Cost-effectiveness of a population genomic screening strategy for FH

A cost-effectiveness study suggests that population genomic screening for FH in young adults could be cost-effective from a healthcare perspective and cost-saving from a societal perspective at testing costs that are feasible.

Introduction and methods

Background

The prevalence of familial hypercholesterolemia (FH) is estimated to be 1:250 in the general population [1]. Early detection of FH is of utmost importance to provide appropriate preventive care as the process of atherosclerosis starts at birth. However, FH remains largely undiagnosed leading to a high burden of premature CVD morbidity and mortality [2,3]. An approach of opportunistic cholesterol screening and cascade testing, which is currently applied in most developed countries, is estimated to miss >90% of individuals with FH [4-7].

Aim of the study

This study investigated the cost-effectiveness of population genomic screening for FH in adults aged 18–40 years in Australia, in comparison with the current Australian standard-of-care for FH.

Model structure and population

Health and economic outcomes of the two different screening strategies for FH were compared using a decision analytic Markov model. The study population included all Australians aged 18-40 years (8,297,729 individuals). There were three different health states in the model: ‘Alive, no CHD’, ‘Alive, with CHD’, and ‘Dead’. The analysis was aimed to capture CHD morbidity and mortality in the FH population over a lifetime horizon.

Assumptions used in the model

The model used a heterozygous FH (HeFH) population prevalence of 1/250 [1]. It was further assumed that the current Australian detection strategy would detect 10% of individuals with HeFH in the modeled population [5]. For the strategy of population genomic screening to detect pathogenic variants in the LDLR/APOB/PCSK9 genes, the model assumed to detect 100% of individuals with HeFH.

The model assumed that 64.7% of the current FH population were receiving statin therapy, following a recent Australian study in patients with phenotypic FH [8]. In the population genomic screening strategy, the model assumed that 100% of individuals identified with FH received statin therapy after diagnosis.

Other variables that were applied in the model included coronary heart disease risk in the primary and secondary prevention population, effects of lipid-lowering treatment and utility weights (reflection of the perception of health by individuals). In scenario analyses, several parameters were varied including, but not limited to, FH prevalence, proportion of detected cases, proportion of patients treated with lipid-lowering therapy, effect sizes, and test costs.

Costs

The study included costs of population genomic screening, direct medical costs, costs of lipid-lowering treatment, and productivity costs due to the increased morbidity and mortality in

individuals with FH. A validated cost-adaptation method [9] was used to adapt results to eight high-income countries: France, Germany, Italy, The Netherlands, Slovenia, Spain, the UK, and the USA.

Outcomes

The primary outcome of this analysis was the incremental cost-effectiveness ratio (ICER), which was defined as cost per quality-adjusted life year (QALY). Secondary outcomes were years of life saved, and the number of CHD events prevented by the population genomic screening strategy.

Main results

Primary outcome: Incremental cost-effectiveness ratio (cost per QALY)

• For population genomic screening to be cost-effective in Australian, the cost per screening test needs to be ≤AU$250, which was calculated using a willingness-to-pay threshold of AU$28,000 per QALY.
• The population genomic screening strategies with costs of AU$250 per screening test, would increase the total direct healthcare costs from current standard of care for FH (AU$1797 million) to AU$3232 million (95% UI 2266–5787 million, difference: AU$1434 million), which results in an incremental cost-effectiveness ratio of AU$27,705 (95% UI -6543 to 45,676) per QALY gained.
• From a societal perspective, taking into account productivity loss due to the increased morbidity and mortality in individuals with FH, population genomic screening was a cost-saving (dominant) strategy.

Secondary outcomes: Years of life saved, number of CHD events prevented and QALYs gained

• Population genomic screening would result in 33,488 (95% UI 25,170–39,635) years of life saved (1.0/FH patient) and 51,790 (95% UI 42,025–60,432) QALYs gained (1.6/FH patient). In addition, it would prevent 3093 CHD events (95% UI 1498–4494, 1813 non-fatal, 1279 fatal) over a lifetime, compared to the current standard-of-care for FH.

Adaptation of results to other countries

• The cost-adaptation analysis suggested that population genomic screening for FH could be cost-effective from a healthcare perspective in France, Germany, Italy, The Netherlands, Slovenia, Spain, the UK, and the USA. In addition, it would be a cost-saving (dominant) strategy in all investigated countries from a societal perspective.

Conclusion

References

Find this article online at Eur Heart J.