Cardiovascular risk prediction in a population with the metabolic syndrome: Framingham vs. UKPDS algorithms

European Journal of Preventive Cardiology
Ella ZomerChristopher M Reid

Abstract

Cardiovascular disease (CVD) risk-prediction algorithms are key in determining one's eligibility for prevention strategies, but are often population-specific. Metabolic syndrome (MetS), a clustering of risk factors that increase the risk of CVD, does not currently have a risk-prediction algorithm available for prediction of CVD. The aim of this study was to compare the predictive capacities of an algorithm intended for 'healthy' individuals and one intended for 'diabetic' individuals. Individual-specific data from 2700 subjects defined as MetS but free of diagnosed CVD from the Australian Diabetes, Obesity and Lifestyle study was used to estimate 5-year risk of CVD using the two algorithms, and compared using Wilcoxon-signed rank test. CVD end point data was used to assess the performance using discrimination and calibration techniques of the two algorithms. Five-year risk-prediction comparisons demonstrated that the UKPDS algorithm overpredicted risk in the younger age groups (25-54 years) and underpredicted risk in the older age groups (≥55 years) compared to the Framingham algorithm. A total of 133 CVD events occurred over a median follow up of 5.0 years. Model performance analyses demonstrated both the Framingham and UKPDS ...Continue Reading

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Citations

Mar 28, 2013·American Journal of Cardiovascular Drugs : Drugs, Devices, and Other Interventions·Ella ZomerDanny Liew
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Sep 18, 2020·Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research·Lei SiAndrew J Palmer

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