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Updated: Jul 23, 2026
Development of Obliterative Bronchiolitis in a Murine Model of Orthotopic Lung Transplantation
Published on: July 10, 2012
A piecewise-homogeneous Markov chain process of lung transplantation
L D Sharples1, G I Taylor, M Faddy
1MRC Biostatistics Unit, Cambridge, UK.
Background:
Markov and semi-Markov models are increasingly used in clinical and public health epidemiology to represent disease processes. We present a Markov model of events following lung transplantation as a case study in clinical epidemiology.
Methods:
A five-state discrete-time Markov model with two-way transitions between acute event states is applied to the analysis of 356 lung transplant patients. A two-state continuous time Markov model for chronic disease onset is fitted. Values of transition parameters are estimated by maximum likelihood using numerical methods.
Results:
Accurate estimates of acute and chonic event rates, and survival probabilities are calculated from transition probabilities. Costs attributed to different acute and chronic states are calculated.
Conclusions:
Transition models provide a useful and flexible representation of acute and chronic events and can be used to explore the economic impact of changes in therapy.
