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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Gastroenterol. Jul 7, 2026; 32(25): 119364
Published online Jul 7, 2026. doi: 10.3748/wjg.119364
Novel inflammation-based model for postoperative early recurrence prediction of hepatitis B virus-related hepatocellular carcinoma ≤ 5 cm
Tian-Xing Dai, Jing Li, Hua Li, Guo-Ying Wang
Tian-Xing Dai, Guo-Ying Wang, Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou 510120, Guangdong Province, China
Tian-Xing Dai, Hua Li, Guo-Ying Wang, Department of Hepatic Surgery and Liver Transplant Program, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, Guangdong Province, China
Jing Li, Department of Infectious Diseases, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou 510260, Guangdong Province, China
Co-first authors: Tian-Xing Dai and Jing Li.
Author contributions: Wang GY and Dai TX conceived and designed the analysis; Dai TX and Li J collected the data, handled the visualization, provided the funding support, and wrote the original draft and they contribute equally to this study as co-first authors; Li H and Dai TX contributed data or analysis tools; Wang GY, Dai TX and Li H performed the analysis; all authors reviewed and edited the manuscript.
Supported by National Natural Science Foundation of China, No. 82303859; and the Scientific and Technological Planning Project of Guangzhou City, China, No. 2024A04J3543 and No. 2025A03J4318.
Institutional review board statement: The study was reviewed and approved by the Institutional Review Board of the Third Affiliated Hospital of Sun Yat-sen University (Approval No. 02-057-01).
Informed consent statement: Informed consent was waived by the Institutional Review Board of the Third Affiliated Hospital of Sun Yat-sen University.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: No additional data are available.
Corresponding author: Guo-Ying Wang, PhD, Chief Physician, Professor, Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangzhou Medical University, No. 151 Yanjiangxi Road, Guangzhou 510120, Guangdong Province, China. wanggy3@126.com
Received: January 26, 2026
Revised: February 23, 2026
Accepted: March 10, 2026
Published online: July 7, 2026
Processing time: 156 Days and 9.5 Hours
Abstract
BACKGROUND

Despite surgical treatment, hepatocellular carcinoma (HCC) remains highly recurrent, particularly in hepatitis B virus (HBV)-related cases. The mechanisms of early (≤ 2 years) vs late recurrence differ substantially; however, the inflammation-related divers of early recurrence in HBV-related HCC are poorly defined.

AIM

To construct an inflammation-related score (IRS) model to predict recurrence in HBV-related HCC with tumors ≤ 5 cm.

METHODS

A total of 650 eligible patients with HCC were retrospectively enrolled and randomly divided into the training (n = 390) and validation (n = 260) groups. Univariate, least absolute shrinkage and selection operator Cox analyses were used to identify early recurrence-related inflammation indices and construct an IRS model in the training cohort. An IRS-based nomogram was established and assessed for both cohorts.

RESULTS

Early recurrence accounted for 74.7% (222/297) of all recurrences. Four critical inflammation indices were screened for the IRS model construction. Patients with a high IRS had significantly lower early recurrence-free survival (RFS) than those with a low IRS in both the training and validation cohorts (all P < 0.01). In combination with tumor diameter, number, and microvascular invasion, a novel IRS-based nomogram for predicting early RFS was established. The concordance index was 0.658 in both training and validation cohorts. A high concordance was observed in the calibration curves. The nomogram revealed a better capacity for risk discrimination and clinical usefulness than other staging systems. Finally, patients were classified into different risk groups based on the total points of the nomogram.

CONCLUSION

The integrated IRS model and corresponding nomogram provide good clinical implications for identifying high-risk populations with early recurrence.

Keywords: Hepatocellular carcinoma; Inflammation; Prognostic model; Recurrence-free survival; Nomogram

Core Tip: In patients with hepatitis B virus-related hepatocellular carcinoma with tumors ≤ 5 cm, early recurrence (≤ 2 years) accounted for 74.7% of all recurrences. An inflammation-related score model was developed based on four key indices (glutamyl transpeptidase-to-platelet ratio, prognostic nutritional index, albumin-bilirubin index, and aminotransferase to lymphocyte ratio index), and integrated with clinicopathological factors into a novel nomogram. This model demonstrated superior prognostic accuracy and clinical utility in predicting early recurrence compared to conventional staging systems, and effectively identified high-risk patients with significantly poorer outcomes.

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