title: Overview of risk prediction models in cardiovascular disease research.
abstract: Many risk prediction models have been developed for cardiovascular diseases in different countries during the past three decades. However, there has not been consistent agreement regarding how to appropriately assess a risk prediction model, especially when new markers are added to an established risk prediction model. Researchers often use the area under the receiver operating characteristic curve (ROC) to assess the discriminatory ability of a risk prediction model. However, recent studies suggest that this method has serious limitations and cannot be the sole approach to evaluate the usefulness of a new marker in clinical and epidemiological studies. To overcome the shortcomings of this traditional method, new assessment methods have been proposed. The aim of this article is to overview various risk prediction models for cardiovascular diseases, to describe the receiver operating characteristic curve method and discuss some new assessment methods proposed recently. Some of the methods were illustrated with figures from a cardiovascular disease study in Australia.
authors.affiliation: World Health Organization Collaborating Centre for Obesity Prevention, Deakin University, Melbourne, Australia. jisheng.cui@deakin.edu.au
authors.forename: Jisheng
authors.initials: J
authors.lastname: Cui
mesh_terms: D019540:Area Under Curve; D015415:Biomarkers; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D006801:Humans; D015233:Models, Statistical; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods*
chemical_list: D015415:Biomarkers