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Pharmacoeconomics. 2010;28(1):61-74. doi: 10.2165/11318240-000000000-00000.

A policy model to evaluate the benefits, risks and costs of warfarin pharmacogenomic testing.

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  • 1Department of Pharmacy, University of Washington, Seattle, Washington 98195, USA.



In 2007, the US FDA added information about pharmacogenomics to the warfarin label based on the influence of the CYP2C9 and VKORC1 genes on anticoagulation-related outcomes. Payers will be facing increasing demand for coverage decisions regarding this technology, but the potential clinical and economic impacts of testing are not clear.


To develop a policy model to evaluate the potential outcomes of warfarin pharmacogenomic testing based on the most recently available data.


A decision-analytic Markov model was developed to assess the addition of genetic testing to anticoagulation clinic standard care for a hypothetical cohort of warfarin patients. The model was based on anticoagulation status (international normalized ratio), a common outcome measure in clinical trials that captures both the benefits and risks of warfarin therapy. Initial estimates of testing effects were derived from a recently completed randomized controlled trial (n = 200). Healthcare cost ($US, year 2007 values) and health-state utility data were obtained from the literature. The perspective was that of a US third-party payer. Probabilistic and one-way sensitivity analyses were performed to explore the range of plausible results.


The policy model included thromboembolic events (TEs) and bleeding events and was populated by data from the COUMAGEN trial. The rate of bleeding calculated for standard care approximated bleeding rates found in an independent cohort of warfarin patients. According to our model, pharmacogenomic testing provided an absolute reduction in the incidence of bleeds of 0.17%, but an absolute increase in the incidence of TEs of 0.03%. The improvement in QALYs was small, 0.003, with an increase in total cost of $US162 (year 2007 values). The incremental cost-effectiveness ratio (ICER) ranged from testing dominating to standard care dominating, and the ICER was <$US50,000 per QALY in 46% of simulations. Results were most sensitive to the cost of genotyping and the effect of genotyping.


Our model, based on initial clinical studies to date, suggests that warfarin pharmacogenomic testing may provide a small clinical benefit with significant uncertainty in economic value. Given the uncertainty in the analysis, further updates will be important as additional clinical data become available.

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