Key result
Novel biomarkers yield only modest discrimination improvements over traditional CV risk models.
Why the study?
Despite advances in risk prediction, cardiovascular prevention remains suboptimal due to limitations in model architecture, incomplete integration of contextual determinants, and inadequate translation into clinical practice.
Population
Epidemiological, methodological, and health systems evidence published between 2000 and 2025
Design
Review
Authors
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Modest discrimination gains from added biomarkers advise against routine use; leaves open whether implementation strategies can reduce events.
Effect estimate: ΔC-statistic ≈ 0.004-0.007
Despite methodological advances in cardiovascular risk prediction, improvements in model discrimination remain modest and have not consistently translated into reduced cardiovascular burden due to persistent implementation gaps.
Andrei C. Spósito (2026) conducted a review in Cardiovascular disease. Novel biomarkers or variables vs. Traditional risk factors was evaluated on Discrimination (ΔC-statistic) (ΔC-statistic ≈ 0.004-0.007). Adding novel biomarkers to traditional cardiovascular risk models produced only modest improvements in discrimination (ΔC-statistic ≈ 0.004-0.007) without proportional reductions in disease burden.
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