• Christine Wallisch, Georg Heinze, Christoph Rinner, Gerald Mundigler, Wolfgang C Winkelmayer, and Daniela Dunkler.
• Medical University of Vienna, CeMSIIS, Section for Clinical Biometrics, Vienna, Austria.
• Int. J. Cardiol. 2019 May 15; 283: 165-170.

BackgroundCardiovascular prevention guidelines advocate the use of statistical risk equations to predict individual cardiovascular risk. However, predictive accuracy and clinical value of existing equations may differ in populations other than the one used for their development. Using baseline and follow-up data of the Austrian health-screening program, we assessed discrimination, calibration, and clinical utility of three widely recommended equations-the Framingham 1991 and 2008 general cardiovascular disease (CVD) equations, and the Pooled Cohort equations predicting atherosclerotic CVD.MethodsThe validation cohort comprised 1.7 M individuals aged 30-79, without documented CVD history who participated in the program from 2009 to 2014. CVD events were defined by a cardiovascular cause of hospitalization or death.ResultsThe observed five-year general CVD risk was 4.66%. Discrimination c-indices (0.72-0.78) were slightly lower than those reported for the development cohorts. C-indices for women were always higher than for men. CVD risk was overestimated by the Framingham 2008 equation, but underestimated by the Pooled Cohort equations. The Framingham 1991 equation was well-calibrated, especially for individuals up to 64 years. If applied to recommend health interventions at a predicted five-year risk between 5 and 10%, the equations were clinically useful with their net benefits, weighting true positives against false positives, ranging from 0.13 to 3.43%.ConclusionThe equations can discriminate high-risk from low-risk individuals, but predictive accuracy (especially for high-risk individuals) might be improved by recalibration. The Framingham 1991 equation yielded the most accurate predictions.Copyright © 2018 Elsevier B.V. All rights reserved.

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