External validation of the 2023 American Heart Association Predicting Risk of cardiovascular disease EVENTs equations for atherosclerotic cardiovascular disease in primary cardiovascular prevention setting and comparison with 2021 Systematic COronary Risk Evaluation and 2013 Pooled Cohort Equations.

Aims: External validation of the new 10-year PREVENT risk score for atherosclerotic cardiovascular disease (ASCVD) is important to assess its potential clinical applicability in Switzerland and to highlight its influence in preventive treatment eligibility.

Methods and results: This study, which was not used in the development process of PREVENT, included 5064 individuals from a prospective Swiss cohort, aged 40 or older, without pre-existing ASCVD, and with complete data for risk score calculation. Main outcomes were adjudicated ASCVD events, including fatal and non-fatal myocardial infarction and strokes. The performances of the PREVENT score were assessed overall, and stratified by gender and age groups (<70 vs. ≥70 years), and compared with SCORE2 and the Pooled Cohort Equation (PCE) scores. Among 4356 participants followed from 2009 to 2012 over a median of 9 years, 224 experienced a first incident of ASCVD. The PREVENT cardiovascular risk prediction model demonstrated adequate discrimination performance, correctly identifying 76% of concordant pairs [C-Index, 95% Confidence Interval (CI) 0.73 to 0.79]. The model's calibration performances suggest systematic underestimation (Observed/Expected ratio 1.45, 95% CI 1.44-1.46), especially in women and those under 70 years old, yet it maintained positive clinical utility across all subgroups, particularly at the 7.5% threshold, which is the lower limit of the intermediate-risk category in clinical practice. However, PREVENT did not improve predictive performance when compared with SCORE2 and PCE.

Conclusion: Our study confirmed the PREVENT model demonstrated adequate discrimination and calibration capabilities, along with significant clinical utility, particularly at intermediate-risk thresholds. However, it did not outperform the established models, SCORE2 or PCE. Additionally, PREVENT may systematically underestimate risk, which could raise concerns about the underprescription of preventive treatments.