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Cost-Effectiveness of ApoB, Non-HDL-C, and LDL-C Goals for Primary Prevention Lipid-Lowering Therapy
Samuel Luebbe1, Allan D Sniderman2, Andrew E Moran3
1Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
Insights
Apolipoprotein B (apoB) is a cost-effective marker for guiding lipid-lowering therapy in primary prevention, improving cardiovascular health outcomes. This approach offers better value compared to LDL-C or non-HDL-C goals.
Area of Science:
- Cardiovascular Medicine
- Health Economics
- Preventive Cardiology
Background:
- Apolipoprotein B (apoB) is a superior marker for atherosclerotic cardiovascular disease risk compared to LDL-C and non-HDL-C.
- The cost-effectiveness of using apoB, LDL-C, or non-HDL-C goals for lipid-lowering therapy (LLT) has not been established.
Purpose of the Study:
- To determine the relative cost-effectiveness of intensifying LLT for primary prevention using LDL-C, non-HDL-C, or apoB goals.
- To evaluate the economic impact of different lipid targets in cardiovascular disease prevention.
Main Methods:
- Economic evaluation using a computer simulation model.
- Analysis of a cohort of 250,000 US adults based on NHANES data, simulating LLT intensification with statins or ezetimibe.
- Model inputs derived from national surveys, cohort studies, and literature, with uncertainty explored via sensitivity analysis.
Main Results:
- An apoB goal yielded an incremental cost-effectiveness ratio of $30,300 per QALY gained, considered cost-effective at a $120,000 threshold.
- ApoB-guided LLT was optimal in 65% of probabilistic analyses, surpassing non-HDL-C (25%) and LDL-C goals.
- Higher costs associated with apoB goals were linked to longer life expectancy and sustained preventive treatment.
Conclusions:
- Apolipoprotein B (apoB) is a cost-effective marker for guiding primary prevention LLT.
- Utilizing apoB goals can improve population health outcomes in cardiovascular disease prevention.
- The findings support the use of apoB testing for optimizing LLT strategies.
Importance:
Apolipoprotein B (apoB) is a superior marker of residual atherosclerotic cardiovascular disease risk in patients treated with lipid-lowering therapy (LLT) compared with low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C). The cost-effectiveness of LDL-C, non-HDL-C, and apoB goals has not been established.
Objective:
To determine the relative cost-effectiveness of intensifying LLT for primary prevention based on LDL-C, non-HDL-C, and apoB goals.
Design, Setting, And Participants:
This economic evaluation used a computer simulation model to evaluate the cost-effectiveness of intensifying LLT with high-intensity statins or ezetimibe according to LDL-C, non-HDL-C, or apoB goals. A cohort of 250 000 statin-eligible and atherosclerotic cardiovascular disease-free US adults was constructed from 2005 to 2016 National Health and Nutrition Examination Survey participants (N = 4149). Individuals commenced the simulation after lipid screening and received statin therapy based on 2018 American Heart Association/American College of Cardiology guidelines. Model inputs were derived from national survey data, pooled longitudinal cohort studies, and published literature. Uncertainty was explored with traditional and probabilistic sensitivity analysis.
Exposures:
Lipid-lowering therapy was intensified if individuals did not achieve treated LDL-C level less than 100 mg/dL, non-HDL-C level less than 118 mg/dL, or apoB level less than 78.7 mg/dL.
Main Outcomes And Measures:
Lifetime quality-adjusted life-years (QALYs) and costs (in 2025 US dollars), discounted 3.0% annually. The primary outcome was the incremental cost-effectiveness ratio. Strategies were considered cost-effective if they cost less than $120 000 per QALY gained.
Results:
Compared with an LDL-C goal, 965 QALYs (95% uncertainty interval [UI], -3551 to 5341 QALYs) would be gained with a non-HDL-C goal, alongside a $2.1 million (95% UI, -$94.2 million to $92.0 million) reduction in costs. Compared with a non-HDL-C goal, 1324 QALYs (95% UI, -2602 to 5669 QALYs) would be gained with an apoB goal, alongside a $40.2 million (95% UI, -$43.6 million to $134 million) increase in costs, yielding an incremental cost-effectiveness ratio of $30 300 per QALY gained. At a willingness-to-pay threshold of $120 000 per QALY gained, an apoB goal was optimal in 65% of probabilistic analyses and a non-HDL-C goal was optimal in 25%. The cost of apoB testing was marginal; higher costs reflected longer life expectancy and prolonged preventive treatment.
Conclusions And Relevance:
The results of this computer simulation study suggest that apoB can be used as a cost-effective marker to guide primary prevention LLT and improve population health.
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