Population genomic screening of young adults for familial hypercholesterolaemia: a cost-effectiveness analysis - Marquina, Clara; Lacaze, Paul; Tiller, Jane; Riaz, Moeen; Sturm, Amy C; Nelson, Mark R; Ference, Brian A; Pang, Jing; Watts, Gerald F; Nicholls, Stephen J; Zoungas, Sophia; Liew, Danny; et al. (European heart journal, 2022)
The aim of this study was to assess the impact and cost-effectiveness of offering population genomic screening to all young adults in Australia to detect heterozygous familial hypercholesterolaemia (FH). We designed a decision analytic Markov model to compare the current standard of care for heterozygous FH diagnosis in Australia (opportunistic cholesterol screening and genetic cascade testing) with the alternate strategy of population genomic screening of adults aged 18-40 years to detect pathogenic variants in the LDLR/APOB/PCSK9 genes. We used a validated cost-adaptation method to adapt findings to eight high-income countries. The model captured coronary heart disease (CHD) morbidity/mortality over a lifetime horizon, from healthcare and societal perspectives. Risk of CHD, treatment effects, prevalence, and healthcare costs were estimated from published studies. Outcomes included quality-adjusted life years (QALYs), costs and incremental cost-effectiveness ratio (ICER), discounted 5% annually. Sensitivity analyses were undertaken to explore the impact of key input parameters on the robustness of the model. Over the lifetime of the population (4 167 768 men; 4 129 961 women), the model estimated a gain of 33 488years of life lived and 51 790 QALYs due to CHD prevention. Population genomic screening for FH would be cost-effective from a healthcare perspective if the per-test cost was ≤AU$250, yielding an ICER of <AU$28 000 per QALY gained. From a societal perspective, population genomic screening would be cost-saving. ICERs from societal perspective remained cost-saving after adaptation to other countries. Based on our model, offering population genomic screening to all young adults for FH could be cost-effective, at testing costs that are feasible.