Predictive models for conversion of prediabetes to diabetes

AimTo clarify the natural course of prediabetes and develop predictive models for conversion to diabetes.MethodsA retrospective longitudinal study of 2105 adults with prediabetes was carried out with a mean observation period of 4.7 years. 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 (< − 0.31 kg/m2) and high δBMI (≥ − 0.31 kg/m2) subjects after matching the two groups for the covariates.ResultsDiabetes developed in 252 (2.5%/year), and positive family history, male sex, higher systolic blood pressure, plasma glucose (fasting and 1 h- and 2 h-values during 75 g 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).ConclusionsPrediabetes conversion to diabetes could be predicted with accuracy, and weight reduction during the observation was associated with lowered conversion rate.