Nomogram for the prediction of diabetic nephropathy risk among patients with type 2 diabetes mellitus based on a questionnaire and biochemical indicators: a retrospective study

Abstract

Purpose: Develop a diabetic nephropathy incidence risk nomogram in a Chinese population with type 2 diabetes mellitus. Results: Predictors included systolic blood pressure, diastolic blood pressure, fasting blood glucose, glycosylated hemoglobin A1c, total triglycerides, serum creatinine, blood urea nitrogen and body mass index. The model displayed medium predictive power with a C-index of 0.744 and an area under curve of 0.744. Internal verification of C-index reached 0.737. The decision curve analysis showed the risk threshold was 20%. The value of net reclassification improvement and integrated discrimination improvement were 0.131, 0.05, and that the nomogram could be applied in clinical practice. Conclusion: Diabetic nephropathy incidence risk nomogram incorporating 8 features is useful to predict diabetic nephropathy incidence risk in type 2 diabetes mellitus patients. Methods: Questionnaires, physical examinations and biochemical tests were performed on 3489 T2DM patients in six communities in Shanghai. LASSO regression was used to optimize feature selection by running cyclic coordinate descent. Logistic regression analysis was applied to build a prediction model incorporating the selected features. The C-index, calibration plot, curve analysis, forest plot, net reclassification improvement, integrated discrimination improvement and internal validation were used to validate the discrimination, calibration and clinical usefulness of the model.

A Nomogram Model that Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Retrospective Study

“…Data from a community-based study conducted by the Jiangsu Center for Disease Control and Prevention in 2013 indicated that high levels of SCr are strongly related to increased DN incidence risk among T2DM individuals [ 23 ]. Similarly, another retrospective study has reported that BUN and SCr levels are positively correlated with DN risk in T2DM patients [ 10 ]. In this study, the results of the logistic regression analysis also support the finding that levels of BUN and SCr are strongly associated with a higher risk of DN in patients with T2DM.…”

“…Our study is the first to build a nomogram model that includes inflammation-related indicators, such as NLR and RDW, in predicting the incidence risk of DN among T2DM patients. Hu et al [ 10 ] constructed a nomogram model to predict DN incidence risk, and the C-index of their nomogram was 0.744. Similarly, Jiang et al [ 35 ] established a prognostic nomogram to estimate renal prognosis in DN patients, and the C-index of the model was 0.79.…”

Effect of probiotics on oxidative stress and inflammatory status in diabetic nephropathy: A systematic review and meta-analysis of clinical trials

“…Diabetic nephropathy (DN) is characterized by albuminuria (>300 mg/day) and a reduced Glomerular Filtration Rate (GFR) [ 1 ]; it is the leading cause of the End-Stage Renal Disease (ESRD) worldwide. The incidence of DN in patients with Type 2 Diabetes Mellitus (T2DM) is 20–40% [ 2 ]. Thickening of the glomerular basement membrane, glomerulosclerosis, and expansion of the mesangial cells lead to kidney fibrosis in DN, however, the exact mechanisms implicated in the pathogenesis of DN are complex [ 3 ].…”

Predicting the Failure Risk of Internal Fixation Devices in Chinese Patients Undergoing Spinal Internal Fixation Surgery: Development and Assessment of a New Predictive Nomogram

“…The least absolute shrinkage and selection operator (LASSO) method is suitable for the reduction of high-dimensional data for selecting risk factors with the best predictive features from patients undergoing spinal internal fixation surgery. The features with nonzero coefficients in the LASSO regression model were selected [ 16 , 17 ]. Then, based on the selected features of the model, a prediction model was constructed using multivariate logistic regression analysis.…”