Zeyin Lin1, Dongming Guo2, Juntian Chen2, Baoqun Zheng3. 1. Department of Ultrasound, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China. 2. Department of General Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China. 3. Department of Ultrasound, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China. sdfycsk@126.com.
Abstract
PURPOSE: To develop a nomogram for predicting 5-year incidence of type 2 diabetes (T2D) in Chinese adults. METHODS: This is a retrospective cohort study from a prospectively collected database. We included a total 32,766 adults free of T2D at baseline with a median follow-up of 3 years. Univariate and multivariate Cox regression analyses were applied to identify independent predictors. A nomogram was constructed to predict 5-year incident rate of T2D based on the multivariate analysis results. Harrell's C-indexes and calibration plots were used to evaluate the accuracy of the nomogram in both internal and external validations. RESULTS: The overall prevalence of T2D was 2.1%. Participants were randomly divided into a training set (n = 21,844) and a validation set (n = 10,922). After multivariate analysis in the training set, age, sex, BMI, hypertension, dyslipidemia, smoking status, and family history were found as risk predictors and integrated into the nomogram. Harrell's C-indexes were 0.815 (95% CI: 0.797-0.834) and 0.779 (95% CI: 0.747-0.811) in the training and validation sets, respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. CONCLUSION: Our nomogram could be a simple and reliable tool for predicting 5-year risk of developing T2D in high-risk Chinese. Through the model, early identifying high-risk individuals is helpful for timely intervention to reduce the incidence of T2D.
RCT Entities:
PURPOSE: To develop a nomogram for predicting 5-year incidence of type 2 diabetes (T2D) in Chinese adults. METHODS: This is a retrospective cohort study from a prospectively collected database. We included a total 32,766 adults free of T2D at baseline with a median follow-up of 3 years. Univariate and multivariate Cox regression analyses were applied to identify independent predictors. A nomogram was constructed to predict 5-year incident rate of T2D based on the multivariate analysis results. Harrell's C-indexes and calibration plots were used to evaluate the accuracy of the nomogram in both internal and external validations. RESULTS: The overall prevalence of T2D was 2.1%. Participants were randomly divided into a training set (n = 21,844) and a validation set (n = 10,922). After multivariate analysis in the training set, age, sex, BMI, hypertension, dyslipidemia, smoking status, and family history were found as risk predictors and integrated into the nomogram. Harrell's C-indexes were 0.815 (95% CI: 0.797-0.834) and 0.779 (95% CI: 0.747-0.811) in the training and validation sets, respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. CONCLUSION: Our nomogram could be a simple and reliable tool for predicting 5-year risk of developing T2D in high-risk Chinese. Through the model, early identifying high-risk individuals is helpful for timely intervention to reduce the incidence of T2D.
Entities:
Keywords:
Diabetes prevalence; Epidemiology; Nomogram; Risk factors; Type 2 diabetes
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