treatment regimens.

Keywords

Sojourn Time Life Data Cancer Clinical Trial Partial Likelihood Markov Renewal Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  • Natacha Heutte
    • 1
  • Catherine Huber-Carol
    • 1
    • 2
  1. 1.Université René DescartesFrance
  2. 2.U472 INSERMFrance

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