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

ABSTRACT

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.

KEYWORDS:

• Markov Model
• partitioned survival model
• economic evaluation
• CADTH

Article Highlights

• The Markov and partitioned survival (PS) models are commonly used for the cost-effective analysis of cancer treatments. Whether large differences exist in the results obtained using both models in empirical research and what the differences in methodology are between the two methods remain unknown. This study is the first to summarize all current empirical studies and CADTH reports that used both models at the same time and provides recommendations for the choice of models in the economic evaluation of cancer treatments.

• Among all the literature and CADTH reports that used both the Markov model and partitioned survival model during the past 5 years, we found that the results from the Markov model and partitioned survival model were similar when the model structure and model assumptions were the same.

• The following aspects have an impact on the results: (1) model structure; (2) model assumptions; (3) software use; (4) the data requirements of the model; (5) the data source; (6) characteristics of the two models themselves; (7) extrapolation methods; and (8) external verification. The deviations of the partitioned survival model indicated in the previous studies have not been confirmed in empirical studies. We look forward to future studies that can provide relevant evidence so that researchers can choose appropriate models when evaluating oncology drug cost-effectiveness.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewers disclosure

Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

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Additional information

Funding

No funding was received for this study.