The cost impact of unselective vs selective MammaPrint testing in early-stage breast cancer in Southern Africa

Abstract

Background: MammaPrint (MP) has been applied in South Africa (SA) for decision-making in early-stage hormone receptor-positive breast cancer since 2006. The cost-impact of MP in SA has not been assessed. Aim: To assess different MP testing strategies for cost-minimization in early-stage breast carcinoma using a funder perspective. Methods: Clinico-pathologic information was extracted from a prospectively collected database. Clinical risk stratification was done using Adjuvant Online! (AOL) and the Predict V2.1 algorithm (www.predict.nhs.uk). An unselected MP testing strategy was compared to a selective strategy, testing only clinically high risk (cHigh) patients. Excluding human epidermal growth factor receptor-2 positive tumours, the costs for chemotherapy treatment and MP using funding data were used to evaluate the financial impact of these strategies. Results: In 583 patients with 601 tumours, 52% were clinically low risk (cLow) (AOL) while the average Predict 10-year survival with chemotherapy was 2.9%. MP correlated strongly with Predict and 318 (60%) patients were MP low risk. Unselective testing allowed omission of chemotherapy in 44 (8.4%) patients but escalated cost by 57.7%. Using a selective testing strategy, only 251 would be tested, de-escalating treatment in 138 (55%) and reducing cost by 19.5%. Considering a Predict value up to 3.2% as cHigh, cost would be up to 7.3% (p = 0.0467) lower with a selective testing strategy. Conclusion: MP allowed reduction in the use of adjuvant chemotherapy. Unselective use of MP increases overall costs. A selective testing strategy through clinical risk stratification using AOL/Predict results in substantial cost saving.

Keywords

• Breast
• Cancer
• Chemotherapy
• Predict
• MammaPrint
• Microarray