IntroductionPrecision medicine (PM) involves gene testing to identify disease risk, enable early diagnosis or guide therapeutic choice, and targeted gene therapy. We aim to perform a systematic review and meta-analysis to quantify the cost-effectiveness profile of PM stratified by intervention type, identify sources of heterogeneity in the value-for-money of PM.Methods and analysisWe will perform a systematic search in Embase, MEDLINE, EconLit and CRD databases for studies published in English language or with translation in English between 1 January 2011 and 8 July 2021 on the topic of cost-effectiveness analysis of PM interventions. The focus will be on studies that reported health and economic outcomes. Study quality will be assessed using the Biases in Economic Studies checklist. The incremental net benefit of PM screening, diagnostic, treatment-targeting and therapeutic interventions over conventional strategies will be respectively pooled across studies using a random-effect model if heterogeneity is present, otherwise a fixed-effect model. Subgroup analyses will be performed based on disease area, WHO region and World Bank country-income level. Additionally, we will identify the potential sources of heterogeneity with random-effect meta-regressions. Finally, biases will be detected using jackknife sensitivity analysis, funnel plot assessment and Egger’s tests.Ethics and disseminationFor this type of study ethics approval or formal consent is not required. The results will be disseminated at various presentations and feedback sessions, in conference abstracts and manuscripts that will be submitted to peer-reviewed journals.PROSPERO registration numberCRD42021272956.

Background Breast cancer is the leading cause of cancer among women in India. Treatment with hormone therapy reduces recurrence. We undertook this cost-effectiveness study to ascertain the treatment option offering the best value for money. Methods The lifetime costs and health outcomes of using tamoxifen, AI and switch therapy were measured in a cohort of 50-year-old women with HR-positive early stage breast cancer. A Markov model of disease was developed using a societal perspective with a lifetime study horizon. Local, contralateral, and distant recurrence were modelled along with treatment related adverse effects. Primary data collected to obtain estimates of out-of-pocket expenditure (OOPE) and utility weights. Both health system cost and OOPE were included. The future costs and consequences were discounted at 3%. A probabilistic sensitivity analysis was used. Results The lifetime cost of hormone therapy with tamoxifen, AI and switch therapy was to be ₹1,472,037 (I$ 68,947), ₹1,306,794 (I$ 61,208) and ₹1,281,811 (I$ 60,038). The QALYs lived per patient receiving tamoxifen, AI and switch were 13.12, 13.42 and 13.32. tamoxifen was found to be more expensive and less effective. As compared to switch therapy, AI for five years incurred an incremental cost of ₹259,792 (I$12,168) per QALY gained. At the willingness to pay equals to per capita GDP of India, there is 55% probability of AI therapy to be cost-effective compared to switch therapy. Conclusion In postmenopausal women with HR-positive early-stage breast cancer, switch therapy is recommended for use on the basis of cost-effectiveness.

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