Cost-Effectiveness Analysis for Therapy Sequence in Advanced Cancer: A Microsimulation Approach with Application to Metastatic Prostate Cancer

Elizabeth A. Handorf, J. Robert Beck, Andres Correa, Chethan Ramamurthy and Daniel M. Geynisman
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Elizabeth A. Handorf: Rutgers University School of Public Health, Cancer Institute of New Jersey, USA
J. Robert Beck: Fox Chase Cancer Center, Cancer Prevention and Control Program, Philadelphia, PA, USA
Andres Correa: Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA
Chethan Ramamurthy: Division Hematology/Oncology, Mays Cancer Center UT Health San Antonio, San Antonio, TX, USA
Daniel M. Geynisman: Department of Hematology/Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA

Medical Decision Making, 2023, vol. 43, issue 7-8, 949-960

Abstract: Purpose Patients with advanced cancer may undergo multiple lines of treatment, switching therapies as their disease progresses. We developed a general microsimulation framework to study therapy sequence and applied it to metastatic prostate cancer. Methods We constructed a discrete-time state transition model to study 2 lines of therapy. Using digitized published survival curves (progression-free survival, time to progression, and overall survival [OS]), we inferred event types (progression or death) and estimated transition probabilities using cumulative incidence functions with competing risks. We incorporated within-patient dependence over time; first-line therapy response informed subsequent event probabilities. Parameters governing within-patient dependence calibrated the model-based results to a target clinical trial. We applied these methods to 2 therapy sequences for metastatic prostate cancer, wherein both docetaxel (DCT) and abiraterone acetate (AA) are appropriate for either first- or second-line treatment. We assessed costs and quality-adjusted life-years (5-y QALYs) for 2 treatment strategies: DCT → AA versus AA → DCT. Results Models assuming within-patient independence overestimated OS time, which corrected with the calibration approach. With generic pricing, AA → DCT dominated DCT → AA, (higher 5-y QALYs and lower costs), consistent for all values of calibration parameters (including no correction). Model calibration increased the difference in 5-y QALYs between treatment strategies (0.07 uncorrected v. 0.15 with base-case correction). Applying the correction decreased the estimated difference in cost (−$5,360 uncorrected v. −$3,066 corrected). Results were strongly affected by the cost of AA. Under a lifetime horizon, AA → DCT was no longer dominant but still cost-effective (incremental cost-effectiveness ratio: $19,463). Conclusions We demonstrate a microsimulation approach to study the cost-effectiveness of therapy sequences for advanced prostate cancer, taking care to account for within-patient dependence. Highlights We developed a discrete-time state transition model for studying therapy sequence in advanced cancers. Results are sensitive to dependence within patients. A calibration approach can introduce dependence across lines of therapy and closely match simulation outcomes to target trial outcomes.

Keywords: microsimulation model; calibration; therapy sequence (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:43:y:2023:i:7-8:p:949-960

DOI: 10.1177/0272989X231201621

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