A Retrospective Population Study to Develop a Predictive Model of Prediabetes and Incident Type 2 Diabetes Mellitus from a Hospital Database in Japan Between 2004 and 2015

BACKGROUND: Type 2 diabetes mellitus is a global public health problem. Prediabetes may be reversed by weight loss, diet, and lifestyle changes. However, without intervention, between 30–50% of individuals with prediabetes develop type 2 diabetes. This retrospective population study was conducted to develop a predictive model of prediabetes and incident type 2 diabetes mellitus using data from 2004 to 2015 from the DRYAD Japanese hospital database. MATERIAL/METHODS: A retrospective longitudinal population study was conducted using the DRYAD database from Murakami Memorial Hospital, Gifu, Japan, to construct a predictive model for prediabetes and incident type 2 diabetes mellitus in the population. Univariate analysis and multivariate analysis were performed to identify the variables that were associated with prediabetes. These variables were used to construct (75% samples) and verify (25% samples) the predictive model. RESULTS: From 2004 to 2015, a total of 11,113 cases were identified. Multivariate logistic regression analysis included the six variables of age, waist circumference, smoking history, the presence of fatty liver, fasting blood glucose (FBG), and glycated hemoglobin (HbA1c) level. Data were used to construct (75% samples) and verify (25% samples) in a predictive model. The area under the receiver operating characteristic (ROC) curve (AUC) of the predictive model was 0.87 (0.85–0.89) in the training cohort and 0.87 (0.86–0.90) in the validation cohort. CONCLUSIONS: A prognostic model based on six variables was predictive for incident type 2 diabetes mellitus and prediabetes in a healthy population in Japan.