Metroticket 2.0 Model for Analysis of Competing Risks of Death after Liver Transplantation for Hepatocellular Carcinoma
Open accessAbstract
Background & aims Outcomes of liver transplantation for hepatocellular carcinoma (HCC) are determined by cancer-related and non-related events. Treatments for hepatitis C virus infection have reduced non-cancer events among patients receiving liver transplants, so reducing HCC-related death might be an actionable end point. We performed a competing-risk analysis to evaluate factors associated with survival of patients with HCC and developed a prognostic model based on features of HCC patients before liver transplantation.Methods We performed multivariable competing-risk regression analysis to identify factors associated with HCC-specific death of patients who underwent liver transplantation. The training set comprised 1018 patients who underwent liver transplantation for HCC from January 2000 through December 2013 at 3 tertiary centers in Italy. The validation set comprised 341 consecutive patients who underwent liver transplantation for HCC during the same period at the Liver Cancer Institute in Shanghai, China. We collected pretransplantation data on etiology of liver disease, number and size of tumors, patient level of α-fetoprotein (AFP), model for end-stage liver disease score, tumor stage, numbers and types of treatment, response to treatments, tumor grade, microvascular invasion, dates, and causes of death. Death was defined as HCC-specific when related to HCC recurrence after transplantation, disseminated extra- and/or intrahepatic tumor relapse and worsened liver function in presence of tumor spread. The cumulative incidence of death was segregated for hepatitis C virus status.Results In the competing-risk regression, the sum of tumor number and size and of log 10 level of AFP were significantly associated with HCC-specific death (P < .001), returning an average c-statistic of 0.780 (95% confidence interval, 0.763-0.798). Five-year cumulative incidence of non-HCC-related death was 8.6% in HCV-negative patients and 18.1% in HCV-positive patients. For patients with HCC to have a 70% chance of HCC-specific survival 5 years after transplantation, their level of AFP should be <200 ng/mL and the sum of number and size of tumors (in centimeters) should not exceed 7; if the level of AFP was 200-400 ng/mL, the sum of the number and size of tumors should be ≤5; if their level of AFP was 400-1000 ng/mL, the sum of the number and size of tumors should be ≤4. In the validation set, the model identified patients who survived 5 years after liver transplantation with 0.721 accuracy (95% confidence interval, 0.648%-0.793%). Our model, based on patients' level of AFP and HCC number and size, outperformed the Milan; University of California, San Francisco; Shanghai-Fudan; Up-to-7 criteria (P < .001); and AFP French model (P = .044) to predict which patients will survive for 5 years after liver transplantation.Conclusions We developed a model based on level of AFP, tumor size, and tumor number, to determine risk of death from HCC-related factors after liver transplantation. This model might be used to select end points and refine selection criteria for liver transplantation for patients with HCC. To predict 5-year survival and risk of HCC-related death using an online calculator, please see www.hcc-olt-metroticket.org/. ClinicalTrials.gov ID NCT02898415.
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The Metroticket 2.0 score predicts survival after liver transplantation for HCC through competing-risk analysis.
“The Metroticket 2.0 score proposed by Mazzaferro and coworkers (22) predicts survival after liver transplantation for HCC through competing-risk analysis.”
From Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation (2022) · cites this paper as [22]
The Metroticket 2.0 validation set showed an accuracy of 0.721 (95% CI, 0.648%-0.793%) in predicting 5-year survival after liver transplant.
“The validation set showed an accuracy of 0.721 (95% CI, 0.648%–0.793%) in predicting 5-year survival after liver transplant.”
From Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation (2022) · cites this paper as [22]
Metroticket 2.0 demonstrated a superior predictive ability compared to Milan, Up-to-7 and UCSF criteria.
“This model was compared to Milan, Up-to-7 and UCSF criteria, demonstrating a superior predictive ability.”
From Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation (2022) · cites this paper as [22]
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- Authors
- Mazzaferro, V., Sposito, C., Zhou, J., Pinna, A. D., De Carlis, L., Fan, J., Cescon, M., Di Sandro, S., Yi-feng, H., Lauterio, A., Bongini, M., & Cucchetti, A.
- Affiliations
- University of Milan (IT)
- Fudan University (CN)
- University of Bologna (IT)
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT)
- Corresponding author
- Mazzaferro, Vincenzo
- ORCID
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2018-01
- Volume
- 154
- Issue
- 1
- Pages
- 128-139
- ISSN
- 0016-5085 (ISSN-L)
- OpenAlex
- W2760934854
- Cited by
- 655
- References
- 32
- Citations by year
- 2026: 45 · 2025: 81 · 2024: 104 · 2023: 81 · 2022: 86 · 2021: 91 · 2020: 86 · 2019: 47 · 2018: 33 · 2016: 1
- FWCI
- 28.32
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- Gastroenterology (publishedVersion)
- PubMed (publishedVersion)
- IRIS UNIMORE (University of Modena and Reggio Emilia) (submittedVersion, cc-by)
- BOA (University of Milano-Bicocca) (submittedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- Topics
- Health Sciences › Medicine › Hepatology › Hepatocellular Carcinoma Treatment and Prognosis
- Health Sciences › Medicine › Surgery › Organ Transplantation Techniques and Outcomes
- Health Sciences › Medicine › Epidemiology › Hepatitis B Virus Studies
- Keywords
- hepatocellular carcinoma, liver transplantation, competing risks, alpha-fetoprotein, prognostic model, hepatitis C virus, tumor recurrence, non-cancer mortality, MELD score, tumor size and number, microvascular invasion, survival prediction
- MeSH terms
- alpha-Fetoproteins, Female, Carcinoma, Hepatocellular, Humans, Liver Neoplasms, Male, Middle Aged, Neoplasm Recurrence, Local, Regression Analysis, Cohort Studies, Survival Analysis, Liver Transplantation, Risk Assessment
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