Study of Nomogram in Predicting the Risk of Type 2 Diabetes in Patients with Impaired Fasting Glucose

ZHU Lijuan; WANG Linlin; DONG Song; LIU Jia; LI Xiaojing; DU Yangfan; LIU Hongzhou; SHEN Yi

doi:10.3639/j.issn.2095-3097.2025.03.032

Abstract：Objective To construct and validate a nomogram model for predicting the 3-year and 5-year risk of type 2 diabetes mellitus(T2DM)in a Chinese population with impaired fasting glucose(IFG).Methods This study adopted a ret-rospective cohort design.A total of 7193 individuals with IFG were included and followed up for3-year and 5-year periods.Univariate and multivariate Cox regression analyses were performed to identify independent risk factors for T2DM.Based on Cox regression results,a nomogram was constructed to predict the 3-year and 5-year incidence of T2DM in IFG patients.The discrimination and calibration of the nomogram were evaluated using the C-index and calibration curves in both the training and validation sets.Results The study population was randomly divided into a modeling set(n=5 036)and a validation set(n=2 157).Multivariate Cox regression analysis in the training set identified age,body mass index(BMI),fasting plasma glucose(FPG),triglycerides(TG),and alanine aminotransferase(ALT)as independent risk factors for T2DM,which were incorporated into the nomogram model.In the training and validation sets,the C-indexes were 0.642 33(95%CI:0.625 34-0.659 31)and 0.642 37(95%CI:0.615 86-0.668 89),respectively.The calibration plot showed good agreement between the estimated probabilities and the actual observed rates.Conclusion The nomogram developed in this study is a simple and reliable tool for predicting the 3-year and 5-year risk of T2DM in the Chinese IFG population.It can help identify high-risk individuals early,providing a basis for timely intervention and reducing the incidence of T2DM.