Related Experiment Video
Updated: Feb 16, 2026

A Hepatocellular Cancer Patient-Derived Organoid Xenograft Model to Investigate Impact of Liver Regeneration on Tumor Growth
Published on: February 2, 2024
Value of HCC-MELD Score in Patients With Hepatocellular Carcinoma Undergoing Liver Transplantation
Gian Piero Guerrini1, Domenico Pinelli2, Elena Marini2
11 General and oncological surgery Unit, Department of Surgical Oncology, National Cancer institute, Centro di Riferimento Oncologico IRCCS, Aviano, Italy.
Context:
Liver transplantation (LT) is considered the ideal therapy for patients with hepatocellular carcinoma (HCC) having cirrhosis but the shortage of liver donors and the risk of dropout from the wait list due to tumor progression severely limit transplantation. A new prognostic score, the HCC-model for end-stage liver disease (HCC-MELD), was developed by combining α-fetoprotein (AFP), MELD, and tumor size, to improve risk stratification of dropout in patients with HCC.
Objectives:
In this study, we investigated the ability of the HCC-MELD score in predicting the posttransplant for patients fulfilling Milan criteria (MC).
Design:
Two hundred patients with stage II tumor were retrospectively reviewed from a total of 1290 transplants performed at our institution from October 1997 through April 2015. Cox regression analysis was performed to identify the prognostic factors impacting the posttransplant survival.
Results:
Overall survival at 1, 5, and 10 years was 89.3%, 71.1%, and 67.2%, whereas disease-free survival was 86.4%, 66.5%, and 52.4%, respectively. Multivariate analysis showed HCC-MELD score (hazard ratio [HR] 39.6, P < .001) and microvascular invasion (HR 2.41, P = .002) to be independent risk factors for recurrence, whereas HCC diameter (HR 1.15, P = .041), HCC-MELD (HR 15.611, P = .006), and grading (HR 2.17, P = .03) proved to be predictive factors of poor overall survival.
Conclusion:
Our study showed the validity of the HCC-MELD equation in the evaluation of patients undergoing LT for HCC. This score offers a reliable method to assess the risk of waiting list dropout and predict posttransplantation outcomes.

