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- Title
Development of a new scoring system to predict 5-year incident diabetes risk in middle-aged and older Chinese.
- Authors
Han, Xu; Wang, Jing; Li, Yaru; Hu, Hua; Li, Xiulou; Yuan, Jing; Yao, Ping; Miao, Xiaoping; Wei, Sheng; Wang, Youjie; Liang, Yuan; Zhang, Xiaomin; Guo, Huan; Pan, An; Yang, Handong; Wu, Tangchun; He, Meian
- Abstract
Aims: The aim of this study was to develop a new risk score system to predict 5-year incident diabetes risk among middle-aged and older Chinese population. Methods: This prospective study included 17,690 individuals derived from the Dongfeng–Tongji cohort. Participants were recruited in 2008 and were followed until October 2013. Incident diabetes was defined as self-reported clinician diagnosed diabetes, fasting glucose ≥7.0 mmol/l, or the use of insulin or oral hypoglycemic agent. A total of 1390 incident diabetic cases were diagnosed during the follow-up period. <italic>β</italic>-Coefficients were derived from Cox proportional hazard regression model and were used to calculate the risk score.Results: The diabetes risk score includes BMI, fasting glucose, hypertension, hyperlipidemia, current smoking status, and family history of diabetes. The <italic>β</italic>-coefficients of these variables ranged from 0.139 to 1.914, and the optimal cutoff value was 1.5. The diabetes risk score was calculated by multiplying the <italic>β</italic>-coefficients of the significant variables by 10 and rounding to the nearest integer. The score ranges from 0 to 36. The area under the receiver operating curve of the score was 0.751. At the optimal cutoff value of 15, the sensitivity and specificity were 65.6 and 72.9%, respectively. Based upon these risk factors, this model had the highest discrimination compared with several commonly used diabetes prediction models.Conclusions: The newly established diabetes risk score with six parameters appears to be a reliable screening tool to predict 5-year risk of incident diabetes in a middle-aged and older Chinese population.
- Subjects
MATHEMATICAL models; PREDICTION models; HYPOGLYCEMIC agents; HYPOGLYCEMIC agents industry; DIABETES risk factors
- Publication
Acta Diabetologica, 2018, Vol 55, Issue 1, p13
- ISSN
0940-5429
- Publication type
Article
- DOI
10.1007/s00592-017-1047-1