New biomarkers and predictive models that aim to improve the identification of people at risk of cardiovascular disease are constantly proposed. Clinicians need to be aware of the various methods used to assess these biomarkers and models and how these should be interpreted. New biomarkers and models are assessed in terms of their contribution to global fit, discrimination, calibration, and reclassification. These measures, when used in isolation, do not address the clinically important questions of whether the new model predicts risk more accurately than existing models and whether the risks predicted for individuals are sufficiently different to warrant a change in treatment decisions. We recommend that these measures be supplemented with graphical displays such as a calibration plot for the Hosmer-Lemeshow test and a scatterplot of the risks predicted by the models being compared. We encourage researchers to report such analyses from studies on the clinical utility of new biomarkers because this information is pertinent for the clinician who must decide whether to test for a new biomarker in their clinical practice.
Calibration plots for the predictive model containing the Framingham variables and retinal arteriolar caliber. A, Categories based on equal increments of risk (P = .35, Gronnesby-Borgan test). B, Categories based on equal numbers of people in each category (P = .52, Gronnesby-Borgan test).
Ten-year risk of incident coronary heart disease (CHD) predicted by the model containing retinal arteriolar caliber and Framingham variables against risk predicted by model containing only the Framingham variables. Data are given as CHD events/total number of events and censored observations (total = 207/4912).
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