scholarly journals Resistin Protein Analysis Using Receiver Operating Characteristics Curve in Predicting the Occurrence of Type 2 Diabetes Mellitus in Respondents of Cohort Study of Risk Factors for Noncommunicable Diseases in Bogor

Author(s):  
Uly Alfi Nikmah ◽  
Asri Werdhasari ◽  
Frans Dany ◽  
Tati Febrianti ◽  
Dwi Febriyana ◽  
...  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Qingqing Liu ◽  
Jie Yuan ◽  
Maerjiaen Bakeyi ◽  
Jie Li ◽  
Zilong Zhang ◽  
...  

Background. The twin epidemic of overweight/obesity and type 2 diabetes mellitus (T2DM) is a major public health problem globally, especially in China. Overweight/obese adults commonly coexist with T2DM, which is closely related to adverse health outcomes. Therefore, this study aimed to develop risk nomogram of T2DM in Chinese adults with overweight/obesity. Methods. We used prospective cohort study data for 82938 individuals aged ≥20 years free of T2DM collected between 2010 and 2016 and divided them into a training (n = 58056) and a validation set (n = 24882). Using the least absolute shrinkage and selection operator (LASSO) regression model in training set, we identified optimized risk factors of T2DM, followed by the establishment of T2DM prediction nomogram. The discriminative ability, calibration, and clinical usefulness of nomogram were assessed. The results were assessed by internal validation in validation set. Results. Six independent risk factors of T2DM were identified and entered into the nomogram including age, body mass index, fasting plasma glucose, total cholesterol, triglycerides, and family history. The nomogram incorporating these six risk factors showed good discrimination regarding the training set, with a Harrell’s concordance index (C-index) of 0.859 [95% confidence interval (CI): 0.850–0.868] and an area under the receiver operating characteristic curve of 0.862 (95% CI: 0.853–0.871). The calibration curves indicated well agreement between the probability as predicted by the nomogram and the actual probability. Decision curve analysis demonstrated that the prediction nomogram was clinically useful. The consistent of findings was confirmed using the validation set. Conclusions. The nomogram showed accurate prediction for T2DM among Chinese population with overweight and obese and might aid in assessment risk of T2DM.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaomei Chen ◽  
Qiying Xie ◽  
Xiaoxue Zhang ◽  
Qi Lv ◽  
Xin Liu ◽  
...  

Background. This study is aimed at investigating the systemic risk factors of diabetic retinopathy and further establishing a risk prediction model for DR development in T2DM patients. Methods. This is a retrospective cohort study including 330 type 2 diabetes mellitus (T2DM) patients who were followed up from December 2012 to November 2020. Multivariable cox regression analysis identifying factors associated with the hazard of developing diabetic retinopathy (DR) was used to construct the DR risk prediction model in the form of nomogram. Results. 50.6% of participants (mean age: 58.60 ± 10.55 ) were female, and mean duration of diabetes was 7.09 ± 5.36   years . After multivariate cox regression, the risk factors for developing DR were age (HR 1.068, 95%Cl 1.021-1.118, P = 0.005 ), diabetes duration (HR 1.094, 95%Cl 1.018-1.177, P = 0.015 ), HbA1c (HR 1.411, 95%Cl 1.113-1.788, P = 0.004 ), albuminuria (HR 6.908, 95%Cl 1.794-26.599, P = 0.005 ), and triglyceride (HR 1.554, 95%Cl 1.037-2.330, P = 0.033 ). The AUC values of the nomogram for predicting developing DR at 3-, 4-, and 5-year were 0.854, 0.845, and 0.798. Conclusion. Combining age, diabetes duration, HbA1c, albuminuria, and triglyceride, the nomogram model is effective for early recognition and intervention of individuals at high risk of DR development.


BMJ Open ◽  
2016 ◽  
Vol 6 (12) ◽  
pp. e014102 ◽  
Author(s):  
Keren Papier ◽  
Susan Jordan ◽  
Catherine D‘Este ◽  
Chris Bain ◽  
Janya Peungson ◽  
...  

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