丙氨酸转氨酶<2正常上限的慢性乙肝炎抗病毒治疗决策的非

StephenW

A noninvasive model to predict liver histology for antiviral therapy decision in chronic hepatitis B with alanine aminotransferase < 2 upper limit of normal
Shanshan Chen  1   2 , Haijun Huang  3 , Wei Huang  4
Affiliations
Affiliations

    1
    Department of Infectious Disease, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang, China. [email protected].
    2
    Graduate School of Clinical Medicine, Bengbu Medical College, BengbuAnhui, 233000, China. [email protected].
    3
    Department of Infectious Disease, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang, China.
    4
    Department of Digestive Disease, Zhejiang Provincial People's Hospital, Hangzhou, 310014, Zhejiang, China.

    PMID: 33407146 PMCID: PMC7788863 DOI: 10.1186/s12876-020-01576-6

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Abstract

Background: At present, most assessments of liver fibrosis staging mainly focus on non-invasive diagnostic methods. This study aims to construct a noninvasive model to predict liver histology for antiviral therapy in chronic hepatitis B (CHB) with alanine aminotransferase (ALT) < 2 times upper limit of normal (ULN).

Methods: We retrospectively analyzed 577 patients with CHB who received liver biopsy and whose ALT was less than 2 ULN. Then they were randomly divided into a training group and a validation group. Through logistic regression analysis, a novel predictive model was constructed in the training group to predict significant changes in liver histology [necro-inflammatory activity grade (G) ≥ 2 or fibrosis stage (S) ≥ 2] and then validated in the validation group.

Results: If liver biopsy showed moderate or severe inflammation or significant fibrosis, antiviral treatment was recommended. Aspartate aminotransferase (AST), anti-hepatitis B virus core antibody (anti-HBC) and glutamine transpeptidase (GGT) were identified as independent predictors for antiviral therapy, with area under the ROC curve (AUROC) of 0.649, 0.647 and 0.616, respectively. Our novel model index, which combined AST, anti- HBC and GGT with AUROC of 0.700 and 0.742 in training set and validation set.

Conclusions: This study established a noninvasive model to predict liver histology for antiviral treatment decision in patients with CHB with ALT < 2 ULN, which can reduce the clinical needs of liver biopsy.

Keywords: Anti-hepatitis B virus core antibody (anti-HBC); Hepatitis B virus; Liver biopsy; Noninvasive model.

StephenW

丙氨酸转氨酶<2正常上限的慢性乙型肝炎抗病毒治疗决策的非侵入性模型，可预测肝脏组织学
陈珊珊1 2，黄海军军3，黄伟4
隶属关系
隶属关系

    1个
    浙江省人民医院传染病科，浙江杭州310014 [email protected]。
    2
    蚌埠医学院临床医学研究生院，安徽蚌埠233000 [email protected]。
    3
    浙江省人民医院传染病科，浙江杭州310014
    4
    浙江省人民医院消化内科，浙江杭州310014

    PMID：33407146 PMCID：PMC7788863 DOI：10.1186 / s12876-020-01576-6

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抽象

背景：目前，大多数肝纤维化分期的评估主要集中在非侵入性诊断方法上。这项研究旨在构建一个非侵入性模型，预测丙氨酸转氨酶（ALT）<正常上限（ULN）上限的2倍的慢性乙型肝炎（CHB）抗病毒治疗的肝脏组织学。

方法：我们回顾性分析了577例行肝活检且ALT小于2 ULN的CHB患者。然后将他们随机分为训练组和验证组。通过逻辑回归分析，在训练组中构建了一个新的预测模型，以预测肝脏组织学的显着变化[坏死性炎症等级（G）≥2或纤维化阶段（S）≥2]，然后在验证组中进行验证。

结果：如果肝活检显示中度或重度炎症或明显纤维化，则建议抗病毒治疗。天冬氨酸转氨酶（AST），抗乙型肝炎病毒核心抗体（抗HBC）和谷氨酰胺转肽酶（GGT）被确定为抗病毒治疗的独立预测因子，ROC曲线下面积（AUROC）分别为0.649、0.647和0.616。 。我们将训练集和验证集的AST，抗HBC和GGT与AUROC分别为0.700和0.742结合在一起的新颖模型指数。

结论：本研究建立了一种非侵入性模型，以预测ALT <2 ULN的CHB患者的肝组织学抗病毒治疗决策，从而可以减少肝活检的临床需求。

关键词：抗乙肝病毒核心抗体（anti-HBC）；乙型肝炎病毒;肝活检；无创模型。

StephenW

https://bmcgastroenterol.biomedc ... 876-020-01576-6.pdf