Predictive models for conversion of prediabetes to diabetes.

AIM: To clarify the natural course of prediabetes and develop predictive models for conversion to diabetes. METHODS: A retrospective longitudinal study of 2105 adults with prediabetes was carried out with a mean observation period of 4.7years. Models were developed using multivariate logistic regression analysis and verified by 10-fold cross-validation. The relationship between [final BMI minus baseline BMI] (δBMI) and incident diabetes was analyzed post hoc by comparing the diabetes conversion rate for low (< -0.31kg/m2) and high δBMI (≥ -0.31kg/m2) subjects after matching the two groups for the covariates. RESULTS: Diabetes developed in 252 (2.5%/year), and positive family history, male sex, higher systolic blood pressure, plasma glucose (fasting and 1h- and 2h-values during 75g OGTT), hemoglobin A1c (HbA1c) and alanine aminotransferase were significant, independent predictors for the conversion. By using a risk score (RS) that took account of all these variables, incident diabetes was predicted with an area under the ROC curve (95% CI) of 0.80 (0.70-0.87) and a specificity of prediction of 61.8% at 80% sensitivity. On division of the participants into high- (n=248), intermediate- (n=336) and low-risk (n=1521) populations, the conversion rates were 40.1%, 18.5% and 5.9%, respectively. The conversion rate was lower in subjects with low than high δBMI (9.2% vs 14.4%, p=0.003). CONCLUSIONS: Prediabetes conversion to diabetes could be predicted with accuracy, and weight reduction during the observation was associated with lowered conversion rate.