Including mRECIST in the Metroticket 2.0 criteria improves prediction of hepatocellular carcinoma-related death after liver transplant.


Journal

Journal of hepatology
ISSN: 1600-0641
Titre abrégé: J Hepatol
Pays: Netherlands
ID NLM: 8503886

Informations de publication

Date de publication:
08 2020
Historique:
received: 11 07 2019
revised: 21 02 2020
accepted: 10 03 2020
pubmed: 24 3 2020
medline: 4 11 2021
entrez: 24 3 2020
Statut: ppublish

Résumé

In the context of liver transplantation (LT) for hepatocellular carcinoma (HCC), prediction models are used to ensure that the risk of post-LT recurrence is acceptably low. However, the weighting that 'response to neoadjuvant therapies' should have in such models remains unclear. Herein, we aimed to incorporate radiological response into the Metroticket 2.0 model for post-LT prediction of "HCC-related death", to improve its clinical utility. Data from 859 transplanted patients (2000-2015) who received neoadjuvant therapies were included. The last radiological assessment before LT was reviewed according to the modified RECIST criteria. Competing-risk analysis was applied. The added value of including radiological response into the Metroticket 2.0 was explored through category-based net reclassification improvement (NRI) analysis. At last radiological assessment prior to LT, complete response (CR) was diagnosed in 41.3%, partial response/stable disease (PR/SD) in 24.9% and progressive disease (PD) in 33.8% of patients. The 5-year rates of "HCC-related death" were 3.1%, 9.6% and 13.4% in those with CR, PR/SD, or PD, respectively (p <0.001). Log Incorporating the modified RECIST criteria into the Metroticket 2.0 framework can improve its predictive ability. The additional information provided can be used to better judge the suitability of candidates for LT following neoadjuvant therapies. In the context of liver transplantation for patients with hepatocellular carcinoma, prediction models are used to ensure that the risk of recurrence after transplantation is acceptably low. The Metroticket 2.0 model has been proposed as an accurate predictor of "tumour-related death" after liver transplantation. In the present study, we show that its accuracy can be improved by incorporating information relating to the radiological responses of patients to neoadjuvant therapies.

Sections du résumé

BACKGROUND & AIMS
In the context of liver transplantation (LT) for hepatocellular carcinoma (HCC), prediction models are used to ensure that the risk of post-LT recurrence is acceptably low. However, the weighting that 'response to neoadjuvant therapies' should have in such models remains unclear. Herein, we aimed to incorporate radiological response into the Metroticket 2.0 model for post-LT prediction of "HCC-related death", to improve its clinical utility.
METHODS
Data from 859 transplanted patients (2000-2015) who received neoadjuvant therapies were included. The last radiological assessment before LT was reviewed according to the modified RECIST criteria. Competing-risk analysis was applied. The added value of including radiological response into the Metroticket 2.0 was explored through category-based net reclassification improvement (NRI) analysis.
RESULTS
At last radiological assessment prior to LT, complete response (CR) was diagnosed in 41.3%, partial response/stable disease (PR/SD) in 24.9% and progressive disease (PD) in 33.8% of patients. The 5-year rates of "HCC-related death" were 3.1%, 9.6% and 13.4% in those with CR, PR/SD, or PD, respectively (p <0.001). Log
CONCLUSION
Incorporating the modified RECIST criteria into the Metroticket 2.0 framework can improve its predictive ability. The additional information provided can be used to better judge the suitability of candidates for LT following neoadjuvant therapies.
LAY SUMMARY
In the context of liver transplantation for patients with hepatocellular carcinoma, prediction models are used to ensure that the risk of recurrence after transplantation is acceptably low. The Metroticket 2.0 model has been proposed as an accurate predictor of "tumour-related death" after liver transplantation. In the present study, we show that its accuracy can be improved by incorporating information relating to the radiological responses of patients to neoadjuvant therapies.

Identifiants

pubmed: 32201284
pii: S0168-8278(20)30177-X
doi: 10.1016/j.jhep.2020.03.018
pii:
doi:

Substances chimiques

alpha-Fetoproteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

342-348

Informations de copyright

Copyright © 2020 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest The authors declare no conflicts of interest that pertain to this work. Please refer to the accompanying ICMJE disclosure forms for further details.

Auteurs

Alessandro Cucchetti (A)

Department of Medical and Surgical Sciences - DIMEC, Alma Mater Studiorum - University of Bologna, Bologna, Italy; Morgagni - Pierantoni Hospital, Forlì, Italy. Electronic address: aleqko@libero.it.

Matteo Serenari (M)

Department of Medical and Surgical Sciences - DIMEC, Alma Mater Studiorum - University of Bologna, Bologna, Italy; S.Orsola - Malpighi Hospital, Bologna, Italy.

Carlo Sposito (C)

General Surgery and Liver Transplantation Unit, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy; Università degli Studi di Milano, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy.

Stefano Di Sandro (S)

General Surgery and Abdominal Transplantation Unit, ASST Niguarda Hospital, Milan, Italy.

Cristina Mosconi (C)

S.Orsola - Malpighi Hospital, Bologna, Italy.

Ilaria Vicentin (I)

Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Department of Diagnostic and Interventional Radiology, ASST Niguarda Hospital, Milan, Italy.

Enrico Garanzini (E)

Department of Radiology, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy.

Vincenzo Mazzaferro (V)

General Surgery and Liver Transplantation Unit, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy; Università degli Studi di Milano, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy.

Luciano De Carlis (L)

General Surgery and Abdominal Transplantation Unit, ASST Niguarda Hospital, Milan, Italy; Department of Medicine and Surgery, University of Milano-Bicocca, Italy.

Rita Golfieri (R)

S.Orsola - Malpighi Hospital, Bologna, Italy; Department of Specialized, Diagnostic and Experimental Medicine - DIMES, Alma Mater Studiorum - University of Bologna, Bologna, Italy.

Carlo Spreafico (C)

Department of Radiology, Fondazione IRCCS Istituto Nazionale Tumori di Milano, Milan, Italy.

Angelo Vanzulli (A)

Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy; Department of Diagnostic and Interventional Radiology, ASST Niguarda Hospital, Milan, Italy.

Vincenzo Buscemi (V)

General Surgery and Abdominal Transplantation Unit, ASST Niguarda Hospital, Milan, Italy.

Matteo Ravaioli (M)

Department of Medical and Surgical Sciences - DIMEC, Alma Mater Studiorum - University of Bologna, Bologna, Italy; S.Orsola - Malpighi Hospital, Bologna, Italy.

Giorgio Ercolani (G)

Department of Medical and Surgical Sciences - DIMEC, Alma Mater Studiorum - University of Bologna, Bologna, Italy; Morgagni - Pierantoni Hospital, Forlì, Italy.

Antonio Daniele Pinna (AD)

Department of Medical and Surgical Sciences - DIMEC, Alma Mater Studiorum - University of Bologna, Bologna, Italy; S.Orsola - Malpighi Hospital, Bologna, Italy.

Matteo Cescon (M)

Department of Medical and Surgical Sciences - DIMEC, Alma Mater Studiorum - University of Bologna, Bologna, Italy; S.Orsola - Malpighi Hospital, Bologna, Italy.

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