Integrating cardiac biomarkers into the AHA PREVENT equations: impact on atherosclerotic cardiovascular disease risk stratification

BACKGROUND: Cardiac biomarkers independently predict atherosclerotic cardiovascular disease (ASCVD) events but are not integrated into the newly developed AHA PREVENT equations. We evaluated their incremental value and clinical utility of hs-cTn and NT-proBNP for primary prevention based on PREVENT equations. METHODS AND RESULTS: We pooled 15,477 ASCVD-free participants from ARIC and MESA cohorts (mean age 62.0 years; 55.9% female), with external validation in UK Biobank (N=40,359). Over a median 12.1-year follow-up, 1,836 events occurred. Model performance was assessed via C-index, NRI, IDI, and Decision Curve Analysis (DCA). Individuals with clinical low/borderline risk (<7.5%) but elevated biomarkers exhibited higher observed event rate and hazards ratio (HR 2.74 95%CI: 2.45-3.06) than those with high clinical risk (≥7.5%) but normal biomarkers (HR 1.42 95%CI: 1.22-1.65). The combined high-risk group exhibited the highest risk (HR 4.46 95%CI: 3.92-5.07). Incorporating biomarkers reclassified 16.4% of low-risk (<5%) and 25.8% of borderline-risk (5%-7.5%) individuals into the intermediate-risk category (≥7.5%). The biomarker-augmented PREVENT model was well-calibrated and significantly improved discrimination (ΔC-index: 0.022; p<0.001) and reclassification (NRI: 0.193; IDI: 0.102). The reclassification improvement was highest in borderline-risk group. At the 7.5% clinical threshold, DCA demonstrated a three-fold increase in net benefit, identifying 27 additional true-positive cases per 1,000 individuals without increasing over-treatment. These findings were robustly confirmed in UK Biobank, where the borderline-risk group showed the highest improvement (ΔAUC=0.049; p <0.001). CONCLUSIONS: Integrating cardiac biomarkers into PREVENT equations identifies high-risk individuals masked by traditional factors, optimizing the clinical yield of primary prevention, especially for borderline-risk populations.