Will the Markov model and partitioned survival model lead to different results? A review of recent economic evidence of cancer treatments.

Introduction: Balancing the high cost of treatment brought about by new therapies has become a problem that needs to be considered. Cost-effectiveness analysis (CEA) is a commonly used method that provides information on the potential value of new cancer treatments. The Markov and partitioned survival (PS) models are commonly used. Whether the results differ between the models in empirical research and the methodological differences remain unclear.Areas covered: A review was conducted to identify Canadian Agency for Drugs and Technologies in Health (CADTH) reports and papers published during the past 5 years that reported full economic evaluations of cancer treatments and used both models. In the included studies, most results except one obtained using the two models did not significantly differ.Expert opinion: Not enough evidence could support that there existed relevant bias in empirical studies about the PS model, and more methodological research and application of empirical research should be performed. We recommended that when individual data are available and the model structure is not complicated, the PS model is more appropriate. Both the PS and Markov models are recommended to assess model structure uncertainty.