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J Med Econ. 2020 Jan 21:1-10. doi: 10.1080/13696998.2019.1711100. [Epub ahead of print]

Modeling the impact of patient treatment preference on health outcomes in relapsing-remitting multiple sclerosis.

Author information

1
Precision Health Economics, Los Angeles, CA, USA.
2
Global Evidence & Value Development, Global Research & Development, EMD Serono Inc, Billerica, MA, USA.

Abstract

Aims: Model how moving from current disease-modifying drug (DMD) prescribing patterns for relapsing-remitting multiple sclerosis (RRMS) observed in the United Kingdom (UK) to prescribing patterns based on patient preferences would impact health outcomes over time.Materials and methods: A cohort-based Markov model was used to measure the effect of DMDs on long-term health outcomes for individuals with RRMS. Data from a discrete choice experiment were used to estimate the market shares of DMDs based on patient preferences (i.e. preference shares). These preference shares and real-world UK market shares were used to calculate the effect of prescribing behavior on relapses, disability progression, and quality-adjusted life-years (QALYs). The incremental benefit of patient-centered prescribing over current practices for the UK RRMS population was then estimated; scenario and sensitivity analyses were also conducted.Results: Compared to current prescribing practices, when UK patients with RRMS were treated following patient preferences, health outcomes were improved. This population was expected to experience 501,690 relapses and gain 1,003,263 discounted QALYs over 50 years under patient-centered prescribing practices compared to 538,417 relapses and 958,792 discounted QALYs under current practices (-6.8% and +4.6%, respectively). Additionally, less disability progression was observed when prescribed treatment was based on patient preferences. In a scenario analysis where only oral treatments were considered, the results were similar, although the magnitude of benefit was smaller. Number of relapses was most sensitive to how the annualized relapse rate was modeled; disability progression was most sensitive to mortality rate assumptions.Limitations: Treatment efficacy estimates applied to various models in this study were based on data derived from clinical trials, rather than real-world data; the impact of patient-centered prescribing on treatment adherence and/or switching was not modeled.Conclusions: The population of UK RRMS patients may experience overall health gains if patient preferences are better incorporated into prescribing practices.

KEYWORDS:

I10; I19; Relapsing-remitting multiple sclerosis; budget impact; disease-modifying drug; patient preference model; prescribing patterns

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