Classical and novel biomarkers for cardiovascular risk prediction in the United States

Area of Science:

• Cardiology
• Preventive Medicine
• Epidemiology

Background:

• Cardiovascular disease (CVD) risk prediction models are crucial for primary prevention.
• Traditional risk factors from cohort studies form the basis of current models.
• Evaluating novel risk markers is an ongoing area of research.

Purpose of the Study:

• To review cardiovascular risk prediction in the US.
• To assess the utility of novel risk factors in improving CVD risk prediction.
• To summarize recommendations for incorporating novel markers into clinical practice.

Main Methods:

• Review of existing literature on cardiovascular risk prediction models.
• Analysis of studies evaluating novel risk markers.
• Summary of conclusions from a US consensus panel on risk prediction.

Main Results:

• Classical risk factors remain powerful predictors of CVD.
• Many novel risk markers show association with CVD but offer marginal improvement over traditional factors.
• A US consensus panel identified specific novel markers for clinical use.

Conclusions:

• Traditional risk factors are foundational for cardiovascular risk prediction.
• Novel markers like hemoglobin A1c, microalbuminuria, C-reactive protein, and others may enhance risk stratification in select populations.
• Clinical measurement of certain novel markers is deemed reasonable for intermediate-risk patients.