Why the study?
PREVENT improves ASCVD risk estimation over Pooled Cohort Equations in older adults, but markers are needed to further refine risk estimates and guide personalized prevention.
Does the addition of specific biomarkers or polygenic risk scores improve risk de-escalation for incident ASCVD events in intermediate-risk older adults compared to the PREVENT equation alone?
Observational (n=7,764)
Does the addition of specific biomarkers or polygenic risk scores improve risk de-escalation for incident ASCVD events in intermediate-risk older adults compared to the PREVENT equation alone?
Adding polygenic risk for coronary artery disease to the PREVENT equations can help de-escalate ASCVD risk estimates and personalize prevention in intermediate-risk older adults.
May aid ASCVD risk de-escalation in low polygenic risk older adults; leaves open prospective validation versus PREVENT equations.
BACKGROUND: Previous studies showed that the Pooled Cohort Equations substantially overestimate atherosclerotic cardiovascular disease (ASCVD) risk in older adults, and the recently published PREVENT equation offers better performance. Identifying markers that can further refine risk estimates is essential for personalized prevention in this age group. This study evaluates the clinical utility of 6 markers for reclassifying intermediate-risk older adults (10-year PREVENT-estimated ASCVD risk, 7.5% to 20%), with a focus on de-escalation. METHODS: This post hoc analysis evaluated intermediate-risk older adults aged ≥70 years using data from ASPREE (Aspirin in Reducing Events in the Elderly; URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01038583). ASPREE was a randomized trial of low-dose aspirin versus placebo in healthy older adults who were free of prior cardiovascular events at enrollment. Six markers were evaluated: the lowest quartile (Q1) of NT-proBNP (N-terminal pro-B-type natriuretic peptide), hs-TnI (high-sensitivity troponin I), and hs-CRP (high-sensitivity C-reactive protein), polygenic risk for lipoprotein(a) and polygenic risk for coronary artery disease, and absence of family history of ASCVD. Incident ASCVD events were adjudicated by expert panels. Statistical performance of each marker was assessed using diagnostic likelihood ratios, change in Harrell C statistic (ΔC), and net reclassification index relative to a baseline model incorporating variables included in the PREVENT equation. RESULTS: The study included 7764 participants (48% female; median age, 74 years [interquartile range, 72–77]), with a median follow-up of 10.3 years. During follow-up, 725 participants (9.3%) experienced ASCVD events. Q1 polygenic risk for coronary artery disease was the most powerful marker for down-grading risk, providing 37% risk reduction (diagnostic likelihood ratio: 0.627) and improving discrimination (ΔC: +1.44%; P =0.004) when compared with the baseline model, and correctly reclassifying 25.9% of nonevents downward (net reclassification index: 0.101). Q1 hs-TnI showed second-best performance (diagnostic likelihood ratio: 0.727; ΔC: +0.71%, net reclassification index: 0.075). CONCLUSIONS: Adding polygenic risk for coronary artery disease to the PREVENT equations may further personalize risk estimates and support clinical decision-making for older adults at intermediate risk for ASCVD events.
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Zhou et al. (2026) conducted an observational in Intermediate-risk for ASCVD (n=7,764). Lowest quartile (Q1) polygenic risk for coronary artery disease vs. Baseline model incorporating PREVENT equation variables was evaluated on Incident ASCVD events (ΔC: +1.44%, p=0.004).
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