Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/85818
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Type: Journal article
Title: Validation of continuous clinical indices of cardiometabolic risk in a cohort of Australian adults
Author: Carroll, S.
Paquet, C.
Howard, N.
Adams, R.
Taylor, A.
Daniel, M.
Citation: BMC Cardiovascular Disorders, 2014; 14(1):27-1-27-9
Publisher: BioMed Central
Issue Date: 2014
ISSN: 1471-2261
1471-2261
Statement of
Responsibility: 
Suzanne J Carroll, Catherine Paquet, Natasha J Howard, Robert J Adams, Anne W Taylor and Mark Daniel
Abstract: Background: Indicators 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). Methods: Data 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. Results: Both 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. Conclusions: cCICRs 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.
Keywords: Cardiometabolic; cardiovascular disease; type 2 diabetes; risk scores; ROC; AUC; validation
Rights: © 2014 Carroll et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
RMID: 0020137777
DOI: 10.1186/1471-2261-14-27
Grant ID: http://purl.org/au-research/grants/nhmrc/570150
http://purl.org/au-research/grants/nhmrc/631917
Appears in Collections:Medicine publications

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