Predicted burden could replace predicted risk in preventive strategies for cardiovascular disease

Publication date: Available online 21 September 2017
Source:Journal of Clinical Epidemiology
Author(s): G.R. Lagerweij, G.A. de Wit, K.G.M. Moons, W.M.M. Verschuren, J. Boer, H. Koffijberg
ObjectivesTo explore the extent of the differences in definitions of composite endpoints and assess how these differences influence estimates of CVD burden.Study Design and Settings: Data from a Dutch cohort study (n=19484) were used to calculate 10-year risks according to four CVD risk prediction models: ATP-III, Framingham (FRS), Pooled Cohort Equations (PCE) and SCORE. Health loss was estimated based on the impact of event types included in the corresponding composite endpoints. Finally, each prediction model was used to estimate the expected CVD burden in high-risk individuals, expressed as Quality-Adjusted Life Years (QALYs) lost.ResultsThe definition of the composite endpoints varied widely across the four models. FRS predicted the highest CVD risks and the composite endpoint used in SCORE was associated with the highest health burden. The predicted CVD burden in high-risk individuals was 0.23, 0.74, 0.43, and 0.39 QALYs lost per individual when using ATP, FRS, PCE and SCORE, respectively.ConclusionThe investigated CVD risk prediction models showed huge variation in definition of composite endpoints and associated health burden. Therefore, health consequences related to predicted risks cannot be readily compared across prediction models, and estimates of burden of disease depend crucially on the prediction model used.



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