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. 2022 Sep-Oct;16(5):667-675.
doi: 10.1016/j.jacl.2022.07.014. Epub 2022 Jul 30.

Cost-effectiveness of population-wide genomic screening for familial hypercholesterolemia in the United States

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Cost-effectiveness of population-wide genomic screening for familial hypercholesterolemia in the United States

Scott J Spencer et al. J Clin Lipidol. 2022 Sep-Oct.

Abstract

Background: Population genomic screening for familial hypercholesterolemia (FH) in unselected individuals can prevent premature cardiovascular disease.

Objective: To estimate the clinical and economic outcomes of population-wide FH genomic screening versus no genomic screening.

Methods: We developed a decision tree plus 10-state Markov model evaluating the identification of patients with an FH variant, statin treatment status, LDL-C levels, MI, and stroke to compare the costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness of population-wide FH genomic screening. FH variant prevalence (0.4%) was estimated from the Geisinger MyCode Community Health Initiative (MyCode). Genomic test costs were assumed to be $200. Age and sex-based estimates of MI, recurrent MI, stroke, and recurrent stroke were obtained from Framingham risk equations. Additional outcomes independently associated with FH variants were derived from a retrospective analysis of 26,025 participants screened for FH. Sensitivity and threshold analyses were conducted to evaluate model assumptions and uncertainty.

Results: FH screening was most effective at younger ages; screening unselected 20-year-olds lead to 111 QALYs gained per 100,000 individuals screened at an incremental cost of $20 M. The incremental cost-effectiveness ratio (ICER) for 20-year-olds was $181,000 per QALY, and there was a 38% probability of cost-effectiveness at a $100,000 per QALY willingness-to-pay threshold. If genomic testing cost falls to $100, the ICER would be $91,000 per QALY.

Conclusion: Population FH screening is not cost-effective at current willingness to pay thresholds. However, reducing test costs, testing at younger ages, or including FH within broader multiplex screening panels may improve clinical and economic value.

Keywords: Cost-effectiveness analysis; Cost-utility analysis; Familial hypercholesterolemia; Genomic screening; Population screening.

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Conflict of interest statement

Declaration of Competing Interest The authors declare no conflicts of interest. The funders did not have a role in the design of the study, in the collection, analysis, or interpretation of data, in the manuscript writing, or in the decision to publish results.

Figures

Figure 1.
Figure 1.
Model Schematic
Figure 2:
Figure 2:
One Way Sensitivity Analysis for 20-year-olds and 35-year-olds
Figure 3:
Figure 3:
Base Case Results by Age of Genomic Screening

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