Christofoli de Barros I, Vanzin Fernandes M, Rodríguez Villafuerte S, Brandão ABM. Explant-based prognostic models for hepatocellular carcinoma recurrence after liver transplantation: A systematic review and meta-analysis. World J Hepatol 2025; 17(9): 111126 [DOI: 10.4254/wjh.v17.i9.111126]
Corresponding Author of This Article
Santiago Rodríguez Villafuerte, PhD, Associate Professor, Directorate of Postgraduate Studies in Health Sciences, Universidad de las Américas, Vía a Nayón, Quito 170124, Pichincha, Ecuador. santy_rodri03@yahoo.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Meta-Analysis
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Hepatol. Sep 27, 2025; 17(9): 111126 Published online Sep 27, 2025. doi: 10.4254/wjh.v17.i9.111126
Explant-based prognostic models for hepatocellular carcinoma recurrence after liver transplantation: A systematic review and meta-analysis
Iago Christofoli de Barros, Matheus Vanzin Fernandes, Santiago Rodríguez Villafuerte, Ajacio Bandeira de Mello Brandão
Iago Christofoli de Barros, Matheus Vanzin Fernandes, Ajacio Bandeira de Mello Brandão, Graduate Program in Hepatology, School of Medicine, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre 90050-170, Rio Grande do Sul, Brazil
Santiago Rodríguez Villafuerte, Directorate of Postgraduate Studies in Health Sciences, Universidad de las Américas, Quito 170124, Pichincha, Ecuador
Santiago Rodríguez Villafuerte, Department of Hepatology, Hospital Vozandes, Quito 170521, Pichincha, Ecuador
Co-first authors: Iago Christofoli de Barros and Matheus Vanzin Fernandes.
Author contributions: Christofoli de Barros I was responsible for conceptualization, data curation, writing original draft, writing review and editing; Vanzin Fernandes M was responsible for curation of data, analysis and interpretation of data, critical revision of the manuscript for important intellectual content; Rodríguez Villafuerte S was responsible for curation of data, analysis and interpretation of data, critical revision of the manuscript for important intellectual content; Brandão ABM was responsible for curation of data, analysis and interpretation of data, critical revision of the manuscript for important intellectual content; all of the authors read and approved the final version of the manuscript to be published.
Conflict-of-interest statement: The authors declare no conflicts of interest related to this work.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
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/
Corresponding author: Santiago Rodríguez Villafuerte, PhD, Associate Professor, Directorate of Postgraduate Studies in Health Sciences, Universidad de las Américas, Vía a Nayón, Quito 170124, Pichincha, Ecuador. santy_rodri03@yahoo.com
Received: June 24, 2025 Revised: July 10, 2025 Accepted: August 21, 2025 Published online: September 27, 2025 Processing time: 94 Days and 1.5 Hours
Abstract
BACKGROUND
Liver transplantation (LT) is the preferred curative treatment for early-stage hepatocellular carcinoma (HCC). However, approximately 17% of patients experience post-transplant recurrence. Extrahepatic recurrence and early recurrence (within one year after LT) are associated with poorer post-recurrence survival.
AIM
To assess which explant-based prognostic model best predicts HCC recurrence after LT.
METHODS
A systematic search was performed in PubMed, EMBASE, Web of Science, and the Cochrane Library from inception to January 30, 2025. Nine retrospective studies comprising 5348 patients were included. Three explant-based prognostic models were analyzed: (1) Risk estimation of tumor recurrence after transplant (RETREAT); (2) Decaens; and (3) Predicting Cancer Recurrence Score (PCRS). Primary outcomes included: (1) HCC recurrence rate; and (2) Predictive accuracy of each score over a five-year follow-up.
RESULTS
All studies were retrospective and included validation cohorts from North America, Europe, and Asia. The overall recurrence rate was 7%. For high-risk thresholds, pooled sensitivity and specificity were Risk Estimation of Tumor Recurrence after Transplant (RETREAT) ≥ 5 (0.381/0.953), Decaens ≥ 4 (0.676/0.817), and PCRS ≥ 3 (0.217/0.987). Among high-risk patients, recurrence reached 45% (95%CI: 35.1-57.0). Area under the curve comparisons showed no statistically significant differences among models. Thus, no model demonstrated clear superiority.
CONCLUSION
Although several explant-based models exist, their limited sensitivity suggests that many patients at risk of recurrence remain unidentified. The RETREAT score, developed in a large cohort, remains the most extensively validated. Future approaches should focus on developing improved prognostic tools using larger, preferably prospective datasets, and integrating artificial intelligence to enhance risk stratification and post-transplant surveillance.
Core Tip: This systematic review and meta-analysis assessed the prognostic accuracy of three explant-based models-Risk Estimation of Tumor Recurrence after Transplant (RETREAT), Decaens, and Predicting Cancer Recurrence Score-in predicting hepatocellular carcinoma recurrence after liver transplantation. Analyzing nine retrospective studies with 5348 patients, recurrence was 7%, with no significant differences in area under the curve among models. While RETREAT is the most validated, all models demonstrated limited sensitivity, risking underestimation of recurrence risk. The findings highlight the need for improved prognostic tools, potentially through incorporating larger, prospective datasets and artificial intelligence, to enhance risk stratification, guide post-transplant surveillance, and optimize patient outcomes.
