ORIGINAL RESEARCH article
Front. Nutr.
Sec. Nutrition and Metabolism
Establishment and evaluation of a novel practical tool for the screening of metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus
Provisionally accepted
- 1First Hospital of Lanzhou University, Lanzhou, China
- 2Lanzhou University School of Pharmacy, Lanzhou, China
- 3Lanzhou University Second Hospital, Lanzhou, China
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Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major comorbidity in type 2 diabetes mellitus (T2DM), yet early prediction models tailored to this population are limited. This study aimed to develop and validate a novel diagnostic predictive model for MASLD in adults with T2DM. Methods: A total of 4,726 T2DM patients were retrospectively analyzed. Candidate predictors were screened by least absolute shrinkage and selection operator (LASSO) regression, and a multivariable logistic regression model was built. Significant variables were integrated into a diagnostic predictive nomogram (DPN), with online and Excel-based calculators developed. Model performance was comprehensively evaluated and compared with four established models for fatty liver disease across training, internal, and external (NHANES) validation datasets. Subgroup analyses assessed generalizability. Results: Eight independent predictors (sex, age, body mass index, alanine aminotransferase, albumin, diabetes duration, triglycerides, and high-density lipoprotein cholesterol) were included in the final model. The DPN achieved robust discrimination in training set (AUC: 0.775, 95% CI: 0.759–0.791), validation set (0.767, 95% CI: 0.742–0.791), and test set (0.794, 95% CI: 0.749–0.839) compared to existing models. NRI and IDI confirmed improved predictive capacity (P < 0.05). Calibration curves were excellent in the training (P = 0.936, Brier score = 0.184), validation (P = 0.956, Brier score = 0.189), and test sets (P = 0.687, Brier score = 0.156). DCA and CIC further demonstrated higher clinical net benefit. Subgroup analyses confirmed stability and broad applicability. Conclusions: The DPN is a clinically practical and resource-efficient screening tool that enables early risk stratification for MASLD in patients with T2DM. Its implementation could streamline screening pathways and facilitate timely intervention in routine clinical practice.
Keywords: type 2 diabetes mellitus, Metabolic dysfunction-associated steatotic liver disease, Diagnostic predictive nomogram, NHANES database, clinical practice
Received: 25 Aug 2025; Accepted: 27 Nov 2025.
Copyright: © 2025 Wu, Zhang, Wang and Zhou. 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:
Xin'an Wu
Yan Zhou
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