Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China
Yushan Wang,1,* Yushan Zhang,2,* Kai Wang,3 Yinxia Su,1 Jinhui Zhuge,2 Wenli Li,2 Shuxia Wang,1 Hua Yao1 1Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Urumqi, People’s Republic of China; 2College of Public Health, Xinjiang Medical Universit...
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| Formato: | article |
| Lenguaje: | EN |
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Dove Medical Press
2021
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| Acceso en línea: | https://doaj.org/article/b2f037e3db8b4ba8aebcd8836217f602 |
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| Sumario: | Yushan Wang,1,* Yushan Zhang,2,* Kai Wang,3 Yinxia Su,1 Jinhui Zhuge,2 Wenli Li,2 Shuxia Wang,1 Hua Yao1 1Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Urumqi, People’s Republic of China; 2College of Public Health, Xinjiang Medical University, Urumqi, People’s Republic of China; 3Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hua Yao; Shuxia WangCenter of Health Management, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830011, People’s Republic of ChinaTel +86-13999180161; +86-13579901672Email yaohua01@sina.com; 2724443591@qq.comObjective: 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/m2 (men) and 24.95kg/m2 (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.Keywords: type 2 diabetes mellitus, T2DM, nomogram, risk factor, risk predictive model |
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