Abstract:Development and validation of a prediction model for the risk of type 2 diabetes (T2DM) in the elderly in China was attempted. Based on the database of a health examination project in China, 24,804 elderly people without T2DM at baseline were included, and the follow-up time was 3 and 5 years. Divided into training set and validation set at a ratio of 7:3, univariate and multivariate Cox regression analysis was used to determine independent risk factors, and a nomogram was constructed to predict the 3-year and 5-year incidence rate of T2DM in the elderly in China. C index, calibration chart and clinical decision curve analysis (DCA) are used to evaluate the accuracy of nomogram in the validation set. Finally, age, fasting plasma glucose (FPG), body mass index (BMI), systolic blood pressure (SBP), triglyceride (TG), alanine aminotransferase (ALT) and urea nitrogen (UN) were found to be independent risk factors for T2DM, and were included in the nomogram. In the training set and validation set, the C index was 0.8278 (95% CI: 0.8125-0.8432) and 0.8414 (95% CI: 0.8195-0.8632), respectively. The calibration diagram shows that there is good consistency between the estimated probability and the actual observation rate. DCA shows that early intervention in high-risk groups according to this nomogram can obtain net benefits. Through this model, early identification of high-risk groups is helpful to timely intervention and reduce the incidence rate of T2DM.