Estimated Atherosclerotic Cardiovascular Disease Risk Score: An Automated Decision Aid for Statin Therapy.

Pubmed ID: 35900196

Journal: Clinical chemistry

Publication Date: Oct. 6, 2022

Affiliation: ['Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.', 'Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA.']

MeSH Terms: Humans, Male, Female, Cardiovascular Diseases, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Risk Factors, Risk Assessment, Cholesterol, Nutrition Surveys, Atherosclerosis, Triglycerides, Decision Support Techniques, Lipoproteins, HDL

Authors: Dunbar R, Wolska A, Sampson M, Remaley AT, Amar M, Ueda M, Soffer D

Cite As: Sampson M, Wolska A, Amar M, Ueda M, Dunbar R, Soffer D, Remaley AT. Estimated Atherosclerotic Cardiovascular Disease Risk Score: An Automated Decision Aid for Statin Therapy. Clin Chem 2022 Oct 6;68(10):1302-1310.

Studies:

Abstract

BACKGROUND: Estimation of atherosclerotic cardiovascular disease (ASCVD) risk is a key step in cardiovascular disease (CVD) prevention, but it requires entering additional risk factor information into a computer. We developed a simplified ASCVD risk score that can be automatically calculated by the clinical laboratory when a fasting standard lipid panel is reported. METHODS: Equations for an estimated ASCVD (eASCVD) risk score were developed for 4 race/sex groups (non-Hispanic White/Black, men/women), using the following variables: total cholesterol, high-density lipoprotein cholesterol, triglycerides, and age. The eASCVD score was derived using regression analysis to yield similar risk estimates as the standard ASCVD risk equations for non-diabetic individuals not on lipid-lowering therapy in the National Health and Nutrition Examination Survey (NHANES) (n = 6027). RESULTS: At a cutpoint of 7.5%/10-year, the eASCVD risk score had an overall sensitivity of 69.1% and a specificity of 97.5% for identifying statin-eligible patients with at least intermediate risk based on the standard risk score. By using the sum of other risk factors present (systolic blood pressure >130 mmHg, blood pressure medication use, and cigarette use), the overall sensitivity of the eASCVD score improved to 93.7%, with a specificity of 92.3%. Furthermore, it showed 90% concordance with the standard risk score in predicting cardiovascular events in the Atherosclerosis Risk in Communities (ARIC) study (n = 14 742). CONCLUSIONS: Because the automated eASCVD risk score can be computed for all patients with a fasting standard lipid panel, it could be used as an adjunctive tool for the primary prevention of ASCVD and as a decision aid for statin therapy.