Key result
CVD risk models show acceptable but lower discrimination in older adults and ignore competing risks.
Why the study?
Older adults represent a rapidly expanding population with elevated CVD risk, necessitating an examination of relevant CVD risk prediction models, their performance, and clinical implications.
CVD risk prediction in older adults has acceptable but modest discrimination and variable calibration, highlighting the need to incorporate geriatric-specific factors to improve accuracy.
Answers are grounded in this paper and cite their sources.
May warrant caution applying current models in older adults; leaves open development of tools incorporating competing risks.
PURPOSE OF REVIEW: This review examines cardiovascular disease (CVD) risk prediction models relevant to older adults, a rapidly expanding population with elevated CVD risk. It discusses model characteristics, performance metrics, and clinical implications. RECENT FINDINGS: Some models have been developed specifically for older adults, while several others consider a broader age range, including some older individuals. These models vary in terms of predictors, outcomes, horizon, and statistical approaches, with some accounting for competing risks and considering age-predictor interactions. Discrimination is generally acceptable and more modest in older versus younger individuals. Calibration shows great variation across populations. Accurate CVD risk prediction is essential to guide individualized prevention strategies and support shared decision-making in older adults. CVD risk prediction in this population is challenged by age-related CVD risk heterogeneity, elevated competing risk due to non-CVD mortality, and comorbidities. Further refinement by incorporating geriatric-specific factors may help to enhance discrimination.
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Colantonio et al. (2025) conducted a review in Cardiovascular disease. Cardiovascular disease risk prediction models was evaluated. Cardiovascular disease risk prediction models generally demonstrate acceptable but lower discriminatory performance in older adults compared to younger individuals, and often fail to account for competing risks.
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