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Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China

OBJECTIVE: A simple type 2 diabetes mellitus (T2DM) screening model was established preciously based on easily available variables for identifying high-risk individuals in western Xinjiang, China. METHODS: A total of 458,153 cases participating in the national health examination were recruited. Logi...

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Autores principales: Wang, Yushan, Zhang, Yushan, Wang, Kai, Su, Yinxia, Zhuge, Jinhui, Li, Wenli, Wang, Shuxia, Yao, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357405/
https://www.ncbi.nlm.nih.gov/pubmed/34393494
http://dx.doi.org/10.2147/DMSO.S313838
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author Wang, Yushan
Zhang, Yushan
Wang, Kai
Su, Yinxia
Zhuge, Jinhui
Li, Wenli
Wang, Shuxia
Yao, Hua
author_facet Wang, Yushan
Zhang, Yushan
Wang, Kai
Su, Yinxia
Zhuge, Jinhui
Li, Wenli
Wang, Shuxia
Yao, Hua
author_sort Wang, Yushan
collection PubMed
description OBJECTIVE: A simple type 2 diabetes mellitus (T2DM) screening model was established preciously based on easily available variables for identifying high-risk individuals in western Xinjiang, China. METHODS: A total of 458,153 cases participating in the national health examination were recruited. Logistic regression and the least absolute shrinkage and selection operator (LASSO) models were used for univariate analysis, factors selection, and the establishment of prediction model. Receiver operating characteristic (ROC) curve, Hosmer–Lemeshow test and clinical decision curve (CDA) were applied for evaluating the discrimination, calibration and clinical validity, respectively. The optimal threshold for predicting risk factors for T2DM has been estimated as well. RESULTS: The nomogram depicted the risk of T2DM based on different genders, the factors mainly consisted of age, family history of T2DM (FHOT), waist circumference (WC), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDLc), body mass index (BMI), high-density lipoprotein cholesterol (HDLc), etc. The area under ROC of men and women was 0.864 and 0.816 in the development group, similarly in the validation group, which was 0.865 and 0.815, respectively. The calibration curve showed that the nomogram was accurate for predicting the risk of T2DM, and the CDA proved great clinical application value of the nomogram. Threshold values of the age, WC, TC, TG, HDLc, BMI in different genders were 52.5 years old (men) and 48.5 years old (women), 85.50 cm (men) and 89.9 cm (women), 4.94 mmol/L (men) and 4.94mmol/L (women), 1.26mmol/L (men) and 1.67mmol/L (women), 1.40mmol/L (men) and 1.40mmol/L (women), 24.70kg/m(2) (men) and 24.95kg/m(2) (women), respectively. CONCLUSION: Our results give a clue that the nomogram may be useful for identifying adults who have high risk for diabetes, which is simple, affordable, with high credibility and can be widely implemented. Further studies are needed to evaluate the utility and feasibility of this model in various settings.
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spelling pubmed-83574052021-08-12 Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China Wang, Yushan Zhang, Yushan Wang, Kai Su, Yinxia Zhuge, Jinhui Li, Wenli Wang, Shuxia Yao, Hua Diabetes Metab Syndr Obes Original Research OBJECTIVE: A simple type 2 diabetes mellitus (T2DM) screening model was established preciously based on easily available variables for identifying high-risk individuals in western Xinjiang, China. METHODS: A total of 458,153 cases participating in the national health examination were recruited. Logistic regression and the least absolute shrinkage and selection operator (LASSO) models were used for univariate analysis, factors selection, and the establishment of prediction model. Receiver operating characteristic (ROC) curve, Hosmer–Lemeshow test and clinical decision curve (CDA) were applied for evaluating the discrimination, calibration and clinical validity, respectively. The optimal threshold for predicting risk factors for T2DM has been estimated as well. RESULTS: The nomogram depicted the risk of T2DM based on different genders, the factors mainly consisted of age, family history of T2DM (FHOT), waist circumference (WC), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDLc), body mass index (BMI), high-density lipoprotein cholesterol (HDLc), etc. The area under ROC of men and women was 0.864 and 0.816 in the development group, similarly in the validation group, which was 0.865 and 0.815, respectively. The calibration curve showed that the nomogram was accurate for predicting the risk of T2DM, and the CDA proved great clinical application value of the nomogram. Threshold values of the age, WC, TC, TG, HDLc, BMI in different genders were 52.5 years old (men) and 48.5 years old (women), 85.50 cm (men) and 89.9 cm (women), 4.94 mmol/L (men) and 4.94mmol/L (women), 1.26mmol/L (men) and 1.67mmol/L (women), 1.40mmol/L (men) and 1.40mmol/L (women), 24.70kg/m(2) (men) and 24.95kg/m(2) (women), respectively. CONCLUSION: Our results give a clue that the nomogram may be useful for identifying adults who have high risk for diabetes, which is simple, affordable, with high credibility and can be widely implemented. Further studies are needed to evaluate the utility and feasibility of this model in various settings. Dove 2021-08-07 /pmc/articles/PMC8357405/ /pubmed/34393494 http://dx.doi.org/10.2147/DMSO.S313838 Text en © 2021 Wang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wang, Yushan
Zhang, Yushan
Wang, Kai
Su, Yinxia
Zhuge, Jinhui
Li, Wenli
Wang, Shuxia
Yao, Hua
Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
title Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
title_full Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
title_fullStr Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
title_full_unstemmed Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
title_short Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
title_sort nomogram model for screening the risk of type ii diabetes in western xinjiang, china
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357405/
https://www.ncbi.nlm.nih.gov/pubmed/34393494
http://dx.doi.org/10.2147/DMSO.S313838
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