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Cost-Effectiveness of Multigene Pharmacogenetic Testing in Patients With Acute Coronary Syndrome After Percutaneous Coronary Intervention

Overview
Journal Value Health
Publisher Elsevier
Date 2020 Jan 19
PMID 31952675
Citations 19
Authors
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Abstract

Objective: To evaluate the cost-effectiveness of multigene testing (CYP2C19, SLCO1B1, CYP2C9, VKORC1) compared with single-gene testing (CYP2C19) and standard of care (no genotyping) in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) from Medicare's perspective.

Methods: A hybrid decision tree/Markov model was developed to simulate patients post-PCI for ACS requiring antiplatelet therapy (CYP2C19 to guide antiplatelet selection), statin therapy (SLCO1B1 to guide statin selection), and anticoagulant therapy in those that develop atrial fibrillation (CYP2C9/VKORC1 to guide warfarin dose) over 12 months, 24 months, and lifetime. The primary outcome was cost (2016 US dollar) per quality-adjusted life years (QALYs) gained. Costs and QALYs were discounted at 3% per year. Probabilistic sensitivity analysis (PSA) varied input parameters (event probabilities, prescription costs, event costs, health-state utilities) to estimate changes in the cost per QALY gained.

Results: Base-case-discounted results indicated that the cost per QALY gained was $59 876, $33 512, and $3780 at 12 months, 24 months, and lifetime, respectively, for multigene testing compared with standard of care. Single-gene testing was dominated by multigene testing at all time horizons. PSA-discounted results indicated that, at the $50 000/QALY gained willingness-to-pay threshold, multigene testing had the highest probability of cost-effectiveness in the majority of simulations at 24 months (61%) and over the lifetime (81%).

Conclusions: On the basis of projected simulations, multigene testing for Medicare patients post-PCI for ACS has a higher probability of being cost-effective over 24 months and the lifetime compared with single-gene testing and standard of care and could help optimize medication prescribing to improve patient outcomes.

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