用于预测慢性乙型肝炎患者肝脏炎症的有希望的非侵入性指

StephenW

Exp Ther Med. 2018 Dec;16(6):4393-4400. doi: 10.3892/etm.2018.6751. Epub 2018 Sep 18.
A promising non-invasive index for predicting liver inflammation in chronic hepatitis B patients with alanine aminotransferase ≤2 upper limit of normal.
Yu XP1, Wen X1,2, Li J1, Zheng YJ3, Long JF4, Zhao WD5, Jiang PX1, Wu JW1, Zhu BD1, Jiang QR1, Yang FF1, Shen ZL1, Mao RC1, Su ZJ3, Zhang JM1.
Author information

1
    Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai 200032, P.R. China.
2
    Department of Infectious Diseases, Jing'an District Centre Hospital of Shanghai (Huashan Hospital Affiliated to Fudan University Jing'an Branch), Shanghai 200032, P.R. China.
3
    Department of Infectious Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China.
4
    Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai 200032, P.R. China.
5
    Department of Laboratory Medicine, Clinical Medicine College, Dali University, Dali, Yunnan 671000, P.R. China.

Abstract

Inexpensive and simple non-invasive indexes for predicting liver inflammation are urgently required, but have been poorly studied in chronic hepatitis B (CHB) patients with alanine transaminase (ALT) ≤2 times the upper limit of normal (ULN). A total of 356 CHB patients with ALT ≤2 ULN who presented at Huashan Hospital (n=181) and the First Hospital of Quanzhou (n=175) were enrolled and randomly divided into an experimental assessment cohort (n=238) and validation cohort (n=118) at a ratio of 2:1. Histological analysis of liver tissue was performed to determine the pathological stage according to the Scheuer scoring system. For the experimental assessment cohort, univariate and multivariate analysis identified aspartate aminotransferase (AST) and albumin (ALB) as independent predictors of liver necroinflammation [liver necroinflammation grade (G)≥2] in patients with ALT ≤2 ULN. Therefore, a novel index, the AST-to-ALB ratio (ATAR), was proposed, which had a better diagnostic performance [area under receiver operating characteristic curve (AUC)=0.721] than that of ALB (AUC=0.632; P=0.039 vs. ATAR) and AST (AUC=0.682; P=0.082 vs. ATAR). In the validation cohort, the AUC of ATAR (0.728) to identify patients with a G≥2 was slightly greater than that of AST (0.660; P=0.149 vs. ATAR) and ALB (0.672; P=0.282 vs. ATAR). Furthermore, a similar diagnostic superiority was also demonstrated in patients with ALT ≤1 ULN. Thus, ATAR may be a promising non-invasive surrogate marker for liver necroinflammation CHB patients with ALT ≤2 ULN and thereby determine whether anti-viral treatment should be initiated.
KEYWORDS:

anti-viral therapy; chronic hepatitis B; diagnosis; hepatic necroinflammation; model

PMID:
    30542389
PMCID:
    PMC6257632
DOI:
    10.3892/etm.2018.6751

StephenW

Exp Ther Med。 2018年12月; 16（6）：4393-4400。 doi：10.3892 / etm.2018.6751。 Epub 2018年9月18日。
用于预测慢性乙型肝炎患者肝脏炎症的有希望的非侵入性指数，丙氨酸氨基转移酶≤2正常上限。
Yu XP1，Wen X1,2，Li J1，Zheng YJ3，Long JF4，Zhao WD5，Jiang PX1，Wu JW1，Zhu BD1，Jiang QR1，Yang FF1，Shen ZL1，Mao RC1，Su ZJ3，Zhang JM1。
作者信息

1
    复旦大学附属华山医院感染科，上海200032，中国。
2
    上海市静安区中心医院感染科（复旦大学静安分院附属华山医院），上海200032，中国。
3
    福建医科大学附属泉州市第一医院感染科，福建泉州362000，中国。
4
    复旦大学附属华山医院药剂科，上海200032，中国。
五
    大理学院临床医学院检验医学系，云南大理671000，中国。

抽象

迫切需要用于预测肝脏炎症的廉价且简单的非侵入性指标，但是在丙氨酸转氨酶（ALT）≤正常上限（ULN）的2倍的慢性乙型肝炎（CHB）患者中研究较少。招募了356名患有ALT≤2ULN的CHB患者，他们在华山医院（n = 181）和泉州市第一医院（n = 175）就诊，随机分为实验评估队列（n = 238）和验证队列（n = 118），比例为2：1。根据Scheuer评分系统进行肝组织的组织学分析以确定病理阶段。对于实验评估队列，单变量和多变量分析确定天冬氨酸氨基转移酶（AST）和白蛋白（ALB）是ALT≤2ULN患者肝脏坏死性炎症[肝脏坏死性炎症等级（G）≥2]的独立预测因子。因此，提出了一种新的指标AST-ALB比（ATAR），其具有比ALB更好的诊断性能[接收器工作特征曲线下面积（AUC）= 0.721]（AUC = 0.632; P = 0.039对比ATAR）和AST（AUC = 0.682; P = 0.082对ATAR）。在验证组中，鉴定G≥2的患者的ATAR的AUC（0.728）略大于AST（0.660; P = 0.149对比ATAR）和ALB（0.672; P = 0.282对比ATAR）。此外，在ALT≤1ULN的患者中也证实了类似的诊断优势。因此，ATAR可能是ALT≤2ULN的肝脏坏死性炎症CHB患者的有前途的非侵入性替代指标，从而确定是否应该开始抗病毒治疗。
关键词：

抗病毒治疗;慢性乙型肝炎;诊断;肝脏坏死性炎症;模型

结论：
    30542389
PMCID：
    PMC6257632
DOI：
    10.3892 / etm.2018.6751

StephenW

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6257632/