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 predictive power for diabetes were waist circumference in Black men, 2-hour glucose in Black women, and fasting glucose in both White men and White women.
Conclusions: The weighted CMDS score has high model discrimination power for diabetes and can be used clinically to identify patients for weight loss therapy based on differential risk for future diabetes.