Clinical utility of novel biomarkers for cardiovascular disease risk stratification

Area of Science:

• Cardiology
• Biomarkers
• Risk Prediction

Background:

• Established cardiovascular disease (CVD) risk factors, including those for coronary artery disease (CAD), have been identified over decades.
• While conventional risk factors are validated, they often fail to accurately predict individual patient risk, leading to misclassification.
• This necessitates the exploration of novel biomarkers to enhance cardiovascular risk prediction accuracy.

Purpose of the Study:

• To review and discuss extensively investigated biomarkers for cardiovascular (CV) risk prediction.
• To critically evaluate the evidence supporting the use of these biomarkers in improving CV risk prediction models.
• To question the actual predictive power of novel biomarkers compared to traditional risk factors.

Main Methods:

• Literature review of studies investigating genetic and non-genetic biomarkers for cardiovascular risk.
• Analysis of existing evidence on the predictive capabilities of various biomarkers.
• Comparison of the performance of novel biomarkers against conventional risk factors in predictive models.

Main Results:

• Numerous genetic and non-genetic biomarkers have been explored to improve cardiovascular risk prediction.
• Only a limited number of these novel biomarkers have demonstrated significant improvement over traditional risk factors.
• The predictive utility of many investigated biomarkers remains uncertain or insufficient.

Conclusions:

• Despite extensive research, accurately predicting individual coronary artery disease and cardiovascular disease risk remains challenging.
• Novel biomarkers have shown limited success in significantly enhancing the predictive accuracy of existing cardiovascular risk models.
• Further rigorous investigation is required to validate the clinical utility of biomarkers in cardiovascular risk stratification.