A Markov model for estimating the cost-effectiveness of immunotherapy for newly diagnosed multiple myeloma patients

Massimo Bilancia, Antonio Giovanni Solimando, Fabio Manca, Angelo Vacca and Roberto Ria

Computational Statistics & Data Analysis, 2025, vol. 206, issue C

Abstract: Multiple myeloma (MM) is a malignancy of plasma cells, originating from B lymphocytes and accumulating within the bone marrow. The prevalence of MM has increased in industrialized countries, representing 1-1.8% of all cancers and 15% of hematologic malignancies. Immunotherapy has broadened therapeutic options for MM, offering treatments with generally improved efficacy and reduced toxicity compared to conventional therapies. Daratumumab, a monoclonal antibody recently granted regulatory approval, exemplifies this advancement, demonstrating improved patient outcomes. However, the substantial cost of daratumumab has significantly increased per-patient treatment expenditures. Consequently, the economic burden associated with this new class of therapies warrants careful evaluation of their cost-effectiveness. To address this, a six-state non-stationary Markov model was developed for cost-effectiveness analysis of immunotherapy in newly diagnosed MM patients and, more broadly, in the oncohematological patient population. This model aims to provide healthcare professionals and policymakers with actionable insights into cost-effective interventions, supporting informed decisions regarding optimal treatment strategies.

Keywords: Multiple myeloma; Pharmaeconomics; Cancer immunotherapy; Markov cohort models; Cost-effectiveness analysis; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:206:y:2025:i:c:s0167947325000064

DOI: 10.1016/j.csda.2025.108130

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