Discrete-event simulation for economic evaluation: A real-world, post-market cost-effectiveness analysis in multiple myeloma using registry data

Adam Irving (), Dennis Petrie, Anthony Harris (), Laura Fanning (), Erica M. Wood (), Elizabeth Moore (), Cameron Wellard (), Neil Waters (), Bradley Augustson (), Gordon Cook (), Francesca Gay (), Georgia McCaughan (), Peter Mollee (), Andrew Spencer () and Zoe K. McQuilten ()
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Adam Irving: Centre for Health Economics, Monash Business School; Transfusion Research Unit, Monash University
Anthony Harris: Centre for Health Economics, Monash Business School, Monash University
Laura Fanning: Centre for Health Economics, Monash Business School, Monash University
Erica M. Wood: Transfusion Research Unit, School of Public Health and Preventive Medicine, Monash University
Elizabeth Moore: Transfusion Research Unit, School of Public Health and Preventive Medicine, Monash University
Cameron Wellard: Transfusion Research Unit, School of Public Health and Preventive Medicine, Monash University
Neil Waters: Transfusion Research Unit, School of Public Health and Preventive Medicine, Monash University
Bradley Augustson: Sir Charles Gairdner Hospital, Nedlands, Perth, Western Australia
Gordon Cook: Leeds Institute of Clinical Trials Research, University of Leeds, United Kingdom
Francesca Gay: Oncology and Hematology Department, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza di Torino, Italy
Georgia McCaughan: Department of Haematology, St Vincent’s Hospital Sydney; School of Clinical Medicine, UNSW
Peter Mollee: Princess Alexandra Hospital, The University of Queensland, Brisbane
Andrew Spencer: Malignant Haematology and Stem Cell Transplantation Service, Alfred Health–Monash University, Melbourne
Zoe K. McQuilten: Transfusion Research Unit, School of Public Health and Preventive Medicine, Monash University

No 2025-18, Working Papers from Centre for Health Economics, Monash University

Abstract: Background Health technology assessments traditionally rely on cohort modelling using clinical trial data, leaving uncertainties about real-world cost-effectiveness. This post-market economic evaluation used individual-level modelling with a discrete-event simulation (DES) framework and registry data to estimate the real-world cost-effectiveness of bortezomib, lenalidomide and dexamethasone (VRd) in Australia which was listed for newly diagnosed multiple myeloma in 2019. Methods We conducted an economic evaluation of VRd versus No VRd using the EpiMAP Myeloma model, a DES model powered by risk equations from the Australia & New Zealand Myeloma and Related Diseases Registry. This approach captured individual patient heterogeneity and complex treatment pathways through up to nine lines of therapy. We assessed differences in quality-adjusted life-years (QALYs) and costs over a lifetime horizon, with bootstrapping to quantify uncertainty. Results VRd was associated with positive incremental QALYs (0.16; 95% CI: 0.10, 0.21) and incremental cost (A$10K; 95% CI: A$8K, A$11K). Improved response to first-line therapy with VRd was predicted to marginally increase receipt of autologous stem cell transplantation by 1.1% (95% CI: 0.6, 1.7%), significantly increase receipt of maintenance therapy by 13.8% (95% CI: 10.4%, 17.3%) and marginally offset further lines of therapy. VRd was the most cost-effective option in 95% of the bootstrap iterations at a willingness-to-pay threshold of $60K/QALY. Conclusion The 2019 decision to list VRd for newly diagnosed multiple myeloma has resulted in a somewhat cost-effective allocation of healthcare resources when judged against the traditional A$50K/QALY willingness-to-pay threshold. This analysis demonstrates how using individual-level modelling with registry data to perform economic evaluation can capture the interplay between patient characteristics, treatment decisions, and outcomes. Our findings provide nuanced insights into the real-world cost-effectiveness of VRd, highlighting how post-market evaluations can inform refinement of funding decisions for complex therapeutic interventions.

Keywords: Health Technology Assessment; Cost-Effectiveness Analysis; Discrete-Event Simulation; Multiple Myeloma; Real-World Evidence (search for similar items in EconPapers)
JEL-codes: C63 I11 I18 (search for similar items in EconPapers)
Date: 2025-11
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