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Including mRECIST in the Metroticket 2.0 criteria improves prediction of hepatocellular carcinoma-related death after liver transplant.
- Source :
-
Journal of hepatology [J Hepatol] 2020 Aug; Vol. 73 (2), pp. 342-348. Date of Electronic Publication: 2020 Mar 20. - Publication Year :
- 2020
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Abstract
- 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.<br />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.<br />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 <subscript>10</subscript> AFP (p <0.001) and the sum of number and diameter of the tumour/s (p <0.05) were determinants of "HCC-related death" for PR/SD and PD patients. To maintain the post-LT 5-year incidence of "HCC-related death" <30%, the Metroticket 2.0 criteria were restricted in some cases of PR/SD and in all cases with PD, correctly reclassifying 9.4% of patients with "HCC-related death", at the expense of 3.5% of patients who did not have the event. The overall/net NRI was 5.8.<br />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.<br />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.<br />Competing Interests: 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.<br /> (Copyright © 2020 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)
- Subjects :
- Cause of Death
Female
Humans
Kaplan-Meier Estimate
Liver Transplantation methods
Male
Middle Aged
Postoperative Complications diagnosis
Postoperative Complications mortality
Postoperative Complications prevention & control
Predictive Value of Tests
Prognosis
Risk Assessment methods
Tumor Burden
Ultrasonography methods
alpha-Fetoproteins analysis
Carcinoma, Hepatocellular blood
Carcinoma, Hepatocellular mortality
Carcinoma, Hepatocellular pathology
Carcinoma, Hepatocellular surgery
Liver Neoplasms blood
Liver Neoplasms mortality
Liver Neoplasms pathology
Liver Neoplasms surgery
Liver Transplantation adverse effects
Neoadjuvant Therapy methods
Neoplasm Recurrence, Local diagnosis
Neoplasm Recurrence, Local etiology
Neoplasm Recurrence, Local mortality
Neoplasm Recurrence, Local prevention & control
Technology, Radiologic methods
Subjects
Details
- Language :
- English
- ISSN :
- 1600-0641
- Volume :
- 73
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Journal of hepatology
- Publication Type :
- Academic Journal
- Accession number :
- 32201284
- Full Text :
- https://doi.org/10.1016/j.jhep.2020.03.018