Identifying Risk-De-Escalating Markers in PREVENT-Defined Intermediate-Risk Older Adults: Insights From ASPREE.
Zhen Zhou1, Chenglong Yu1,2, Paul Lacaze1
1School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia (Z.Z., C.Y., P.L., R.W., A.M.T., R.L.W., J.T.N., C.T., J.R.).
Polygenic risk for coronary artery disease best identifies older adults at intermediate atherosclerotic cardiovascular disease (ASCVD) risk who may not need intensive treatment. This marker helps personalize prevention strategies by accurately down-grading risk for many individuals.
Area of Science:
- Cardiovascular disease risk assessment
- Geriatric medicine
- Preventive cardiology
Background:
- Existing atherosclerotic cardiovascular disease (ASCVD) risk calculators, like the Pooled Cohort Equations, tend to overestimate risk in older adults.
- The PREVENT equation shows improved performance, but further refinement of risk estimates is needed for personalized prevention in this demographic.
- Identifying novel biomarkers is crucial for accurately stratifying risk and guiding treatment de-escalation in intermediate-risk older individuals.
Purpose of the Study:
- To evaluate the clinical utility of six potential biomarkers for reclassifying ASCVD risk in older adults.
- To specifically assess the ability of these markers to identify individuals who may be candidates for risk de-escalation.
- To compare the performance of these markers against the established PREVENT equation for risk prediction.
Main Methods:
- A post hoc analysis of the ASPREE randomized trial (NCT01038583) involving adults aged 70 years and older.
- Six markers were assessed: lowest quartile (Q1) of NT-proBNP, hs-TnI, hs-CRP, polygenic risk scores for Lp(a) and CAD, and absence of family history of ASCVD.
- Statistical methods included diagnostic likelihood ratios, change in Harrell C statistic (ΔC), and net reclassification index (NRI) compared to a PREVENT-based model.
Main Results:
- The study included 7764 participants (median age 74 years) with a median follow-up of 10.3 years; 725 (9.3%) experienced ASCVD events.
- Q1 polygenic risk for coronary artery disease (CAD) demonstrated the strongest risk-down-grading capability, reducing risk by 37% (DLR: 0.627) and improving discrimination (ΔC: +1.44%, P=0.004).
- Q1 hs-TnI showed the second-best performance, with a diagnostic likelihood ratio of 0.727, a ΔC of +0.71%, and an NRI of 0.075.
Conclusions:
- Polygenic risk for coronary artery disease is a powerful tool for refining ASCVD risk estimates in older adults.
- Incorporating polygenic risk for CAD into the PREVENT equation can enhance personalized risk assessment for intermediate-risk individuals.
- These findings support the use of polygenic risk scores to aid clinical decision-making and potentially de-escalate preventive therapies.
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