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The International Journal of Biostatistics

Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.

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Non-Markov Multistate Modeling Using Time-Varying Covariates, with Application to Progression of Liver Fibrosis due to Hepatitis C Following Liver Transplant

Peter Bacchetti1 / Ross D Boylan2 / Norah A Terrault3 / Alexander Monto4 / Marina Berenguer5

1University of California, San Francisco

2University of California, San Francisco

3University of California, San Francisco

4University of California, San Francisco

5Hospital Universitario La Fe

Citation Information: The International Journal of Biostatistics. Volume 6, Issue 1, ISSN (Online) 1557-4679, DOI: 10.2202/1557-4679.1213, February 2010

Publication History

Published Online:

Multistate modeling methods are well-suited for analysis of some chronic diseases that move through distinct stages. The memoryless or Markov assumptions typically made, however, may be suspect for some diseases, such as hepatitis C, where there is interest in whether prognosis depends on history. This paper describes methods for multistate modeling where transition risk can depend on any property of past progression history, including time spent in the current stage and the time taken to reach the current stage. Analysis of 901 measurements of fibrosis in 401 patients following liver transplantation found decreasing risk of progression as time in the current stage increased, even when controlled for several fixed covariates. Longer time to reach the current stage did not appear associated with lower progression risk. Analysis of simulation scenarios based on the transplant study showed that greater misclassification of fibrosis produced more technical difficulties in fitting the models and poorer estimation of covariate effects than did less misclassification or error-free fibrosis measurement. The higher risk of progression when less time has been spent in the current stage could be due to varying disease activity over time, with recent progression indicating an "active" period and consequent higher risk of further progression.

Keywords: fibrosis; hepatitis C; liver transplant; memoryless assumptions; multistate modeling

Citing Articles

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Norah Terrault
Best Practice & Research Clinical Gastroenterology, 2012, Volume 26, Number 4, Page 531
A. Rubín, V. Aguilera, and M. Berenguer
Clinics and Research in Hepatology and Gastroenterology, 2011, Volume 35, Number 12, Page 805
Marina Berenguer and Detlef Schuppan
Journal of Hepatology, 2013, Volume 58, Number 5, Page 1028
Marina Berenguer
Liver Transplantation, 2011, Volume 17, Number S3, Page S24
Andrew C. Titman
Biometrics, 2011, Volume 67, Number 3, Page 780
Richard J. Cook and Jerald F. Lawless
Statistics in Biosciences, 2014, Volume 6, Number 1, Page 127

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