Cost-effectiveness analysis of gene expression profiling for breast cancer treatment decisions in India

Background: Breast cancer is the most common cancer among Indian women, with over 200,000 new cases annually. Gene expression profiling can help identify patients who can safely avoid chemotherapy, reducing unnecessary treatment and complications. Methods: A decision-analytic model was developed using TreeAge Pro to assess the cost-effectiveness of gene expression profiling versus standard care for ER-positive, node-negative/low-node breast cancer patients in India. A hypothetical cohort of 300,000 patients was analyzed, focusing on cases spared from chemotherapy, relapse rates and costs. Results: A test with 92% sensitivity and 96% specificity (test 1) could spare 40,000 patients from chemotherapy annually. A tiered pricing model (₹15,000–₹50,000) showed favorable cost-effectiveness over existing tests (Oncotype DX: ₹190,000, CanAssist: ₹65,000). The lowest-cost test (₹15,000) had an ICER of -₹190,200 per case spared, making it a dominant strategy. False negatives resulted in a ₹61 crore annual burden, while false positives added ₹36 crores in unnecessary chemotherapy costs. Conclusions: Gene expression profiling is cost-effective in India, reducing healthcare costs and improving patient quality of life. Optimizing sensitivity and specificity is essential for maximizing clinical and economic benefits.