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ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R
Volume 41 Issue 7
Jul.  2025
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Article Contents

Risk factors and prediction models for primary biliary cholangitis comorbid with Sjögren’s syndrome

DOI: 10.12449/JCH250718
Research funding:

Suzhou Basic Research Pilot Program (SSD2024033);

Suzhou Young Top Talent Program in Healthcare (GSWS2020018)

More Information
  • Corresponding author: WU Jian, wujian001@suda.edu.cn (ORCID: 0000-0001-5165-2306)
  • Received Date: 2025-02-24
  • Accepted Date: 2025-03-17
  • Published Date: 2025-07-25
  •   Objective  To investigate the risk factors associated with the coexistence of Sjögren’s syndrome (SS) in patients with primary biliary cholangitis (PBC), and to develop and compare diagnostic prediction models for the comorbidity of the two conditions.  Methods  A total of 183 patients first diagnosed with PBC at The First Affiliated Hospital of Soochow University from January 2012 to April 2023 were included. They were divided into two groups based on the presence or absence of SS: those with PBC alone(n=96)and those with PBC accompanied by SS(n=87). Clinical manifestations, serological antibody results, and laboratory parameters were compared between the two groups. Continuous data were compared using the t-test or Mann-Whitney U test, while categorical data were compared using the chi-square test. The risk factors for the presence of SS in PBC were identified through a multivariable Logistic regression analysis. Subsequently, an artificial neural network (ANN) model and a multiple logistic regression (MLR) model were constructed to predict the presence of SS in PBS. The receiver operating characteristic curve was plotted in MedCalc, and the area under the curve (AUC) was compared using the Delong test.  Results  Serum IgG level (odds ratio [OR]=1.600, 95% confidence interval [CI]:1.364‍ ‍— ‍‍1.876,P<0.001) was an independent risk factor, while serum total bilirubin level (OR=0.760,95%CI:0.700‍ ‍— ‍‍0.811,P=0.005) was an independent protective factor against the presence of SS in patients with PBC. The AUCs of the ANN model and the MLR model diagnosing SS in PBC were 0.919 (95%CI:0.870‍ ‍— ‍‍0.954) and 0.896 (95%CI:0.843‍ ‍— ‍‍0.936), respectively, both showing good predictive efficacy, and the predictive efficacy of the ANN model was significantly better than that of the MLR model (P=0.019 2).  Conclusion  Patients with PBC complicated by SS usually present at an early stage with mild symptoms during their initial medical consultation, when early diagnosis and treatment are beneficial for their prognosis. For patients with PBC showing high serum IgG levels at the first diagnosis or consultation, SS screening is necessary.

     

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