Cost-effectiveness analysis of gene expression profiling for breast cancer treatment decisions in India
DOI:
https://doi.org/10.18203/2394-6040.ijcmph20251019Keywords:
Breast cancer, Cost effective analysis, Genetics screeningAbstract
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.
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References
OncoStem Diagnostics. CanAssist Breast Pricing Information. 2023.
Ambavane A. Economic evaluation of gene expression profiling in breast cancer management in developing countries. JCO Glob Oncol. 2020;6:451-9.
Mathur P. Cancer statistics, 2020: report from National Cancer Registry Programme, India. JCO Glob Oncol. 2020;6:1063-75. DOI: https://doi.org/10.1200/GO.20.00122
Kalinsky K. 21-gene assay to inform chemotherapy benefit in node-positive breast cancer. N Engl J Med. 2021;385(25):2336-47. DOI: https://doi.org/10.1056/NEJMoa2108873
Pramesh CS. Cancer Management in India during Covid-19. N Engl J Med. 2020;382(20):61. DOI: https://doi.org/10.1056/NEJMc2011595
Bartlett JMS. Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Accurate Than Another. J Natl Cancer Inst. 2023;115(1):19-31.
Wang SY. Prognostic effect of multigene assays in early-stage estrogen receptor-positive breast cancer: a network meta-analysis. NPJ Breast Cancer. 2022;8(1):103.
Chhatwal J. Cost-effectiveness of adjuvant chemotherapy for early breast cancer in elderly women. Value Health. 2023;26(3):823-32.
Goyal H. Cost of care for breast cancer in India: a cross-sectional study. Indian J Surg Oncol. 2020;11(2):197-204.
Woodward RM. Novel pricing strategies to support universal access to cancer drugs. Lancet Oncol. 2021;22(1):17-23.
Ghosh S, Nambiar D. Leveraging the Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY) platform for cancer care in India. Lancet Oncol. 2021;22(8):323-9.
Sestak I. Risk stratification with genomic signatures in patients with early breast cancer: 10-year analysis. J Clin Oncol. 2022;40(16):1816-24.
Sullivan R. Cancer care in India: challenges and future considerations. Lancet Oncol. 2022;23(4):143-53.
Wu J. Implementation and impact of molecular testing on treatment decisions in a developing country: a real-world study. JCO Glob Oncol. 2020;6:277-86.
Lester SC. Clinical applications of breast cancer risk assessment guidelines in resource-limited environments. Lancet Oncol. 2021;22(8):332-42.
Lee A. How should we evaluate new diagnostic tests for breast cancer recurrence risk? J Natl Cancer Inst. 2021;113(4):1-8.
Barrios CH. Patterns of care of cancer patients in Latin America and the Caribbean: ongoing progress in the fight against cancer. Lancet Oncol. 2022;23(8):370-92.
Gyawali B. Cancer drugs in low-income and middle-income countries: recommendations for action. Lancet Oncol. 2022;23(5):563-66.