Methods
We estimated the 10 year risk of diabetes in a cohort study of middle-aged and elderly participants who were free from diabetes at baseline. Cox regression coefficients were used to construct the simple points model and the discriminatory ability of the resulting prediction rule was determined using AUC and net reclassification improvement and integrated discrimination improvement statistics. Fivefold random splitting was used to test the internal validity and obtain bootstrap estimates of the AUC.
Results
Of the 2,960 participants without diabetes at the baseline examination, 548 developed type 2 diabetes during a median 10 year follow-up period. Age (four points), elevated fasting glucose (11 points), body mass index (eight points), triacylglycerol (five points), white blood cell count (four points) and a higher HDL-cholesterol (negative four points) were found to strongly predict diabetes incidence in a multivariate model. The estimated AUC for the model was 0.702 (95% CI 0.676–0.727). This model performed better than existing prediction models developed in other populations, including the Prospective Cardiovascular Münster, Cambridge, San Antonia and Framingham models for diabetes risk.