文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

评估慢性乙型/丙型肝炎、酒精性肝硬化和非酒精性肝硬化中非侵入性生物标志物的鉴别性能:一项比较分析。

Evaluating the Discriminative Performance of Noninvasive Biomarkers in Chronic Hepatitis B/C, Alcoholic Cirrhosis, and Nonalcoholic Cirrhosis: A Comparative Analysis.

作者信息

Dumitrache Păunescu Alina, Ionescu Șuțan Nicoleta Anca, Țânțu Monica Marilena, Ponepal Maria Cristina, Soare Liliana Cristina, Țânțu Ana Cătălina, Atamanalp Muhammed, Baniță Ileana Monica, Pisoschi Cătălina Gabriela

机构信息

University of Medicine and Pharmacy of Craiova, Petru-Rareș Street No. 2, 200349 Craiova, Romania.

Department of Natural Sciences, National University of Science and Technology Politehnica Bucharest, Piteşti University Centre, 1st Targu din Vale Str., 110040 Pitesti, Romania.

出版信息

Diagnostics (Basel). 2025 Jun 20;15(13):1575. doi: 10.3390/diagnostics15131575.


DOI:10.3390/diagnostics15131575
PMID:40647574
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12248557/
Abstract

The clinical implementation of noninvasive tests for liver fibrosis assessment has attracted increasing attention, particularly for diagnosing advanced fibrosis (≥F3). This observational study aimed to evaluate the stratification accuracy of nine direct and seven indirect biomarkers across four etiologies: chronic hepatitis B (CHB), chronic hepatitis C (CHC), alcoholic liver cirrhosis (ALC), and nonalcoholic liver cirrhosis (NALC). : Our study was conducted on 116 participants, including 96 with chronic liver disease (16 CHB, 15 CHC, 49 ALC, and 16 NALC) and 20 healthy controls. The values of direct (aspartate aminotransferase, alanine aminotransferase, total bilirubin, serum albumin, platelet count, international normalized ratio, gamma-glutamyl transpeptidase, CD5 antigen-like, and transforming growth factor-beta 1) and indirect non-serological biomarkers (De Ritis ratio, albumin-bilirubin score, gamma-glutamyl transpeptidase-to-platelet ratio, aspartate aminotransferase-to-platelet-ratio index, fibrosis-4 index, INR-to-platelet ratio, and fibrosis quotient) were analyzed for their discriminative power in fibrosis stratification. Statistical analyses revealed a significant correlation (0.05 level; two-tailed), and AUC 95% CI ranged within 0.50-1.00 between the direct and indirect biomarker values across all etiologies. Among the evaluated biomarkers, the recorded AUC was 0.998 in CHB for APRI, 0.981 in CHC for FIB-4, and 1.000 in ALC and NALC for APRI and AST, respectively, while CD5L consistently achieved an AUC of 1.000 across all etiologies. These findings suggest that applying a multifactorial approach in liver pathology may improve diagnosis accuracy compared to the use of individual biomarkers and can provide data that may inform the development of clinically applicable mathematical models.

摘要

用于肝纤维化评估的非侵入性检测的临床应用已引起越来越多的关注,尤其是在诊断晚期纤维化(≥F3)方面。这项观察性研究旨在评估九种直接生物标志物和七种间接生物标志物在四种病因中的分层准确性,这四种病因分别为:慢性乙型肝炎(CHB)、慢性丙型肝炎(CHC)、酒精性肝硬化(ALC)和非酒精性肝硬化(NALC)。我们的研究对116名参与者进行,其中包括96名慢性肝病患者(16名CHB、15名CHC、49名ALC和16名NALC)以及20名健康对照者。分析了直接生物标志物(天冬氨酸转氨酶、丙氨酸转氨酶、总胆红素、血清白蛋白、血小板计数、国际标准化比值、γ-谷氨酰转肽酶、CD5抗原样分子和转化生长因子-β1)和间接非血清学生物标志物(德瑞蒂斯比值、白蛋白-胆红素评分、γ-谷氨酰转肽酶与血小板比值、天冬氨酸转氨酶与血小板比值指数、纤维化-4指数、国际标准化比值与血小板比值以及纤维化商数)在纤维化分层中的判别能力。统计分析显示存在显著相关性(0.05水平;双侧),并且在所有病因中,直接和间接生物标志物值之间的AUC 95%置信区间在0.50至1.00范围内。在评估的生物标志物中,CHB中APRI的记录AUC为0.998,CHC中FIB-4的AUC为0.981,ALC和NALC中APRI和AST的AUC分别为1.000,而CD5L在所有病因中始终达到1.000的AUC。这些发现表明,与使用单个生物标志物相比,在肝脏病理学中采用多因素方法可能会提高诊断准确性,并可为临床适用的数学模型的开发提供参考数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/59191539b4e4/diagnostics-15-01575-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/a9e5ab338cb3/diagnostics-15-01575-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/b110ff6cd86a/diagnostics-15-01575-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/0a373ddedf1e/diagnostics-15-01575-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/d37d4b297da3/diagnostics-15-01575-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/7e290cd40999/diagnostics-15-01575-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/fe01af38bbe0/diagnostics-15-01575-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/86f89639e256/diagnostics-15-01575-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/4056da4c311a/diagnostics-15-01575-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/c230b9e11aec/diagnostics-15-01575-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/453c06dfd261/diagnostics-15-01575-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/b1f112f0faad/diagnostics-15-01575-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/536d58347d74/diagnostics-15-01575-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/08befae4141d/diagnostics-15-01575-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/52df96b2c436/diagnostics-15-01575-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/f398337dc12f/diagnostics-15-01575-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/c9227f3a4e36/diagnostics-15-01575-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/db1349b209ee/diagnostics-15-01575-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/16315eda27b8/diagnostics-15-01575-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/f1991e182686/diagnostics-15-01575-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/dde8fca66fba/diagnostics-15-01575-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/59191539b4e4/diagnostics-15-01575-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/a9e5ab338cb3/diagnostics-15-01575-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/b110ff6cd86a/diagnostics-15-01575-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/0a373ddedf1e/diagnostics-15-01575-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/d37d4b297da3/diagnostics-15-01575-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/7e290cd40999/diagnostics-15-01575-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/fe01af38bbe0/diagnostics-15-01575-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/86f89639e256/diagnostics-15-01575-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/4056da4c311a/diagnostics-15-01575-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/c230b9e11aec/diagnostics-15-01575-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/453c06dfd261/diagnostics-15-01575-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/b1f112f0faad/diagnostics-15-01575-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/536d58347d74/diagnostics-15-01575-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/08befae4141d/diagnostics-15-01575-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/52df96b2c436/diagnostics-15-01575-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/f398337dc12f/diagnostics-15-01575-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/c9227f3a4e36/diagnostics-15-01575-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/db1349b209ee/diagnostics-15-01575-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/16315eda27b8/diagnostics-15-01575-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/f1991e182686/diagnostics-15-01575-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/dde8fca66fba/diagnostics-15-01575-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca03/12248557/59191539b4e4/diagnostics-15-01575-g021.jpg

相似文献

[1]
Evaluating the Discriminative Performance of Noninvasive Biomarkers in Chronic Hepatitis B/C, Alcoholic Cirrhosis, and Nonalcoholic Cirrhosis: A Comparative Analysis.

Diagnostics (Basel). 2025-6-20

[2]
Liver fibrosis stage based on the four factors (FIB-4) score or Forns index in adults with chronic hepatitis C.

Cochrane Database Syst Rev. 2024-8-13

[3]
Investigation of Hepatitis C, D, and HIV Seroprevalence and Evaluation of APRI and FIB-4 Scores in HbsAg-Positive Patients.

Viruses. 2025-4-15

[4]
Systematic review with meta-analysis: direct comparisons of biomarkers for the diagnosis of fibrosis in chronic hepatitis C and B.

Aliment Pharmacol Ther. 2016-1

[5]
Transient elastography for diagnosis of stages of hepatic fibrosis and cirrhosis in people with alcoholic liver disease.

Cochrane Database Syst Rev. 2015-1-22

[6]
Comparison of diagnostic accuracy of aspartate aminotransferase to platelet ratio index and fibrosis-4 index for detecting liver fibrosis in adult patients with chronic hepatitis B virus infection: a systemic review and meta-analysis.

Hepatology. 2014-11-24

[7]
Platelet count, spleen length, and platelet count-to-spleen length ratio for the diagnosis of oesophageal varices in people with chronic liver disease or portal vein thrombosis.

Cochrane Database Syst Rev. 2017-4-26

[8]
Adefovir dipivoxil and pegylated interferon alfa-2a for the treatment of chronic hepatitis B: a systematic review and economic evaluation.

Health Technol Assess. 2006-8

[9]
Diagnostic performance of a new algorithm combining simple, non-invasive and inexpensive tests for predicting the presence of advanced liver fibrosis in patients with chronic hepatitis B.

BMC Gastroenterol. 2025-7-1

[10]
Ultrasonography for diagnosis of alcoholic cirrhosis in people with alcoholic liver disease.

Cochrane Database Syst Rev. 2016-3-2

本文引用的文献

[1]
Collagen-targeted PET imaging for progressive experimental lung fibrosis quantification and monitoring of efficacy of anti-fibrotic therapies.

Theranostics. 2025-1-13

[2]
Pleiotropic Action of TGF-Beta in Physiological and Pathological Liver Conditions.

Biomedicines. 2024-4-22

[3]
AASLD Practice Guideline on blood-based noninvasive liver disease assessment of hepatic fibrosis and steatosis.

Hepatology. 2025-1-1

[4]
AST to ALT ratio as a prospective risk predictor for liver cirrhosis in patients with chronic HBV infection.

Eur J Gastroenterol Hepatol. 2024-3-1

[5]
Gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio is a more powerful marker than TyG index for predicting metabolic syndrome in patients with type 2 diabetes mellitus.

Front Endocrinol (Lausanne). 2023

[6]
Resmetirom for nonalcoholic fatty liver disease: a randomized, double-blind, placebo-controlled phase 3 trial.

Nat Med. 2023-11

[7]
Measurement and clinical usefulness of bilirubin in liver disease.

Adv Lab Med. 2021-7-9

[8]
AST/ALT ratio, APRI, and FIB-4 compared to FibroScan for the assessment of liver fibrosis in patients with chronic hepatitis B in Bandar Abbas, Hormozgan, Iran.

BMC Gastroenterol. 2023-5-11

[9]
Serum γ-glutamyltransferase level and incidence risk of metabolic syndrome in community dwelling adults: longitudinal findings over 12 years.

Diabetol Metab Syndr. 2023-2-23

[10]
The ALBI score: From liver function in patients with HCC to a general measure of liver function.

JHEP Rep. 2022-8-18

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索