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腹部肥胖患者 2 型糖尿病发病率的预测模型:来自一般人群的见解
Authors Tan C, Li B, Xiao L, Zhang Y, Su Y, Ding N
Received 18 August 2022
Accepted for publication 8 November 2022
Published 15 November 2022 Volume 2022:15 Pages 3555—3564
DOI https://doi.org/10.2147/DMSO.S386687
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Antonio Brunetti
Background: This study aimed to distinguish the risk factors for type 2 diabetes mellitus (T2DM) and construct a predictive model of T2DM in Japanese adults with abdominal obesity.
Methods: This study was a post hoc analysis. A total of 2012 individuals with abdominal obesity were included and randomly divided into training and validation groups at 70% (n = 1518) and 30% (n = 494), respectively. The LASSO method was used to screen for risk variables for T2DM, and to construct a nomogram incorporating the selected risk factors in the training group. We used the C-index, calibration plot, decision curve analysis, and cumulative hazard analysis to test the discrimination, calibration and clinical significance of the nomogram.
Results: In the training cohort, the C-index and receiver operating characteristic were 0.819 and the 95% CI was 0.776– 0.858, with a specificity and sensitivity of 77% and 74.68%, respectively. In the validation cohort, the C-index was 0.853; sensitivity and specificity were 77.6% and 88.1%, respectively. The decision curve analysis showed that the model’s prediction was effective and cumulative hazard analysis demonstrated that the high-risk score group was more likely to develop T2DM than the low-risk score group.
Conclusion: This nomogram may help clinicians screen abdominal obesity at a high risk for T2DM.
Keywords: type 2 diabetes, T2DM, abdominal obesity, nomogram, prediction model