High-sensitive factor I and C-reactive protein based biomarkers for coronary artery disease

Area of Science:

• Cardiology
• Biomarkers
• Preventive Medicine

Background:

• Coronary artery disease (CAD) remains a leading cause of mortality worldwide.
• Accurate risk stratification is crucial for effective primary prevention strategies.
• Current risk assessment models may not fully capture all relevant predictive information.

Purpose of the Study:

• To analyze the efficacy of high-sensitive factor I and C-reactive proteins as biomarkers for coronary artery disease (CAD).
• To evaluate the impact of incorporating these biomarkers into existing risk prediction models.
• To model the clinical implications of statin therapy based on these enhanced risk assessments.

Main Methods:

• A meta-analysis of 19 cohort studies involving 21,567 participants without prior CAD.
• Development and refinement of a prognostic model for CAD risk.
• Assessment of risk discrimination using the C-index.
• Modeling of statin therapy initiation based on predicted 10-year risk categories.

Main Results:

• The baseline prognostic model demonstrated a C-index increase of 0.0101 with conventional risk factors.
• Incorporating factor I and C-reactive proteins individually raised the C-index by 0.0045 and 0.0053, respectively.
• Conventional risk factors alone classified 2,254 out of 15,000 adults (≥45 years) as medium risk.
• Statin therapy was initiated for individuals with >20% predicted risk or existing risk factors like diabetes.

Conclusions:

• High-sensitive factor I and C-reactive proteins significantly enhance the predictive accuracy of CAD risk models.
• Assessing these biomarkers in individuals at medium risk could lead to improved prevention outcomes.
• Screening 390-500 people with medium CAD risk using these biomarkers may prevent one additional CAD event per decade.