{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T16:06:27Z","timestamp":1791389187385,"version":"4.3.3"},"reference-count":25,"publisher":"American Medical Association (AMA)","issue":"17","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA"],"published-print":{"date-parts":[[2026,5,5]]},"abstract":"\n Importance<\/jats:title>\n 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\u2013high-density lipoprotein cholesterol (non\u2013HDL-C). The cost-effectiveness of LDL-C, non\u2013HDL-C, and apoB goals has not been established.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To determine the relative cost-effectiveness of intensifying LLT for primary prevention based on LDL-C, non\u2013HDL-C, and apoB goals.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n 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\u2013HDL-C, or apoB goals. A cohort of 250\u202f000 statin-eligible and atherosclerotic cardiovascular disease\u2013free US adults was constructed from 2005 to 2016 National Health and Nutrition Examination Survey participants (N\u2009=\u20094149). 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.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Lipid-lowering therapy was intensified if individuals did not achieve treated LDL-C level less than 100 mg\/dL, non\u2013HDL-C level less than 118 mg\/dL, or apoB level less than 78.7 mg\/dL.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n 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\u202f000 per QALY gained.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Compared with an LDL-C goal, 965 QALYs (95% uncertainty interval [UI], \u22123551 to 5341 QALYs) would be gained with a non\u2013HDL-C goal, alongside a $2.1 million (95% UI, \u2212$94.2 million to $92.0 million) reduction in costs. Compared with a non\u2013HDL-C goal, 1324 QALYs (95% UI, \u22122602 to 5669 QALYs) would be gained with an apoB goal, alongside a $40.2 million (95% UI, \u2212$43.6 million to $134 million) increase in costs, yielding an incremental cost-effectiveness ratio of $30\u202f300 per QALY gained. At a willingness-to-pay threshold of $120\u202f000 per QALY gained, an apoB goal was optimal in 65% of probabilistic analyses and a non\u2013HDL-C goal was optimal in 25%. The cost of apoB testing was marginal; higher costs reflected longer life expectancy and prolonged preventive treatment.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jama.2026.2986","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T15:00:32Z","timestamp":1775660432000},"page":"1507","source":"Crossref","is-referenced-by-count":9,"title":["Cost-Effectiveness of ApoB, Non\u2013HDL-C, and LDL-C Goals for Primary Prevention Lipid-Lowering Therapy"],"prefix":"10.1001","volume":"335","author":[{"given":"Samuel","family":"Luebbe","sequence":"first","affiliation":[{"name":"Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allan D.","family":"Sniderman","sequence":"additional","affiliation":[{"name":"Mike and Valeria Rosenbloom Center for Cardiovascular Prevention, Division of Cardiology, McGill University Health Center, Montreal, Quebec, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew E.","family":"Moran","sequence":"additional","affiliation":[{"name":"Division of General Medicine, Columbia University Irving Medical Center, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John T.","family":"Wilkins","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois"},{"name":"Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ciaran 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