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Development and validation of a noninvasive prediction model for significant hepatic liver fibrosis in Chinese patients with autoimmune hepatitis.
Chen, Hanzhu; Ren, Wenya; Yang, Xingdi; Hu, Piao; Wang, Shouhao; Xu, Chengan; Lv, Fei; Zhao, Yue; Yin, Qiaoqiao; Zheng, Wei; Xu, Jing; Pan, Hongying.
Afiliação
  • Chen H; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, PR China; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 3
  • Ren W; The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, PR China; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 3
  • Yang X; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China.
  • Hu P; The First People's Hospital of Xiaoshan District, Xiaoshan First Affiliated Hospital of Wenzhou Medical University, Hangzhou 311200 Zhejiang, PR China.
  • Wang S; Hepatology Diagnosis and Treatment Center, The First Affiliated Hospital of Wenzhou Medical University & Zhejiang Provincial Key Laboratory for Accurate Diagnosis and Treatment of Chronic Liver Diseases, Wenzhou, Zhejiang 325035, PR China.
  • Xu C; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China.
  • Lv F; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China.
  • Zhao Y; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China.
  • Yin Q; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China.
  • Zheng W; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China.
  • Xu J; Hepatology Department II, Affiliated Hangzhou Xixi Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310023, PR China. Electronic address: xukeren@163.com.
  • Pan H; Center for General Practice Medicine, Department of Infectious Diseases, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang 310014, PR China. Electronic address: hypanzjsrmyy@126.com.
Ann Hepatol ; 29(3): 101287, 2024.
Article em En | MEDLINE | ID: mdl-38266674
ABSTRACT
INTRODUCTION AND

OBJECTIVES:

Autoimmune hepatitis (AIH) is a prevalent noninfectious liver disease. However, there is currently a lack of noninvasive tests appropriate for evaluating liver fibrosis in AIH patients. The objective of this study was to develop and validate a predictive model for noninvasive assessment of significant liver fibrosis (S ≥ 2) in patients to provide a reliable method for evaluating liver fibrosis in individuals with AIH. MATERIALS AND

METHODS:

The clinical data of 374 AIH patients were analyzed. A prediction model was established through logistic regression in the training set, and bootstrap method was used to validate the models internally. In addition, the clinical data of 109 AIH patients were collected for external verification of the model.The model was expressed as a nomogram, and area under the curve (AUC) of the receiver operating characteristic (ROC), calibration curve, and decision curve analysis were used to evaluate the accuracy of the prediction model.

RESULTS:

Logistic regression analysis revealed that age, platelet count (PLT), and the A/G ratio were identified as independent risk factors for liver fibrosis in AIH patients (P < 0.05). The diagnostic model that was composed of age, PLT and A/G was superior to APRI and FIB-4 in both the internal validation (0.872, 95%CI 0.819-0.924) and external validation (0.829, 95%CI 0.753-0.904).

CONCLUSIONS:

Our predictive model can predict significant liver fibrosis in AIH patients more accurately, simply, and noninvasively.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Valor Preditivo dos Testes / Curva ROC / Hepatite Autoimune / Nomogramas / Cirrose Hepática Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Ann Hepatol Assunto da revista: GASTROENTEROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de publicação: México
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Valor Preditivo dos Testes / Curva ROC / Hepatite Autoimune / Nomogramas / Cirrose Hepática Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: Asia Idioma: En Revista: Ann Hepatol Assunto da revista: GASTROENTEROLOGIA Ano de publicação: 2024 Tipo de documento: Article País de publicação: México