Markov models are increasingly used in economic evaluations of (new) treatments for chronic diseases. In this study we propose a Markov model with health states defined by the disease activity score (DAS) to be used to extrapolate efficacy data from short-term clinical trials in rheumatoid arthritis to longer term cost-effectiveness results. Moreover, we perform an initial validation of this model.
To test the validity of the model, the expected disease course (according to the model) was first compared with the observed disease course in an inception cohort of newly diagnosed rheumatoid arthritis patients. Then the relationship of the health states with utility and costs was investigated. Finally, costs and QALYs were calculated for usual care of patients in the first 5 years of their disease using the model and compared with the literature.
The model seemed to be able to extrapolate 1-year efficacy data as seen by a comparable distribution over the Markov states between the model results and the observational data. The health states had a significant relationship with costs and utility, and population characteristics had only a moderate effect on the cost and utility values of the Markov states. The distribution over the Markov states resulted in 3.266 expected QALYs per patient over 5 years. The expected medical and total costs per patient over 5 years were 6754 euro (1997 values) and 12,641 euro, respectively, for standard rheumatoid arthritis care in The Netherlands.
The developed Markov model seems a valid model for use in economic evaluations in rheumatoid arthritis. The model produced similar utilities, but lower total costs, to those in previously published studies. Although the steps to develop and validate this Markov model were applied in the context of rheumatoid arthritis, they can be generalised to other chronic diseases.