Sunday, October 23, 2011
Grand Ballroom AB (Hyatt Regency Chicago)
Poster Board # 17
(ESP) Applied Health Economics, Services, and Policy Research

Sandjar Djalalov, PhD, St. Michael's Hospital, Toronto, ON, Canada, Jaclyn Beca, St. Michael's, Toronto, ON, Canada and Jeffrey Hoch, PhD, Cancer Care Ontario, Toronto, ON, Canada

Purpose: Personalized medicine is becoming very popular way to identify patients and groups who are most likely to benefit from new treatments. When the evidence is uncertain about a new genetic test, cost –effectiveness analysis can be used to pinpoint the key issues requiring additional attention. As an example we explore the cost-effectiveness of the test for CYP2D6. The scientific literature expresses different opinions about the benefit of the test, and the cost of subsequent treatment can be large. Approximately 60% of breast cancer cases are a type sensitive to hormones. Tamoxifen is the most widely used treatment of hormone-dependent breast cancer. Patients with reduced CYP2D6 activity may derive inferior therapeutic benefit from tamoxifen, and may alternatively be treated with newer aromatase inhibitors (AIs), but this is still controversial. The alternative, AI has higher cost, which provides incentive for identifying patients who will benefit from tamoxifen prior to treatment. We estimated the cost-effectiveness of genetic testing in combination with hormone therapy for early breast cancer in Canada.

Method: We performed a cost-effectiveness analysis using a Markov model from a societal perspective and a lifetime horizon. The base case assumed 65-year-old ER+ hormone sensitive women with early breast cancer. We evaluated: genetic testing with subsequent treatment based on genetic status (tamoxifen for CYP2D6 extensive metabolizers and AIs for decreased metabolizers) vs. four treatment strategies currently investigated in the clinical trials without genetic testing. Those strategies includes: tamoxifen and AI monotherapies and tamoxifen/letrozole sequential therapies.  Probabilistic sensitivity analysis was used to incorporate parameter uncertainties. Expected value of perfect information was performed to identify future research directions. Outcomes were quality-adjusted life years (QALYs) and costs.

Result: Our preliminary results shows that genetic testing and treatment combination strategy gained a 0.19 QALY when compared to no testing (tamoxifen monotherapy). The incremental cost was CAD $792 compared to standard care, and the incremental cost-effectiveness ratio (ICER) for the base case was $4,253 per QALY.

Conclusion: CYP2D6 Genetic testing in combination with hormone treatment for early breast cancer patients may be economically attractive in the current setting. Future research is required to determine efficacy of extended tamoxifen (more than 5 years) treatment, the rate of progression to a more advanced cancer health state and adverse events by CYP2D6 polymorphism.