Shekar V, Lucke-Wold B. From risk stratification to precision surveillance: Interpreting early-warning models after laparoscopic resection for hepatocellular carcinoma. World J Gastroenterol 2026; 32(31): 118374 [DOI: 10.3748/wjg.118374]
Corresponding Author of This Article
Brandon Lucke-Wold, MD, PhD, Doctor, Lillian S. Wells Department of Neurosurgery, University of Florida, 1505 SW Archer Road, Gainesville, FL 32608, United States. brandon.lucke-wold@neurosurgery.ufl.edu
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Gastroenterology & Hepatology
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review-article
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Shekar V, Lucke-Wold B. From risk stratification to precision surveillance: Interpreting early-warning models after laparoscopic resection for hepatocellular carcinoma. World J Gastroenterol 2026; 32(31): 118374 [DOI: 10.3748/wjg.118374]
World J Gastroenterol. Aug 21, 2026; 32(31): 118374 Published online Aug 21, 2026. doi: 10.3748/wjg.118374
From risk stratification to precision surveillance: Interpreting early-warning models after laparoscopic resection for hepatocellular carcinoma
Veena Shekar, Brandon Lucke-Wold
Veena Shekar, Department of General Medicine, The Oxford Medical College Hospital and Research Centre, Bengaluru 562107, Karnataka, India
Brandon Lucke-Wold, Lillian S. Wells Department of Neurosurgery, University of Florida, Gainesville, FL 32608, United States
Author contributions: Shekar V contributed to conceptualization, manuscript drafting, and critical revision; Lucke-Wold B provided senior supervision, intellectual input, and final approval.
AI contribution statement: The manuscript was conceptualized, written, and critically revised by the authors. During the revision stage, limited AI-assisted tools were used to improve clarity, grammar, and overall readability of the manuscript. No AI tools were used to generate original scientific ideas, interpret results, or draw conclusions. No part of the scientific content, data interpretation, or analytical reasoning in this manuscript was generated or performed using AI tools. All interpretations are based on the authors’ independent academic assessment of the cited literature. The conceptual framework figure and tabulated summary were developed by the authors. AI-assisted tools were used only for formatting and improving visual presentation to meet journal standards. All references were selected by the authors following a structured literature review. AI tools were not used to independently generate references; however, they were occasionally used to assist in formatting and organizing citations.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Corresponding author: Brandon Lucke-Wold, MD, PhD, Doctor, Lillian S. Wells Department of Neurosurgery, University of Florida, 1505 SW Archer Road, Gainesville, FL 32608, United States. brandon.lucke-wold@neurosurgery.ufl.edu
Received: January 4, 2026 Revised: January 16, 2026 Accepted: April 15, 2026 Published online: August 21, 2026 Processing time: 216 Days and 19.3 Hours
Abstract
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with postoperative recurrence representing a major barrier to long-term survival. Advances in minimally invasive surgery, including laparoscopic liver resection, have improved patient outcomes, although early recurrence remains a potential risk. Recent developments in predictive modeling, including least absolute shrinkage and selection operator-based models, have allowed for the incorporation of inflammation, tumor, and hepatic functional reserve factors in personalized risk models. This opinion review aims to evaluate recent developments in early warning models for one-year adverse outcomes in HCC patients undergoing laparoscopic resection. It highlights the biological rationale for tumor-related factors, including alpha-fetoprotein, white blood cell count, tumor invasion, and albumin-bilirubin grade, in early warning models for HCC recurrence. It further discusses potential challenges in validating early warning models, including potential limitations of retrospective model development. It also highlights potential future directions in incorporating artificial intelligence in real-time clinical decision support systems.
Core Tip: This opinion review discusses the clinical implications of a recently published early-warning model predicting one-year adverse outcomes after laparoscopic resection for hepatocellular carcinoma. The model integrates inflammatory markers, tumor burden, and hepatic reserve to support individualized postoperative surveillance and precision management.
