What type of study is this?

This is a Systematic Review study (also classified as: Meta-Analysis).

September 27, 2025

Explant-based prognostic models for hepatocellular carcinoma recurrence after liver transplantation: A systematic review and meta-analysis

Puntos clave

The overall recurrence rate for hepatocellular carcinoma after liver transplantation was found to be 7%, indicating ongoing risk post-surgery.
For the RETREAT, Decaens, and PCRS models, sensitivity and specificity varied, highlighting the challenging nature of accurately predicting outcomes.
All included studies were retrospective, encompassing nine cohorts across North America, Europe, and Asia, stressing the need for diverse validation.
Despite multiple models being assessed, no single approach showed clear superiority, suggesting further development is needed.

Resumen

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.

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