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.
- Journal Article
- breast cancer
- efficient research design
- personalized medicine
- value of information analysis