Validation of continuous clinical indices of cardiometabolic risk in a cohort of Australian adults

BMC Cardiovascular Disorders

Research Article

Anne W Taylor¹  Robert J Adams¹  Suzanne J Carroll²  Natasha J Howard²  Mark Daniel³  Catherine Paquet⁴ 

[1] Discipline of Medicine, The University of Adelaide, Adelaide, South Australia, Australia;Spatial Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia, Australia;Spatial Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia, Australia;Department of Medicine, The University of Melbourne, St. Vincent’s Hospital, Melbourne, VIC, Australia;Spatial Epidemiology and Evaluation Research Group, School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia, Australia;Research Centre of the Douglas Mental Health University Institute, Verdun, Québec, Canada;

关键词: Cardiometabolic;    Cardiovascular disease;    Type 2 diabetes;    Risk scores;    ROC;    AUC;    Validation;   

DOI  :  10.1186/1471-2261-14-27

 received in 2013-11-25, accepted in 2014-02-19,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundIndicators of cardiometabolic risk typically include non-clinical factors (e.g., smoking). While the incorporation of non-clinical factors can improve absolute risk prediction, it is impossible to study the contribution of non-clinical factors when they are both predictors and part of the outcome measure. Metabolic syndrome, incorporating only clinical measures, seems a solution yet provides no information on risk severity. The aims of this study were: 1) to construct two continuous clinical indices of cardiometabolic risk (cCICRs), and assess their accuracy in predicting 10-year incident cardiovascular disease and/or type 2 diabetes; and 2) to compare the predictive accuracies of these cCICRs with existing risk indicators that incorporate non-clinical factors (Framingham Risk Scores).MethodsData from a population-based biomedical cohort (n = 4056) were used to construct two cCICRs from waist circumference, mean arteriole pressure, fasting glucose, triglycerides and high density lipoprotein: 1) the mean of standardised risk factors (cCICR-Z); and 2) the weighted mean of the two first principal components from principal component analysis (cCICR-PCA). The predictive accuracies of the two cCICRs and the Framingham Risk Scores were assessed and compared using ROC curves.ResultsBoth cCICRs demonstrated moderate accuracy (AUCs 0.72 – 0.76) in predicting incident cardiovascular disease and/or type 2 diabetes, among men and women. There were no significant differences between the predictive accuracies of the cCICRs and the Framingham Risk Scores.ConclusionscCICRs may be useful in research investigating associations between non-clinical factors and health by providing suitable alternatives to current risk indicators which include non-clinical factors.

【 授权许可】

CC BY   
© Carroll et al.; licensee BioMed Central Ltd. 2014