Most adults eligible for statins based on PREVENT equations did not report statin use
FRIDAY, June 21, 2024 (HealthDay News) — Use of the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations reduces the number of adults meeting criteria for primary prevention statin therapy compared with use of the 2013 pooled cohort equations (PCEs), according to a study published online June 10 in JAMA Internal Medicine.
Timothy S. Anderson, M.D., from the University of Pittsburgh, and colleagues conducted a cross-sectional study involving adults aged 40 to 75 years who participated in the National Health and Nutrition Examination Survey from 2017 to March 2020. National estimates of 10-year atherosclerotic cardiovascular disease (ASCVD) risk were compared using the 2013 PCEs and the PREVENT equations, developed in 2023.
The researchers found that 20.7 percent of the weighted sample of 3,785 U.S. adults without known ASCVD reported current statin use. The mean estimated 10-year ASCVD risk was 8.0 and 4.3 percent using the PCEs and PREVENT equations, respectively. Compared with the PCEs, the mean estimated 10-year ASCVD risk was lower using the PREVENT equations across all age, sex, and racial subgroups, with the largest difference seen for Black adults (10.9 versus 5.1 percent) and those aged 70 to 75 years (22.8 versus 10.2 percent). The number of adults meeting criteria for primary prevention statin therapy would be reduced from 45.4 to 28.3 million with use of the PREVENT equations instead of the PCEs. Based on the PREVENT equations, 44.1 percent of adults eligible for primary prevention statin therapy reported currently taking statins.
“Use of the PREVENT equations could result in 17.3 million patients no longer meeting criteria for primary prevention statin therapy,” the authors write. “However, the majority of adults eligible for receiving such therapy based on PREVENT equations are not currently receiving statins.”
Abstract/Full Text (subscription or payment may be required)
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Considerable Gaps Identified in LDL Cholesterol Control
Machine Learning LDL-C Equation Comparable to Original Martin-Hopkins
Cardiovascular Risk Factors Linked to Increased Plaque Burden
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