• Bin Wu and Lizheng Shi.
• 1Medical Decision and Economic Group, Department of Pharmacy, Ren Ji Hospital, South Campus, School of Medicine, Shanghai Jiaotong University, Shanghai, China; and.
• J Natl Compr Canc Netw. 2020 Nov 1; 18 (11): 1528-1536.

BackgroundMaintenance therapy with the PARP inhibitor olaparib for metastatic pancreatic cancer (MPC) with a germline BRCA1 or BRCA2 mutation has been shown to be effective. We aimed to evaluate the cost-effectiveness of maintenance olaparib for MPC from the US payer perspective.Materials And MethodsA partitioned survival model was adopted to project the disease course of MPC. Efficacy and toxicity data were gathered from the Pancreas Cancer Olaparib Ongoing (POLO) trial. Transition probabilities were estimated from the reported survival probabilities in each POLO group. Cost and health preference data were derived from the literature. The incremental cost-utility ratio, incremental net-health benefit, and incremental monetary benefit were measured. Subgroup analysis, one-way analysis, and probabilistic sensitivity analysis were performed to explore the model uncertainties.ResultsMaintenance olaparib had an incremental cost-utility ratio of $191,596 per additional progression-free survival (PFS) quality-adjusted life-year (QALY) gained, with a high cost of $132,287 and 0.691 PFS QALY gained, compared with results for a placebo. Subgroup analysis indicated that maintenance olaparib achieved at least a 16.8% probability of cost-effectiveness at the threshold of $200,000/QALY. One-way sensitivity analyses revealed that the results were sensitive to the hazard ratio of PFS and the cost of olaparib. When overall survival was considered, maintenance olaparib had an incremental cost-utility ratio of $265,290 per additional QALY gained, with a high cost of $128,266 and 0.483 QALY gained, compared with results for a placebo.ConclusionsMaintenance olaparib is potentially cost-effective compared with placebo for patients with a germline BRCA mutation and MPC. Economic outcomes could be improved by tailoring treatment based on individual patient factors.

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