ORIGINAL RESEARCH article
Front. Nutr.
Sec. Nutrition and Metabolism
Volume 12 - 2025 | doi: 10.3389/fnut.2025.1605841
This article is part of the Research TopicNutrient Metabolism and Complications of Type 2 Diabetes MellitusView all 11 articles
Development and Validation of a Predictive Nomogram for Differentiating Diabetic Nephropathy from Non-Diabetic Nephropathy in Patients with T2DM: a multicenter study
Provisionally accepted
Zishan Lin1
Tao Hong1
Wenfeng Wang1Shidong Xie1Caiming Chen1
Feng Yang1Dewen Jiang1
Jianxin Wan1Zugang Xie2Yanfang Xu1*- 1Fujian Medical University, Fuzhou, China
- 2Longyan People's Hospital, Longyan, Fujian Province, China
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Type 2 Diabetes Mellitus (T2DM) significantly exacerbates the global health burden, with diabetic nephropathy (DN) emerging as one of the most common causes of chronic kidney disease. In T2DM patients with kidney disease, it is particularly important to distinguish DN from non-diabetic nephropathy (NDN), as treatment strategies differ markedly. However, the gold standard, renal biopsy, is often impractical due to its invasive nature. This multicenter study aims to develop a non-invasive diagnostic model to distinguish DN from NDN in T2DM patients.From January 2014 to December 2023, patients undergoing percutaneous renal biopsies at three hospitals in Fujian were enrolled. The model was formulated using logistic regression analysis based on clinical and laboratory parameters. A visual predictive nomogram was developed and subsequently evaluated for its predictive performance.A total of 292 patients were included, with 164 diagnosed with DN and 128 with NDN. Diabetic retinopathy, duration of diabetes, HbA1c, systolic blood pressure, neutrophil-to-lymphocyte ratio, kidney volume, triglycerides, estimated glomerular filtration rate, and urinary red blood cell count were identified as independent predictors of DN. A nomogram was then constructed. The model demonstrated high diagnostic accuracy with an AUC of 0.941, validated by an independent cohort yielding an AUC of 0.923. Calibration curves showed good agreement between predicted and actual outcomes, and decision curve analysis confirmed notable clinical utility.The developed model offers a non-invasive, reliable alternative to renal biopsy for distinguishing between DN and NDN in T2DM patients. This tool proves especially valuable in clinical settings where renal biopsy is impractical, helping guide more appropriate treatment decisions.
Keywords: type 2 diabetes mellitus, diabetic nephropathy, Diagnostic model, nomogram, Triglerycide
Received: 04 Apr 2025; Accepted: 06 May 2025.
Copyright: © 2025 Lin, Hong, Wang, Xie, Chen, Yang, Jiang, Wan, Xie and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yanfang Xu, Fujian Medical University, Fuzhou, China
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