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quantitative hepatitis b core antibody and quantitative hepatitis b surface antigen:Novel viral biomarkers for chronic hepatitis b management

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World Journal of Hepatology 2024年第4期16卷 550-565页

作者： Wattana Leowattana Pathomthep Leowattana Tawithep Leowattana Department of Clinical Tropical Medicine Mahidol UniversityRachatawee 10400BangkokThailand Department of Medicine Srinakharinwirot UniversityWattana 10110BangkokThailand

The management of hepatitis b virus(HbV)infection now involves regular and appropriate monitoring of viral activity,disease progression,and treatment *** HbV infection biomarkers are limited in their ability to predict clinical outcomes or therapeutic *** of HbV core antibodies(qAnti-Hbc)is a novel non-invasive biomarker that may help with a variety of diagnostic *** was shown to correlate strongly with infection stages,hepatic inflammation and fibrosis,chronic infection exacerbations,and the presence of occult ***,qAnti-Hbc levels were shown to be predictive of spontaneous or treatment-induced HbeAg and HbsAg seroclearance,relapse after medication termination,re-infection following liver transplantation,and viral reactivation in the presence of ***-Hbc,on the other hand,cannot be relied on as a single diagnostic test to address all problems,and its diagnostic and prognostic potential may be greatly increased when paired with *** qAnti-Hbc diagnostic kits are currently not widely *** many methodologies are only semi-quantitative,comparing data from various studies and defining universal cut-off values remains *** review focuses on the clinical utility of qAnti-Hbc and qHbsAg in chronic hepatitis b management.

关键词： quantitative hepatitis b core antibody quantitative hepatitis b surface antigen Chronic hepatitis b management Novels viral biomarkers

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Prediction of hepatic inflammation in chronic hepatitis b patients with a random forest-backward feature elimination algorithm

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World Journal of Gastroenterology 2021年第21期27卷 2910-2920页

作者： Ji-Yuan Zhou Liu-Wei Song Rong Yuan Xiao-Ping Lu Gui-Qiang Wang Department of Gastroenterology The Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510260Guangdong ProvinceChina School of Public Health Xiamen UniversityXiamen 361005Fujian ProvinceChina Intervention and Cell Therapy Center Peking University Shenzhen HospitalShenzhen 518036Guangdong ProvinceChina Department of Infectious Disease Peking University First HospitalBeijing 100034China

bACKGROUND Persistent liver inflammatory damage is the main risk factor for developing liver fibrosis,cirrhosis,and even hepatocellular carcinoma in chronic hepatitis b(CHb)***,accurate prediction of the degree of liver inflammation is a high priority and a growing medical *** To build an effective and robust non-invasive model for predicting hepatitis brelated hepatic *** A total of 650 treatment-naïve CHb(402 HbeAg-positive and 248 HbeAgnegative)patients who underwent liver biopsy were enrolled in this *** inflammation grading was assessed by the Ishak scoring *** quantitative hepatitis b core antibody(qAnti-Hbc)levels and 21 immunerelated inflammatory factors were measured quantitatively using a chemiluminescent microparticle immunoassay.A backward feature elimination(bFE)algorithm utilizing random forest(RF)was used to select optional features and construct a combined *** diagnostic abilities of the model or variables were evaluated based on the estimated area under the receiver operating characteristics curve(AUROC)and compared using the DeLong *** Four features were selected to predict moderate-to-severe inflammation in CHb patients using the RF-bFE *** predictive features included qAnti-Hbc,ALT,AST,and ***’s correlation analysis indicated that serum qAnti-Hbc,ALT,AST,and CXCL11 levels were positively correlated with the histology activity index(HAI)*** selected features were incorporated into the model to establish a novel model named I-3A *** AUROC[0.822;95%confidence interval(CI):0.790-0.851]of the I-3A index was significantly increased compared with qAnti-Hbc alone(0.760,95%CI:0.724-0.792,Pb *** use of an I-3A index cutoff value of 0.41 produced a sensitivity of 69.17%,specificity of 81.44%,and accuracy of 73.8%.Additionally,the I-3A index showed significantly improved diagnostic performance for predicting moderate-to-severe i

关键词： Hepatic inflammation Machine learning quantitative hepatitis b core antibody CXCL11 Diagnostic efficiency

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