Abstract

BackgroundEstablished risk models for the prediction of cardiovascular disease (CVD) include blood pressure, smoking and cholesterol parameters. The use of total cholesterol for CVD risk prediction has been questioned, particularly for primary prevention. We evaluated whether glucose could be used instead of total cholesterol for prediction of fatal CVD using data with long follow-up.MethodsWe followed-up 6,095 men and women aged ≥16 years who participated 1977-79 in a community based health study and were anonymously linked with the Swiss National Cohort until the end of 2008. During follow-up, 727 participants died of CVD. Based on the ESC SCORE methodology (Weibull regression), we used age, sex, blood pressure, smoking, and fasting glucose or total cholesterol. The mean Brier score (BS), area under the receiver-operating characteristic curve (AUC) and integrated discrimination improvement (IDI) were used for model comparison. We validated our models internally using cross-validation and externally using another data set.ResultsIn our models, the p-value of total cholesterol was 0.046, that of glucose was p < 0.001. The model with glucose had a slightly better predictive capacity (BS: 2216x10-5 vs. 2232x10-5; AUC: 0.9181 vs. 0.9169, IDI: 0.009 with p-value 0.026) and could well discriminate the overall risk of persons with high and low concentrations. The external validation confirmed these findings.ConclusionsOur study suggests that instead of total cholesterol glucose can be used in models predicting overall CVD mortality risk.

Highlights

  • Estimation of individual risk of cardiovascular disease (CVD) is traditionally based on age, sex, smoking status, blood pressure and cholesterol parameters

  • There is increasing evidence for glucose parameters being independent CVD risk factors [4]. This variable was available in National Research Program 1A (NRP 1A), and we tested the use glucose instead of total cholesterol for

  • Study population Risk factor data stems from men and women aged ≥16 years who participated in the National Research Program 1A (NRP 1A), a community health promotion initiative focused on cardiovascular disease prevention and conducted

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Summary

Introduction

Estimation of individual risk of cardiovascular disease (CVD) is traditionally based on age, sex, smoking status, blood pressure and cholesterol parameters. Based on these variables, the SCORE (Systematic COronary Risk Evaluation) risk model predicts fatal CVD events [1]. There is increasing evidence for glucose parameters being independent CVD risk factors [4]. This variable was available in NRP 1A, and we tested the use glucose instead of total cholesterol for. Established risk models for the prediction of cardiovascular disease (CVD) include blood pressure, smoking and cholesterol parameters. We evaluated whether glucose could be used instead of total cholesterol for prediction of fatal CVD using data with long follow-up

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