Development and validation of risk prediction models for multiple cardiovascular diseases and Type 2 diabetes.

Accurate risk assessment of an individuals' propensity to develop cardiovascular diseases (CVDs) is crucial for the prevention of these conditions. Numerous published risk prediction models used for CVD risk assessment are based on conventional risk factors and include only a limited number of biomarkers. The addition of novel biomarkers can boost the discriminative ability of risk prediction models for CVDs with different pathogenesis.