Multi-state models for colon cancer recurrence and death with a cured fraction

A. S.C. Conlon, J. M.G. Taylor, D. J. Sargent

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


In cancer clinical trials, patients often experience a recurrence of disease prior to the outcome of interest, overall survival. Additionally, for many cancers, there is a cured fraction of the population who will never experience a recurrence. There is often interest in how different covariates affect the probability of being cured of disease and the time to recurrence, time to death, and time to death after recurrence. We propose a multi-state Markov model with an incorporated cured fraction to jointly model recurrence and death in colon cancer. A Bayesian estimation strategy is used to obtain parameter estimates. The model can be used to assess how individual covariates affect the probability of being cured and each of the transition rates. Checks for the adequacy of the model fit and for the functional forms of covariates are explored. The methods are applied to data from 12 randomized trials in colon cancer, where we show common effects of specific covariates across the trials.

Original languageEnglish (US)
Pages (from-to)1750-1766
Number of pages17
JournalStatistics in Medicine
Issue number10
StatePublished - May 10 2014


  • Colon cancer
  • Cox-Snell residuals
  • Cure model
  • Deviance residuals
  • Multi-state model

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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