Predictive models for future risk of coronary heart disease (CHD) based on traditional risk factors, such as age, male gender, LDL cholesterol, HDL cholesterol, diabetes mellitus, hypertension, smoking and family history of premature CHD, are quite robust but leave room for further improvement. Thus, efforts are being made to assess additional biomarkers for CHD, such as, lipoprotein (a), C-reactive protein, fibrinogen, lipoprotein-associated phospholipase A2, homocysteine and others. However, none of the novel biomarkers has demonstrated improved prediction beyond traditional risk factor models in a consistent fashion across multiple cohorts. Many criteria have to be fulfilled before a biomarker can be considered clinically relevant. Another way is to develop new models predicting long-term or life-time risk of CHD. Further research using novel biomarkers and long-term predictive models has the potential to improve CHD risk prediction.
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism