Value of information analysis of multiparameter tests for chemotherapy in early breast cancer : the OPTIMA prelim trial

Background Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy. Objectives To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators. Methods Women with surgically treated breast cancer (estrogen receptor–positive and lymph node–positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom. Results There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range −£1892 to £195) and quality-adjusted life-year gains (range 0.17–0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research. Conclusions Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency