Abstract 101: Cost-Effectiveness and Decision Analysis of Polygenic Risk Scores in Statin Use for Primary Prevention

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Abstract

Research Objective: Polygenic risk scores can improve prediction of first-time cardiovascular disease (CVD). Prediction of future events is the central factor in statin use in current guidelines Therefore, we hypothesized that if polygenic risk scores were added to current risk scores, statin use could become more efficient. We performed a cost-effectiveness analysis to see if genomic testing could be a cost-effective way to prevent CVD.

Study Design: Decision-analytic model of genomic testing for statin decision-making.

Data sources: Published literature

Time Horizon: Lifetime

Perspective: Third-party payer

Intervention: Statin decision-making based on current guidelines or based on current guidelines augmented with genetic testing in all Americans ages 40-75 with estimated 10-year CVD risk of 5-20%.

Population Studied: Primary prevention population in the United States.

Outcome Measures: Quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and total 10-year spending.

Principal Findings: At $200 per genetic test and $144 for a year of medium-strength statin use, full adherence to the current guidelines are estimated to cost $66,155 per QALY saved. Genetic testing would be $263,000 per additional QALY saved. These results are sensitive to improvements in genetic prediction and cost of genetic testing.

Conclusions: Genomic testing to improve statin use is cost-effective for a very large number of Americans at current prices.

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