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World J Hepatol. May 27, 2026; 18(5): 119798
Published online May 27, 2026. doi: 10.4254/wjh.v18.i5.119798
Published online May 27, 2026. doi: 10.4254/wjh.v18.i5.119798
Liver stiffness-platelet ratio index and machine learning models for the noninvasive diagnosis of significant fibrosis in chronic hepatitis B
Jun-Yi Lin, Xian-Qiong Gong, The School of Clinical Medicine, Fujian Medical University, Fuzhou 350122, Fujian Province, China
Jun-Yi Lin, Xian-Qiong Gong, Department of Hepatology and Infectious Disease, Zhongshan Hospital of Xiamen University, Xiamen 361000, Fujian Province, China
Zao-Xiu Ai, Man-Jin Luo, Li-Zhen Su, Ying-Ying Sun, Hong-Tao Yu, Department of Liver Diseases, Xiamen Hospital of TCM, Xiamen 361000, Fujian Province, China
Xin-Gen Gao, Hua-Li Jiang, Ju-Qiang Lin, Hong-Yi Zhang, School of Opto-Electronic and Communication Engineering, Xiamen University of Technology, Xiamen 361000, Fujian Province, China
Li Zhang, Basic Research Laboratory, Chongqing Hospital of Traditional Chinese Medicine, Chongqing 40010, China
Author contributions: Lin JY was responsible for writing original draft; Lin JY, Ai ZX, Luo MJ, Su LZ, Sun YY, and Yu HT were responsible for data curation and investigation; Lin JY, Ai ZX, Su LZ, Gao XG, Jiang HL, Zhang HY, and Zhang L were responsible for formal analysis and validation; Lin JY, Gao XG, Lin JQ, and Zhang HY were responsible for methodology and software; Lin JY and Jiang HL were responsible for visualization; Lin JY and Gong XQ were responsible for conceptualization and methodology; Gao XG and Gong XQ were responsible for funding acquisition; Gong XQ was responsible for supervision, project administration, writing review and editing; all authors have read and approved the final version of the manuscript.
Supported by Fujian Provincial Health Technology Project, No. 2022GGB020; Xiamen Science and Technology Program, No. 3502Z20224020; Traditional Chinese Medicine Foundation of Xiamen, No. XWZY-2023-0610; Xiamen Science and Technology Major Project, No. 3502Z202374113; Natural Science Foundation of Fujian Province, No. 2023J011456 and No. 2023J05084; and Natural Science Foundation of Xiamen, No. 3502Z202373057.
Institutional review board statement: The study protocol was approved by the Medical Ethics Committee of Xiamen Hospital of TCM (No. 2024-k027-01).
Informed consent statement: The requirement for informed consent was waived by the ethics committee due to the retrospective design and anonymization of all patient data, in accordance with the Declaration of Helsinki.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Data sharing statement: All data supporting the findings of this study are included in the Supplementary material or are available from the corresponding author upon reasonable request.
Corresponding author: Xian-Qiong Gong, Chief Physician, The School of Clinical Medicine, Fujian Medical University, No. 88 Jiaotong Road, Taijiang District, Fuzhou 350005, Fujian Province, China. xianqiong-gong@hotmail.com
Received: February 6, 2026
Revised: February 23, 2026
Accepted: April 16, 2026
Published online: May 27, 2026
Processing time: 109 Days and 15.7 Hours
Revised: February 23, 2026
Accepted: April 16, 2026
Published online: May 27, 2026
Processing time: 109 Days and 15.7 Hours
Core Tip
Core Tip: In this biopsy-based retrospective study of 1098 treatment-naïve patients with chronic hepatitis B, a liver stiffness-platelet ratio index, derived from transient elastography and platelet count, showed strong performance in identifying significant fibrosis (S2-S4) relative to conventional noninvasive scores. Liver stiffness-platelet ratio index also provided incremental value in selected machine learning and deep learning models and demonstrated a net benefit in decision curve analysis, supporting its use as a practical first-line triage tool when liver stiffness measurement and platelet count are routinely available.