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

Abstract

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. 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). 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). 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.