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Publication Name World Journal of Hepatology
Manuscript ID 119430
Country China
Received
2026-01-28 03:10
Peer-Review Started
2026-01-28 03:10
First Decision by Editorial Office Director
2026-01-30 09:04
Return for Revision
2026-01-30 09:04
Revised
2026-02-04 08:41
Publication Fee Transferred
Second Decision by Editor
2026-03-03 02:36
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2026-03-03 08:40
Articles in Press
2026-03-03 08:40
Edit the Manuscript by Language Editor
Typeset the Manuscript
2026-07-15 09:59
Publish the Manuscript Online
2026-09-17 05:48
ISSN 1948-5182 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright ©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Medicine, Research & Experimental
Manuscript Type Correspondence
Article Title Letter to the Editor: Enhancing fibrosis prediction in metabolic dysfunction-associated steatotic liver disease: The potential of combined biomarker approaches
Manuscript Source Invited Manuscript
All Author List Hai-Sheng Hu, Lin-Shu Xu and Bao-Qing Sun
ORCID
Author(s) ORCID Number
Bao-Qing Sun http://orcid.org/0000-0002-1671-0723
Funding Agency and Grant Number
Corresponding Author Bao-Qing Sun, Professor, Department of Clinical Laboratory, The First Affiliated Hospital of Guangzhou Medical University, No. 28 Qiaozhong Middle Road, Guangzhou 510120, Guangdong Province, China. sunbaoqing@vip.163.com
Key Words Metabolic dysfunction-associated steatotic liver disease; Liver fibrosis; Biomarkers; Diagnostic strategy; Inflammatory indices
Core Tip This letter highlights the limited diagnostic accuracy of conventional markers (e.g., neutrophil-to-lymphocyte ratio and C-reactive protein) for predicting liver fibrosis in metabolic dysfunction-associated steatotic liver disease. To advance precision management, we propose a shift toward an integrated diagnostic paradigm. This strategy combines accessible systemic inflammation indices with novel biomarkers reflecting specific hepatic processes, such as N-terminal propeptide of type III collagen for fibrogenesis, liver-specific microRNAs, and metabolic proteins, such as fatty acid-binding protein 4. Future research should prioritize validating such mechanism-informed combinations to enable multidimensional risk assessment, establish actionable clinical thresholds, and guide personalized monitoring and intervention, ultimately improving prognosis in this heterogeneous patient population.
Publish Date 2026-09-17 05:48
Citation

Hu HS, Xu LS, Sun BQ. Letter to the Editor: Enhancing fibrosis prediction in metabolic dysfunction-associated steatotic liver disease: The potential of combined biomarker approaches. World J Hepatol 2026; 18(9): 119430

URL https://www.wjgnet.com/1948-5182/full/v18/i9/119430.htm
DOI https://doi.org/10.4254/wjh.119430
Full Article (PDF) WJH-18-119430-with-cover.pdf
Manuscript File 119430_Auto_Edited_081946.docx
Answering Reviewers 119430-answering-reviewers.pdf
Audio Core Tip 119430-audio.mp3
Conflict-of-Interest Disclosure Form 119430-conflict-of-interest-statement.pdf
Copyright License Agreement 119430-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate 119430-non-native-speakers.pdf
Peer-review Report 119430-peer-reviews.pdf
Scientific Misconduct Check 119430-scientific-misconduct-check.png
CrossCheck Report 119430-crosscheck-report.pdf