Modeling Approaches in Cost-Effectiveness Analysis of Disease-Modifying Therapies for Relapsing–Remitting Multiple Sclerosis: An Updated Systematic Review and Recommendations for Future Economic Evaluations

Abstract

Background

Numerous cost-effectiveness analyses (CEAs) of disease-modifying therapies (DMTs) for relapsing–remitting multiple sclerosis (RRMS) have been published in the last three decades. Literature reviews of the modeling methods and results from these CEAs have also been published. The last literature review that focused on modeling methods, without country or time horizon in the inclusion criteria, included studies published up to 2012. Since then, new DMTs have become available, and new models and data sources have been used to assess their cost effectiveness.

Objective

The aim of this systematic review was to provide a detailed and comprehensive description of the relevant aspects of economic models used in CEAs of DMTs for RRMS, to understand how these models have progressed from recommendations provided in past reviews, what new approaches have been developed, what issues remain, and how they could be addressed.

Methods

EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), the National Health System (NHS) Economic Evaluations Database, the Health Technology Assessment (HTA) Database, and EconLit were searched for cost-effectiveness studies of DMTs for RRMS that used decision-analytic models, published in English between 1 January 2012 and 24 December 2017. The inclusion criteria were as follows: being a full economic evaluation, a decision-analytic model was used, the target population concerned adult patients with RRMS, and being available in full-text format. Studies were not excluded based on the methodological quality. The background information of the included studies, as well as specific information on the components of the economic models related to the areas of recommendation from previous reviews were extracted.

Results

Twenty-three studies from ten countries were included. The model structure of these studies has converged over time, characterizing the course of disease progression in terms of changes in disability and the occurrence of relapses over time. Variations were found in model approach; data sources for the natural course of the disease and comparative efficacy between DMTs; number of lines of treatment modeled; long-term efficacy waning and treatment discontinuation assumptions; type of withdrawal; and criteria for selecting adverse events. Main areas for improvement include using long-term time horizons and societal perspective; reporting relevant health outcomes; conducting scenario analyses using different sources of natural history and utility values; and reporting how the model was validated.

Conclusion

The structure of economic models used in CEAs of DMTs for RRMS has converged over time. However, variation remains in terms of model approach, inputs, and assumptions. Though some recommendations from previous reviews have been incorporated in later models, areas for improvement remain.

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