Economic Impact of Gene Expression Profiling in Patients with Early-Stage Breast Cancer in France

BACKGROUND AND AIMS The heterogeneous nature of breast cancer can make decisions on adjuvant chemotherapy following surgical resection challenging. Oncotype DX is a validated gene expression profiling test that predicts the likelihood of adjuvant chemotherapy benefit in early-stage breast cancer. The aim of this study is to determine the costs of chemotherapy in private hospitals in France, and evaluate the cost-effectiveness of Oncotype DX from national insurance and societal perspectives. METHODS A multicenter study was conducted in seven French private hospitals, capturing retrospective data from 106 patient files. Cost estimates were used in conjunction with a published Markov model to assess the cost-effectiveness of using Oncotype DX to inform chemotherapy decision making versus standard care. Sensitivity analyses were performed. RESULTS The cost of adjuvant chemotherapy in private hospitals was estimated at EUR 8,218 per patient from a national insurance perspective and EUR 10,305 from a societal perspective. Cost-effectiveness analysis indicated that introducing Oncotype DX improved life expectancy (+0.18 years) and quality-adjusted life expectancy (+0.17 QALYs) versus standard care. Oncotype DX was found cost-effective from a national insurance perspective (EUR 2,134 per QALY gained) and cost saving from a societal perspective versus standard care. Inclusion of lost productivity costs in the modeling analysis meant that costs for eligible patients undergoing Oncotype DX testing were on average EUR 602 lower than costs for those receiving standard care. CONCLUSIONS As Oncotype DX was found both cost and life-saving from a societal perspective, the test was considered to be dominant to standard care. However, the delay in coverage has the potential to erode the quality of the French healthcare system, thus depriving patients of technologies that could improve clinical outcomes and allow healthcare professionals to better allocate hospital resources to improve the standard of care for all patients.