Background: The Predicting Risk of CVD Events (PREVENT) equations were developed to address limitations of the Pooled Cohort Equations (PCEs) in predicting atherosclerotic cardiovascular disease (ASCVD) risk. The comparative effectiveness of the PREVENT equations versus the PCEs in predicting mortality risk remains unknown.
Objectives: The purpose of this study was to compare the risk discrimination value of the PREVENT equations with the PCEs for predicting mortality.
Methods: This retrospective cohort study included individuals aged 40 to 79 years, free of cardiovascular disease, from the National Health and Nutrition Examination Survey (1999-2004). The outcomes of interest were all-cause and cardiovascular mortality. Harrell's C-statistics was used to examine risk discrimination.
Results: In this study, including 4,342 individuals (median age: 50.3 [IQR: 44.3-59.6] years, 51.5% females, and 77.0% non-Hispanic White), the median 10-year ASCVD risk was 4.0% (IQR: 1.5%-9.9%) using the PCEs and 2.4% (IQR: 1.2%-5.3%) using the PREVENT equations. The PREVENT equations generated lower ASCVD risk estimates in 81.0% (79.4%-82.6%) of individuals relative to the PCEs, with the lower estimates disproportionately affecting males (97.7% [96.6%-98.8%]) and Black individuals (89.6% [87.3%-91.8%]). Using a 5.0% risk threshold, PREVENT and PCEs classified 26.7% (∼16.9 million U.S. individuals) and 43.4% (∼27.5 million U.S. individuals), respectively, as having a 10-year ASCVD risk >5%. Among the 10.2% classified as high risk by the PCEs, 96.2% were reclassified to a lower risk by PREVENT. The risk discrimination value for all-cause and cardiovascular mortality was similar using the PREVENT equations and the PCEs.
Conclusions: The PREVENT equations provide similar risk discrimination values for mortality compared to the PCEs but estimate lower 10-year ASCVD risk. Replacing PCEs with the PREVENT equations could reduce statin eligibility in a significant number of individuals.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11734013 | PMC |
| http://dx.doi.org/10.1016/j.jacadv.2024.101372 | DOI Listing |
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