Genetic testing versus clinical screening for relatives of patients with hypertrophic cardiomyopathy in the Brazilian public health system: a cost-utility analysis.

Abstract

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant myocardial disorder affecting 0·2% of the global population and a leading cause of sudden cardiac death in young individuals and athletes. Current guidelines recommend periodic clinical screening of first-degree relatives for early diagnosis and risk stratification. Genetic testing identifies at-risk individuals while exempting genotype-negative relatives from lifelong surveillance. However, it remains unavailable in Brazil's public health system (Sistema Único de Saúde, SUS). This study aimed to evaluate the cost-utility of genetic testing for HCM cascade screening in Brazil. A cost-utility analysis was conducted from the SUS perspective, using a hybrid decision tree and Markov model to project lifetime costs and health outcomes. Inputs were derived from literature and validated by a multidisciplinary expert panel. Genetic testing costs were micro-costed; other costs were obtained from Brazil's national reimbursement database (SIGTAP). Effectiveness was measured in quality-adjusted life-years (QALYs). Deterministic and probabilistic analyses assessed model robustness. Genetic testing was cost-effective (incremental cost-effectiveness ratio: US$1411 per QALY), yielding an incremental gain of 0·06 QALYs per relative at an additional cost of $87 per relative. Utility values had the greatest influence on cost-utility outcomes. In probabilistic analysis, genetic testing was cost-effective in 99·4% of simulations at the Brazilian willingness-to-pay threshold of $7421 per QALY. In the base-case hypothetical cohort of 1000 relatives (250 probands with four first-degree relatives each), 205 (20·5%) of 1000 relatives were exempted from lifelong surveillance, reducing screening visits by 18·6% per tested individual. Genetic testing is a cost-effective strategy for HCM cascade screening in Brazil's public health system. By exempting genotype-negative relatives from lifelong surveillance, it optimises resource allocation, reduces unnecessary follow-ups and psychological burden, and supports informed family planning. These findings provide an economic evidence base for integrating genetic testing into SUS clinical practice guidelines. Programa Nacional de Genômica e Saúde de Precisão (Genomas Brasil) of the Brazilian Ministry of Health and Conselho Nacional de Desenvolvimento Científico e Tecnológico.