PERSONALIZED DIAGNOSTIC ALGORITHM INCORPORATING MOLECULAR GENETIC TESTING FOR CYTOMEGALOVIRUS INFECTION, CLINICAL IMPLEMENTATION AND COST-EFFECTIVENESS ANALYSIS
DOI:
https://doi.org/10.17605/Keywords:
Cytomegalovirus infection, personalized medicine, diagnostic algorithm, molecular genetic testing, cost-effectiveness, risk stratification.Abstract
Objective: to develop, implement, and evaluate the clinical and economic effectiveness of a personalized three-stage diagnostic algorithm incorporating molecular genetic testing for five polymorphisms in the management of cytomegalovirus infection (CMVI).
Materials and methods. The algorithm was developed based on genotyping data from 100 CMVI patients and 80 controls from the Fergana Valley (2019–2025). The three-stage approach integrates standard clinical-laboratory assessment, genotyping for TNF-α, IL-10, TLR4, eNOS, and SOD2 polymorphisms with calculation of a cumulative genetic risk score (0–10 points), and risk-stratified management protocols. The algorithm was implemented at two clinical sites from 2024, with 68 patients genotyped during the pilot phase. Cost-effectiveness was modeled over a 3–5 year horizon for a cohort of 100 patients.
Results. Among 68 genotyped patients, 24 (35.3%) were classified as high genetic risk (≥6 points). Intensified monitoring in this subgroup enabled timely detection of rising viral loads and early antiviral therapy before the onset of severe complications. No patient in the high-risk group managed according to the algorithm developed generalized CMVI during the observation period. The projected economic benefit over 3–5 years for 100 patients was 192 million UZS, comprising savings from complication reduction (18 million), disability days prevention (54 million), and reduced childhood disability (150 million), minus genotyping costs (30 million).
Conclusion. The three-stage personalized algorithm integrating molecular genetic testing provides a practical, cost-effective framework for risk-stratified management of CMVI. The one-time genotyping investment yields lifelong prognostic information at a cost comparable to a single biochemical analysis, while delivering substantial clinical and economic benefits.
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