TY - JOUR
T1 - Development of a weighted cardiometabolic disease staging (CMDS) system for the prediction of future diabetes
AU - Guo, Fangjian
AU - Garvey, W. Timothy
N1 - Publisher Copyright:
Copyright © 2015 by the Endocrine Society.
PY - 2015/10/1
Y1 - 2015/10/1
N2 - Context: Metabolic syndrome traits are important risk factors for diabetes; however, each trait has different predictive power for future diabetes. Additionally, the impact of insulin resistance on metabolic profile can differ by gender and racial group, suggesting that gender-race specific prediction algorithms for diabetes may be warranted. Objective: To develop a quantitative scoring system based on weighting of risk components in the cardiometabolic disease staging (CMDS) system for the prediction of future diabetes. Design, Setting, and Participants: We derived the CMDS score in 2857 participants with valid follow-up information on incident diabetes from the Coronary Artery Risk Development in Young Adults study and validated it in 6425 older participants from the Atherosclerosis Risk in Communities study. We assigned a simple integer value for each CMDS risk factor component. Main Outcome Measures: Incident diabetes. Results: Fasting glucose, 2-hour glucose, waist circumference, and blood pressure components contributed similarly for the prediction of future diabetes (CMDS scores, 23, 21, 26, and 20, respectively). The area under the receiver operating characteristic curve was 0.7158 for the CMDS scoring system, whereas it was 0.7053 for the Framingham diabetes score. The CMDS components performed differently for prediction of future diabetes in Black and White men and women. The components with the highest predictivepowerfor diabeteswerewaist circumference in Blackmen, 2-hour glucose in Black women, and fasting glucose in both White men and White women. Conclusions: TheweightedCMDSscorehashighmodeldiscriminationpowerfordiabetesandcanbeused clinically to identify patients for weight loss therapy based on differential risk for future diabetes.
AB - Context: Metabolic syndrome traits are important risk factors for diabetes; however, each trait has different predictive power for future diabetes. Additionally, the impact of insulin resistance on metabolic profile can differ by gender and racial group, suggesting that gender-race specific prediction algorithms for diabetes may be warranted. Objective: To develop a quantitative scoring system based on weighting of risk components in the cardiometabolic disease staging (CMDS) system for the prediction of future diabetes. Design, Setting, and Participants: We derived the CMDS score in 2857 participants with valid follow-up information on incident diabetes from the Coronary Artery Risk Development in Young Adults study and validated it in 6425 older participants from the Atherosclerosis Risk in Communities study. We assigned a simple integer value for each CMDS risk factor component. Main Outcome Measures: Incident diabetes. Results: Fasting glucose, 2-hour glucose, waist circumference, and blood pressure components contributed similarly for the prediction of future diabetes (CMDS scores, 23, 21, 26, and 20, respectively). The area under the receiver operating characteristic curve was 0.7158 for the CMDS scoring system, whereas it was 0.7053 for the Framingham diabetes score. The CMDS components performed differently for prediction of future diabetes in Black and White men and women. The components with the highest predictivepowerfor diabeteswerewaist circumference in Blackmen, 2-hour glucose in Black women, and fasting glucose in both White men and White women. Conclusions: TheweightedCMDSscorehashighmodeldiscriminationpowerfordiabetesandcanbeused clinically to identify patients for weight loss therapy based on differential risk for future diabetes.
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U2 - 10.1210/jc.2015-2691
DO - 10.1210/jc.2015-2691
M3 - Article
C2 - 26241327
AN - SCOPUS:84943745752
SN - 0021-972X
VL - 100
SP - 3871
EP - 3877
JO - Journal of Clinical Endocrinology and Metabolism
JF - Journal of Clinical Endocrinology and Metabolism
IS - 10
ER -