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Оценка клинико-экономической эффективности раннего выявления злокачественных новообразований с помощью наблюдения здоровых носителей высокоонкогенных герминальных мутаций
Introduction. The increasing incidence and mortality of cancer, along with the growing contribution of hereditary malignancies, necessitate the implementation of personalized prevention models based on molecular genetic risk stratification and early cancer detection among asymptomatic carriers of highly penetrant germline mutations. Aim. The aim of this study was to evaluate the clinical and economic effectiveness of early cancer detection programs based on molecular genetic testing and structured surveillance of high-risk populations. Methodology. The economic evaluation was conducted using cost-benefit analysis (CBA) from a societal perspective and included direct medical and non-medical costs as well as indirect losses associated with productivity loss and premature mortality. Two scenarios were modeled: molecular genetic testing at program entry followed by structured surveillance with predominantly early-stage cancer detection, and the absence of genetic testing and systematic surveillance resulting in a higher proportion of late-stage diagnoses. The analysis was based on registry data from 554 carriers of germline mutations enrolled between 2018 and June 2024; during the observation period, 56 cases of breast cancer were identified, predominantly at stages I – II. Modeling was performed over a five-year time horizon with adjustment for projected inflation and discounting of societal costs. Results. The total societal cost per patient under the early detection scenario amounted to RUB 1.736.702, compared with RUB 2.980.342 in the absence of genetic testing and surveillance, resulting in cost savings of RUB 1.243.640 per patient and approximately RUB 70 million for the entire cohort of detected cases. Practical significance. The findings demonstrate the high economic efficiency of genetic testing and surveillance programs for high-risk populations and support their implementation as an effective tool for optimizing cancer care and reducing overall societal costs.