Appendix D
Warfarin Topic Brief

David L. Veenstra, Pharm.D., Ph.D.

University of Washington

CLINICAL SCENARIO

Warfarin is a commonly used anticoagulant that is prescribed for the prevention of thromboembolic events in patients with such indications as atrial fibrillation, previous thromboembolism, and artificial heart valves. Warfarin has a narrow therapeutic index: Too high a dose can lead to major bleeding and too low a dose does not protect from thromboembolic events. In addition, there is high variability in response to the drug both between patients and for a single patient at different points in time. Warfarin therapy is thus carefully managed, with the International Normalized Ratio (INR) used to monitor anticoagulation response and monitoring and dose adjustment occurring every 2–6 weeks. The use of genomic information may improve the ability to predict an optimal initial dose, thus improving therapeutic response during warfarin initiation, when the risk of over-anticoagulation and major bleeding events is highest.

PUBLIC HEALTH IMPORTANCE

Warfarin-related bleeding is one of the most common causes of serious adverse drug events leading to hospitalization.

Test Purpose

Predictive: drug treatment response and safety.



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Appendix D Warfarin Topic Brief David L. Veenstra, Pharm.D., Ph.D. university of Washington CLINICAL SCENARIO Warfarin is a commonly used anticoagulant that is prescribed for the prevention of thromboembolic events in patients with such indications as atrial fibrillation, previous thromboembolism, and artificial heart valves. Warfarin has a narrow therapeutic index: Too high a dose can lead to major bleeding and too low a dose does not protect from thromboembolic events. In addition, there is high variability in response to the drug both between patients and for a single patient at different points in time. Warfarin ther- apy is thus carefully managed, with the International Normalized Ratio (INR) used to monitor anticoagulation response and monitoring and dose adjustment occurring every 2–6 weeks. The use of genomic information may improve the ability to predict an optimal initial dose, thus improving therapeutic response during warfarin initiation, when the risk of over- anticoagulation and major bleeding events is highest. PUBLIC HEALTH IMPORTANCE Warfarin-related bleeding is one of the most common causes of serious adverse drug events leading to hospitalization. Test Purpose Predictive: drug treatment response and safety. 

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 ThE VALuE Of GENETIC AND GENOMIC TEChNOLOGIES Systematic Evidence Reviews An evidence-based review conducted in 2006 by the American Col- lege of Medical Genetics (Flockhart et al., 2008) found that CYPC and VKORC testing to guide warfarin dosing had analytic and clinical validity. However, the review found that “no study has yet shown this intervention to be effective in reducing the incidence of high INR values, the time to stable INR, or the occurrence of serious bleeding events.” A recent system- atic review by Kangelaris and colleagues also reported a lack of evidence of benefit (Kangelaris et al., 2009). Regulatory Guidance On January 22, 2010, the FDA modified the drug label for warfarin to include dose ranges based on pharmacogenomic information. This was an update to the 2007 label change that had added information about the association between CYPC and VKORC variants and warfarin responsiveness. Both label changes inform the prescriber about the associa- tion between genotype and warfarin dosing requirements, but they do not require pharmacogenetic testing. Guidelines by Professional Groups The 2008 American College of Chest Physicians anticoagulation man- agement guidelines state, “[W]e suggest against pharmacogenetic-based dosing until randomized data indicate that it is beneficial (Grade 2C)” (Ansell et al., 2008). Recommendations by Payers CMS recently issued a coverage decision for warfarin pharmacoge- nomic testing that specifies testing will be reimbursed only for patients initiating warfarin who are enrolled in a randomized controlled trial that measures major bleeding and thromboembolic events. EVIDENCE OVERVIEW Analytic Validity Testing for the two to three informative CYPC SNPs and the single informative VKORC SNP is straightforward.

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 APPENDIX D Clinical Validity Together, the CYPC and VKORC variants account for approxi- mately 30 percent of the variance in warfarin dose requirement, while clinical and demographic factors account for approximately 20 percent of the variability (Limdi and Veenstra, 2008). A warfarin dose prediction algorithm was recently developed by the International Warfarin Pharmaco- genetics Consortium (IWPC) using data from 5,700 patients from 9 coun- tries (Klein et al., 2009). Dose prediction that included pharmacogenetic information improved the ability to accurately predict those patients who required ≤ 3 mg/day (54.3 percent versus 33.4 percent) and those who required ≥ 7 mg/day (26.4 percent versus 9.1 percent) compared to using clinical and demographic information only. The risk of major hemorrhage in patients with a variant of CYPC is approximately double that in CYPC wild-type patients (Higashi et al., 2002; Limdi et al., 2008). In contrast, VKORC appears to confer a higher risk of over-anticoagulation (INR > 4) (Meckley et al., 2008; Schwarz et al., 2008) during the first few days of therapy, but not a bleeding risk (Limdi et al., 2008). Clinical utility The impact of genotype-guided dosing on clinical outcomes has been compared with standard care in two small randomized controlled trials, but the results were not definitive. Caraco et al. reported a shorter time to first therapeutic INR and first stable INR among patients receiving CYPC (only) genotype-guided therapy (Caraco et al., 2008). A more recent, higher-quality study by Anderson et al. in 200 patients found no difference in the percentage of INRs within therapeutic range (Anderson et al., 2007), although the effect of genotyping may have been mitigated because 80 percent of the subjects were inpatients and closely monitored. An NIH-funded randomized controlled trial—the Clarification of Optimal Anticoagulation Through Genetics (COAG) trial—has recently been initi- ated to study this issue further (Clinicaltrials.gov, 2008). The trial will enroll approximately 1,200 patients, measure the percentage of time in therapeutic range over the first month as the primary outcome, and com- pare clinical versus clinical plus genomic algorithms for dose initiation. The trial is scheduled for completion in the fall of 2011. Cost Effectiveness An early (non-peer reviewed) cost-effectiveness analysis suggested that warfarin pharmacogenomic testing, if implemented throughout the

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0 ThE VALuE Of GENETIC AND GENOMIC TEChNOLOGIES United States, could save $1 billion annually (McWilliam et al., 2006). However, the assumptions in this study have been criticized (Hughes and Pirmohamed, 2007; Veenstra, 2007). Several more recent studies have come to the conclusion that warfarin pharmacogenomic testing is unlikely to be cost effective unless testing costs drop significantly and the uncertainty around effectiveness is reduced (Eckman et al., 2009; Meckley et al., 2010; Patrick et al., 2009). Summary Variation in the CYPC and VKORC genes clearly affects warfarin dosing requirements, but given that anticoagulation status is (or should be) already closely monitored and individualized in warfarin patients, the incremental benefits of pharmacogenomic testing are less clear (Eckman et al., 2009; Schwarz et al., 2008). The convincing evidence of clinical valid- ity, the unclear evidence of clinical utility, and the contrasting perspectives of stakeholders on the value of warfarin pharmacogenomic testing make it an interesting case study. REFERENCES Anderson, J. L., B. D. Horne, S. M. Stevens, A. S. Grov, S. Barton, Z. P. Nicholas, S. F. Kahn, H. T. May, K. M. Samuelson, J. B. Muhlestein, and J. F. Carlquist. 2007. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anti- coagulation. Circulation 116(22):2563–2570. Ansell J., J. Hirsh, E. Hylek, A. Jacobson, M. Crowther, and G. Palareti. 2008. Pharma- cology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). Chest 133(6 Suppl):160S–198S. Caraco, Y. S., S. Blotnic, and M. Muszkat. 2008. CYP2C9 genotype-guided warfarin pre- scribing enhances the efficacy and safety of anticoagulation: A prospective randomized controlled study. Clin Pharmacol Ther 83(3):460–470. Clinicaltrials.gov. 2008. Clarification of Optimal Anticoagulation Through Genetics (COAG), NCT00839657. Eckman, M. H., J. Rosand, S. M. Greenberg, and B. F. Gage. 2009. Cost-effectiveness of us- ing pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med 150(2):73–83. Flockhart, D. A., D. O’Kane, M. S. Williams, and M. S. Watson. 2008. Pharmacogenetic test- ing of CYP2C9 and VKORC1 alleles for warfarin. Genet Med 10(2):139–150. Higashi, M. K., D. L. Veenstra, L. M. Kondo, A. K. Wittkowsky, S. L. Srinouanprachanh, F. M. Farin, and A. E. Rettie. 2002. Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA 287(13):1690–1698. Hughes, D. A. and M. Pirmohamed. 2007. Warfarin pharmacogenetics: Economic consider- ations. Pharmacoeconomics 25(11):899–902. Kangelaris, K. N., S. Bent, R. L. Nussbaum, D. A. Garcia, and J. A. Tice. 2009. Genetic test- ing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin. J Gen Intern Med 24(5):656–664.

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 APPENDIX D Klein, T. E., R B. Altman, N. Eriksson, B. F. Gage, S. E. Kimmel, M. T. Lee, N. A. Limdi, et al. 2009. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med 360(8):753–764. Limdi, N. A., and D. L. Veenstra. 2008. Warfarin pharmacogenetics. Pharmacotherapy 28(9): 1084–1097. Limdi, N. A., G. McGwin, J. A. Goldstein, T. M. Beasley, D. K. Arnett, B. K. Adler, M. F. Baird, and R. T. Acton. 2008. Influence of CYP2C9 and VKORC1 1173C/T genotype on the risk of hemorrhagic complications in African-American and European-American patients on warfarin. Clin Pharmacol Ther 83(2):312–321. McWilliam, A., R. Lutter, and C. Nardinelli. 2006. Health care savings from personalizing medicine using genetic testing: The case of warfarin. Working Paper 06–23. AEI–Brook- ing Joint Center for Regulatory Studies. Meckley, L. M., A. K. Wittkowsky, M. J. Rieder, A. E. Rettie, D. L. Veenstra, et al. 2008. An analysis of the relative effects of VKORC1 and CYP2C9 variants on anticoagu- lation related outcomes in warfarin-treated patients. Thrombosis & haemostasis 100(2):229–239. Meckley, L. M., J. M. Gudgeon, J. L. Anderson, M. S. Williams, and D. L. Veenstra. 2010. A policy model to evaluate the benefits, risks, and costs of warfarin pharmacogenomic testing. Pharmacoeconomics 28(1):61–74. Patrick, A. R., J. Avorn, and N. K. Choudhry. 2009. Cost-effectiveness of genotype-guided warfarin dosing for patients with atrial fibrillation. Circ Cardiovasc Qual Outcomes 2(5):429–436. Schwarz, U. I., M. D. Ritchie, Y. Bradford, C. Li, S. M. Dudek, A. Frye-Anderson, R. B. Kim, et al. 2008. Genetic determinants of response to warfarin during initial anticoagulation. N Engl J Med 358(10):999–1008. Veenstra, D. L. 2007. The cost-effectiveness of warfarin pharmacogenomics. J Thromb hae- most 5(9):1974–1975.

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