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

<div><p>Background and Aims</p><p>The heterogeneous nature of breast cancer can make decisions on adjuvant chemotherapy following surgical resection challenging. Onco<i>type</i> 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 Onco<i>type</i> DX from national insurance and societal perspectives.</p><p>Methods</p><p>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 Onco<i>type</i> DX to inform chemotherapy decision making versus standard care. Sensitivity analyses were performed.</p><p>Results</p><p>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 Onco<i>type</i> DX improved life expectancy (+0.18 years) and quality-adjusted life expectancy (+0.17 QALYs) versus standard care. Onco<i>type</i> 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 Onco<i>type</i> DX testing were on average EUR 602 lower than costs for those receiving standard care.</p><p>Conclusions</p><p>As Onco<i>type</i> 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.</p></div

Summary of one-way sensitivity analysis outcomes for Onco<i>type</i> DX testing versus standard care.

<p>QALY, quality-adjusted life year; EUR, 2013 Euros; ICER, incremental cost-effectiveness ratio</p><p>* ICERs are presented in EUR per QALY gained; RS, Recurrence Score.</p><p>Summary of one-way sensitivity analysis outcomes for Onco<i>type</i> DX testing versus standard care.</p

Summary cost-effectiveness results for Onco<i>type</i> DX versus standard care to inform adjuvant chemotherapy decision making in French private hospitals.

<p>All costs are expressed in 2013 Euros (EUR). QALY, quality-adjusted life year; ICER, incremental cost-effectiveness ratio.</p><p>Summary cost-effectiveness results for Onco<i>type</i> DX versus standard care to inform adjuvant chemotherapy decision making in French private hospitals.</p

Cost-effectiveness scatterplot of the probabilistic sensitivity analysis.

<p>The cost-effectiveness scatterplot shows incremental costs (€) versus incremental effectiveness expressed in quality-adjusted life years (QALYs) for the comparison of Oncotype DX with standard care. Each blue point represents one iteration of the probabilistic sensitivity analysis (with data based on sampling from distributions around clinical and cost parameters). The red point indicates the mean (of 1,000 iterations).</p

Summary of patient characteristics in the chemotherapy costing analysis.

<p>C, cyclophosphamide; E, epirubicin; 5FU, fluorouracil; HER, human epidermal growth factor receptor; ER, estrogen receptor; PR, progesterone receptor.</p><p>Summary of patient characteristics in the chemotherapy costing analysis.</p

Cost of adjuvant chemotherapy by components for societal and payer perspective.

<p>All costs are expressed in 2013 Euros (EUR).</p><p>Cost of adjuvant chemotherapy by components for societal and payer perspective.</p

Biological differences between the “Caucasian” and “Non-Caucasian” groups.

<p>Biological differences between the “Caucasian” and “Non-Caucasian” groups.</p

CBU inclusion criteria.

<p>CBU inclusion criteria.</p

Banking strategies according to utilization rate and utilization score (US).

<p>Banking strategies according to utilization rate and utilization score (US).</p

Therapeutic and economic value based on banking strategies.

<p>Four recruitment strategies were considered: (A) Banks implement an average selectivity rate of 33%, which reflects the percentage of banked units vs. collected units. The level is increased by applying the Utilization Score up to a total selectivity of 20% (B), then 6% (C) and 2% (D). For each scenario, therapeutic value (left scale) is indicated by the number of transplanted CBUs and confronted to the economic value in USD (right scale). The table presents the operating results for each scenario.</p