Predicting diabetes – clinical, biological and genetic approaches: the D.E.S.I.R. Study

Abstract

Objectives— To provide a simple clinical diabetes risk score; to identify characteristics which predict later diabetes using variables available in clinic, then additionally biological variables and polymorphisms.

Research design and methods— Incident diabetes was studied in 1863 men and 1954 women, 30-65 years at baseline, by treatment or by fasting plasma glucose ≥ 7.0 mmol/l at 3-yearly examinations over nine years. Sex-specific logistic regression equations were used to select variables for prediction.

Results— 140 men, 63 women developed diabetes. The predictive clinical variables were: waist circumference and hypertension in both sexes; for men: smoking, for women: diabetes in the family. Discrimination, as measured by the areas under the receiver operating curves (AROC), were 0.713 for men and 0.827 for women, a little higher than for the FINDRISC score, with fewer variables in the score. Combining clinical and biological variables, the predictive equation included for men: fasting glucose, waist circumference, smoking, □-glutamyltransferase; for women fasting glucose, BMI, triglycerides, diabetes in family. The number of TCF7L2 and IL6 deleterious alleles was predictive in both sexes, but after including the above clinical and biological variables, this variable was only predictive in women (p < 0.03) and the AROC statistics increased only marginally.

Conclusions— The best clinical predictor of diabetes is adiposity, and baseline glucose is the best biological predictor. Clinical and biological predictors differed marginally between men and women. The genetic polymorphisms added little to the prediction of diabetes.