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

Abstract

Objective. To construct a novel nomogram model that predicts the risk of diabetic nephropathy (DN) incidence in Chinese patients with type 2 diabetes mellitus (T2DM). Methods. Questionnaire surveys, physical examinations, routine blood tests, and biochemical index evaluations were conducted on 1095 patients with T2DM from Guilin. A least absolute contraction selection operator (LASSO) regression and multivariable logistic regression analysis were used to screen out DN risk factors. A logistic regression analysis incorporating the screened risk factors was used to establish a predictive nomogram model. The performance of the nomogram model was evaluated using the C-index, an area under the receiver operating characteristic curve (AUC), calibration plots, and a decision curve analysis. Bootstrapping was applied for internal validation. Results. Independent predictors for DN incidence risk included gender, age, hypertension, medicine use, duration of diabetes, body mass index, blood urea nitrogen level, serum creatinine level, neutrophil to lymphocyte ratio, and red blood cell distribution width. The nomogram model exhibited moderate prediction ability with a C-index of 0.819 (95% confidence interval (CI): 0.783–0.853) and an AUC of 0.813 (95%CI: 0.778–0.848). The C-index from internal validation reached 0.796 (95%CI: 0.763–0.829). The decision curve analysis displayed that the DN risk nomogram was clinically applicable when the risk threshold was between 1 and 83%. Conclusion. Our novel and simple nomogram containing 10 factors may be useful in predicting DN incidence risk in T2DM patients.

Development and Validation of a Model That Predicts the Risk of Diabetic Nephropathy in Type 2 Diabetes Mellitus Patients: A Cross-Sectional Study

“… 29 , 30 A retrospective study conducted in Guilin, China, found that BUN was strongly associated with an increased risk of DN in patients with type 2 DM and found that increased Scr levels also increased the risk of DN progression. 31 Our result confirms that BUN and Scr are risk factors for DN in T2DM patients. This is similar to the results of previous studies, suggesting that BUN and Scr are risk factors for DN.…”

Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis

“…The most contributions came from scholars in Jiangsu Province, with a total of seven studies ( 18 , 20 , 28 , 30 , 38 , 40 , 41 ). The earliest studies were published in 2017 ( 35 , 40 ), and there were 23 studies published in the last three years ( 18 , 20 , 21 , 23 – 32 , 35 , 37 – 39 , 41 , 43 , 45 , 46 ). In terms of study types, there were 10 case–control studies ( 16 , 17 , 21 , 24 , 25 , 30 , 33 , 36 , 45 , 47 ), 5 cross-sectional studies ( 19 , 22 , 34 , 35 , 39 ), and 16 cohort studies ( 18 , 20 , 23 , 27 – 29 , 31 , 32 , 37 , 38 , 40 , 41 , 43 , 44 , 46 , 47 ).…”

“…Sixteen studies ( 20 , 23 , 24 , 27 , 31 – 34 , 36 – 38 , 40 , 42 , 44 , 45 , 47 ) consider hypertension a predictive factor for the risk of diabetic nephropathy in patients with type 2 diabetes. Sustained high blood pressure increases the burden on the kidneys.…”

“…Ten studies ( 17 , 19 , 22 – 25 , 27 , 44 , 45 , 47 ) have identified the duration of diabetes as a predictive factor for the risk of diabetic nephropathy in patients with type 2 diabetes. The duration of diabetes is a major factor in the occurrence of microvascular complications.…”

Development and assessment of diabetic nephropathy prediction model using hub genes identified by weighted correlation network analysis

“…The area under the ROC curve (AUC) was 0.813, and the C index of internal verification was 0.796. Decision curve analysis showed the risk profile of DN was clinically appropriate when the risk threshold ranged from 1% to 83% [ 25 ]. These two studies show that nomograms play a certain role in the risk assessment of DN.…”