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ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 42 Issue 9
Sep.  2026
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Article Contents

Value of serum adiponectin, retinol-binding protein 4, and neutrophil-to-lymphocyte ratio in the diagnosis of metabolic dysfunction-associated steatohepatitis

DOI: 10.12449/JCH260913
Research funding:

Shanxi Basic Research Project (202303021221198)

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  • Corresponding author: Guo Jianjin, 15135184838@139.com (ORCID: 0009-0008-7473-1371)
  • Received Date: 2026-02-10
  • Accepted Date: 2026-04-28
  • Published Date: 2026-09-25
  •   Objective  To investigate the value of serum adiponectin (ADPN), retinol-binding protein 4 (RBP4), and neutrophil-to-lymphocyte ratio (NLR) in assessing metabolic dysfunction-associated steatohepatitis (MASH), and to provide a reference for clinical prevention.  Methods  A total of 298 patients with metabolic dysfunction-associated fatty liver disease (MAFLD) who attended The Third Hospital of Shanxi Medical University from January 2023 to January 2025 were enrolled as subjects. A Logistic regression analysis was used to investigate the predictive factors for MASH, and R language rms package was used to construct a nomogram. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were used to evaluate model accuracy and practicality, and a Pearson correlation analysis was used to investigate the correlation between various indicators. The chi-square test was used for comparison of categorical data between groups; the independent-samples t test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups.  Results  A total of 298 MAFLD patients were enrolled, among whom there were 95 patients with MASH and 203 patients with simple steatosis. The multivariate Logistic regression analysis showed that alanine aminotransferase (ALT), alkaline phosphatase (ALP), RBP4, ADPN, and NLR were independent influencing factors for MASH (all P<0.05). A nomogram model was constructed based on the above factors, and the ROC curve analysis showed that the model had an area under the ROC curve of 0.985 (95% confidence interval: 0.976 — 0.995), with a sensitivity of 0.968 and a specificity of 0.901. The calibration curve analysis showed no significant difference between the predicted and actual probabilities based on the Hosmer-Lemeshow goodness-of-fit test (χ2=2.905, P=0.940), suggesting that the model had good fit and high predictive accuracy. The decision curve analysis showed that the model achieved net benefit when the risk threshold was >0.05. The Pearson correlation analysis showed that in MASH patients, serum RBP4 was negatively correlated with ADPN (r=-0.275, P<0.001) and was positively correlated with NLR (r=0.282, P<0.001), and ADPN was negatively correlated with NLR (r=-0.221, P<0.001).  Conclusion  ALT, ALP, RBP4, ADPN, and NLR are independent influencing factors for MASH. It is necessary in clinical practice to enhance monitoring, identify high-risk patients as early as possible, and provide timely intervention, so as to reduce the incidence rate of MASH and the risk of disease progression.

     

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