09.12.2019 | Original Article
A nomogram for predicting 5-year incidence of type 2 diabetes in a Chinese population
verfasst von:
Zeyin Lin, Dongming Guo, Juntian Chen, Baoqun Zheng
Erschienen in:
Endocrine
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Ausgabe 3/2020
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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.