Developing Prediction Models for Allograft Failure After Liver Transplantation
NCT ID: NCT05289609
Last Updated: 2022-03-21
Study Results
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Basic Information
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UNKNOWN
5000 participants
OBSERVATIONAL
2022-04-01
2024-04-01
Brief Summary
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Recently, sophisticated kinetic models became available, offering the possibility to predict 90-day AF with unprecedented accuracy, by computing data from the first 10 days after liver transplant (LT).
The growing utilization of extended criteria and cardiac death donors stimulates the transplant community to further refine such predictive models and validate them on a larger scale population of patients across the nations.
This study aims to develop new algorithms for the timely prediction of AF at 90 and 365 days using a prospective international cohort from high-volume centers, to validate them on a large retrospective cohort, to identify the best time for retransplantation, to stratify the risk of AF according to the graft type (i.e. DBD, ECD, DCD, LD), to weigh the effect of risk-mitigation strategies, and to assess the correlation with post-LT morbidity and mortality.
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Detailed Description
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The evaluation times and the modalities to promptly identify AF are still the object of research. At the same time, no consensus exists on the most accurate predictors of AF and on the possible mitigation strategies. In addition, ECD and DCD grafts are burdened by a higher incidence of ischemic cholangiopathy, that typically develops after 6 to 12 months, which is also a cause of AF and need for retransplant.
Two scores, one developed in the United States at University of California Los Angeles (L-GrAFT) and one in Italy on a multicentric basis (EASE), allow the prediction of EAF with excellent C-statistics. Both were validated on multicentric external populations. L-GrAFT and EASE scores are calculated at day 10 after LT; a modification of the L-GrAFT score at day 7 has been developed and validated. Both scores are also proposed for quantifying the degree of graft recovery in translational studies. However, the prognostic role of pre-transplant histopathology of the graft as well as the detailed characterization of the dynamics that make retransplant sustainable or contraindicated and the possibilities to intervene to mitigate the graft-related risk remain unmet needs. Finally, the differences among phenotypic patterns of various transplant types (DBD, deceased donor grafts after cardiac death \[DCD\] and living donor grafts \[LD\]) have not been investigated, nor a large prospective study has been undertaken.
Rationale. Timely prediction of AF is pivotal to identify patients potentially benefiting from a rescue retransplant before severe complications develop. When massive cytolysis and clear signs of liver failure occur within the first 2-4 days after LT, the indication for a retransplant is clear, independently from the evidence of hepatic vessels thrombosis. Nevertheless, past 5 to 10 days after transplant, the decision whether or not to retransplant is often challenging. AF results from a complex interplay between donor, procurement-related, and recipient perioperative factors. All of them contribute to determine the severity and the capability to recover from the ischemia-reperfusion injury. However, several conditions and/or postoperative events may precipitate such capability (e.g., pre-operative cardiac ischemic damage, frailty-sarcopenia, graft rejection, drug toxicity, kidney failure, or severe infections or sepsis). Only a part of these factors have been studied. Additionally, although L-GrAFT and EASE scores can predict AF after 7 to 10 days, the trajectories of the graft towards recovery, successful or unsuccessful retransplantation and death without retransplant, have not been fully characterized yet. Despite the excellent accuracy and the efficacious discrimination ability, the existing studies have not elucidated the individual role of these events, nor competitive models have been developed in the perspective of retransplantation. Notably, literature is exclusively based on retrospective studies. Almost all these studies span an extended period of time, are often monocentric, do not consider the center volume effect, and are not balanced in the number of recruited patients in each center. Finally, only a small number of DCD grafts and ECD grafts managed by perfusion machines have been included in previous studies.
Study objectives:
* Primary to develop new algorithms for the timely prediction of Allograft Failure at 90 and 365 days using a comprehensive prospectively collected dataset based on the current clinical practice of high-volume centers.
* Secondary to validate the already existing predictive models and the newly developed algorithms on a retrospective cohort of patients from low to medium-volume transplant centers; to develop a novel time-based dynamic algorithm, with increasing accuracy from the 3rd to 7th post-operative day; to identify the best-time for re-transplant (after stratification according to the post-operative weeks, months, trimesters); to investigate differences in the incidence of Allograft Failure at 90 and 365 days according to DBD, DCD, LD donor grafts; to evaluate the effect of mitigation strategies on the precipitating factors of Allograft Failure at 90 and 365 days; to investigate the association of kinetic algorithms with development of post-LT complications (acute kidney injury, ischemic cholangiopathy, other complications); to identify risk factors for mortality that may contraindicate re-transplant.
Study design. Multicenter, international, non-competitive, observational two-cohort study. The two cohorts include a first cohort with prospective patient enrolment and a second cohort with retrospective enrolment.
A steering committee was constituted to design the study. Members were identified according to their experience on the topic and paying attention to their geographic area (Europe, Americas, Asia). The list of the Institution of all the steering committee members is included above. A draft of the preliminary study design and subsequent questionnaires on controversial issues were circulated among members.
No modification to the participating centers standard practice for the management of LT donors and recipients is required. The study has been structured according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Setting. The study will be conducted in 80 liver transplant centers from four continents (the final list of participating centers will be published as soon as all centers have confirmed and are ready to enroll).
Two distinct datasets will be created to collect data from the participating centers, depending on which of the two cohorts their patients belong to.
* Prospective cohort.
* Retrospective cohort. The study design includes two evaluation times (at 90 and 365 days after LT). Participants will be followed-up during their post-transplant hospital stay and at the liver transplant outpatient clinic after discharge from hospital. Readmissions to the hospital for any cause will be recorded.
Variables.
Main variable categories are:
* identification data (ID)
* donor characteristics data
* pre-operative data
* graft histology data
* intraoperative data
* post-operative data
* follow-up data
Data will be entered on the electronic Case Report Form (eCRF). The eCRF has been developed using the REDCap ver 10.0.21 software hosted at https://redcap-irccs.policlinicogemelli.it/, which includes ten forms:
1. ID data (LT progressive number, first 4 letter of the surname, LT date, LT type)
2. Donor data (standard parameters)
3. Biopsy data (central revision of uploaded scanned slides)
4. Pre-operative evaluation of the recipient (standard parameters)
5. Pre-operative quantification of Sarcopenia (central revision of uploaded CT scan)
6. Intra-operative data (surgical and anesthetics parameters)
7. Post-operative data (day 1-10)
8. Surgical complications data (paying attention to infections and contraindications to Re-Transplant)
9. End Point Indicators of graft function (CT scan, MR)
10. Outcome data at 90 and 365 days (ICU LoS, Hospital Los, Graft Survival, Causes of Graft Loss, Patient Survival) The eCRF allows easy calculation of scores including L-GrAFT and EASE scores.
The REDCAP software will automatically perform de-identification and encryption of the data.
The retrospective cohort dataset will include 75 variables, previously registered in the local-center data sources. They will be used to validate previously published kinetic algorithms.
Qualitative variables. Histology obtained during the back-table graft preparation, or alternatively at any time before graft implantation, will constitute a key point although not mandatory condition for the enrolment. The histology slides will be scanned at the local centers, de-identified and uploaded on the eCRF and centrally read for research purposes.Transplant candidates CT scan (DICOM files only) from the pre-listing work-up will be de-identified and uploaded on the eCRF and centrally read for research purposes. The incidence and grade of ischemic cholangiopathy will be measured by means of a cholangio-magnetic resonance (MR) at 10-12 months after LT (on-demand, based on clinical suspicion of ischemic cholangiopathy, e.g., higher than two-fold increase in baseline alkaline phosphatase levels). The DICOM files will be anonymized and uploaded on the eCRF and centrally read for research purposes.
Quantitative variables. Quantitative variables will be first explored by missing analysis at three levels: at a center level; at a country level; at continental level. Then, they will be assessed by descriptive analysis in the overall population and according to three main graft types. Donor characteristics, pre-operative, intraoperative, graft histology, and post-operative outcome-data will be assessed as potential predictors of the main outcome, i.e., allograft survival, as well as of patient survival at 90 and 365 days. The above-mentioned data will also be implemented in algorithms to chose the best time-window within which undergo re-transplant. Impact of donor age, graft percentage of macro-steatosis, Donor Warm Ischemia Time, Donor Asystolic Warm Ischemia Time, Recipient Warm Ischemia Time, Cold Ischemia Time, incidence of post-reperfusion syndrome, length of stay (LoS) in hospital and incidence of vascular thrombosis and of biliary complications (anastomotic and non-anastomotic) will be evaluated paying attention to the graft type.
Conditions
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Study Design
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COHORT
OTHER
Study Groups
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Prospective Cohort
Liver Transplant Recipients from High-volume centers (i.e., performing \>= 65 LTs per year)
Liver Transplantation
Individuals with end-stage liver disease will be subjected to liver transplantation from deceased or living donors
Retrospective Cohort
Liver Transplant Recipients from Low-to-medium volume centers (i.e., performing \<65 LTs per year) and High-volume centers
Liver Transplantation
Individuals with end-stage liver disease will be subjected to liver transplantation from deceased or living donors
Interventions
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Liver Transplantation
Individuals with end-stage liver disease will be subjected to liver transplantation from deceased or living donors
Eligibility Criteria
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Inclusion Criteria
2. First transplant (retransplant cases should be enrolled if the first transplant is part of the study)
3. DBD grafts
4. DCD grafts (controlled and uncontrolled)
5. DBD and DCD grafts managed by perfusion machines
6. Living donor grafts (both left lobe and right lobe grafts) transplanted into adult recipients.
7. Split liver grafts (both left lobe and right lobe grafts) transplanted into adult recipients.
Exclusion Criteria
2. Domino grafts
3. Heterotopic grafts
4. Double grafts
5. Recipients undergoing liver transplants for cholangiocarcinoma and colorectal liver metastases
18 Years
ALL
No
Sponsors
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University of California, Los Angeles
OTHER
University Hospital Padova
OTHER
Mayo Clinic
OTHER
Hospital Italiano de Buenos Aires
OTHER
Tokyo Women's Medical University
OTHER
Hospital Universitario La Paz
OTHER
First Affiliated Hospital, Sun Yat-Sen University
OTHER
University of Roma La Sapienza
OTHER
University of Massachusetts, Worcester
OTHER
The Cleveland Clinic
OTHER
Dr. Rela Institute & Medical Centre
UNKNOWN
University of Toronto
OTHER
Universidade Federal do ParanĂ¡
OTHER
Royal Infirmary of Edinburgh
OTHER
Erasmus Medical Center
OTHER
Fondazione Policlinico Universitario Agostino Gemelli IRCCS
OTHER
Responsible Party
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Prof. Alfonso Avolio
Professor
Principal Investigators
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Vatche Agopian
Role: PRINCIPAL_INVESTIGATOR
University of California, Los Angeles
Alfonso W Avolio
Role: PRINCIPAL_INVESTIGATOR
Fondazione Policlinico universitario Agostino Gemelli IRCCS, Rome, Italy
Locations
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Dumont-UCLA Transplant and Liver Cancer Centers, Department of Surgery, David Geffen School of Medicine at UCLA
Los Angeles, California, United States
Department of Transplant, Mayo Clinic Florida
Jacksonville, Florida, United States
Division of Organ Transplantation, Department of Surgery, University of Massachusetts Memorial Hospital, University of Massachusetts
Worcester, Massachusetts, United States
Transplantation Center, Digestive Disease and Surgery Institute, Cleveland Clinic
Cleveland, Ohio, United States
Division of Hepato Pancreatic Biliary Surgery and Liver Transplant Unit, Department of General Surgery, Hospital Italiano de Buenos Aires
Buenos Aires, , Argentina
Liver Transplant Division, Santa Isabel Hospital
Blumenau, , Brazil
Multi-Organ Transplant and HPB Surgical Oncology, Division of General Surgery, University Health Network
Toronto, , Canada
First Affiliated Hospital, Sun Yat-Sen University
Guangzhou, , China
Dr Rela Institute and Medical Centre
Chennai, , India
Department of Surgery, Oncology and Gastroenterology, Padova University Hospital
Padua, , Italy
Department of Surgery, Oncology and Gastroenterology, Padova University Hospital
Padua, , Italy
General Surgery and Organ Transplantation Unit, Sapienza University of Rome
Roma, , Italy
Fondazione Policlinico Universitario A. Gemelli, IRCCS
Roma, , Italy
GSTeP - Gemelli Science and Technology Park, Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Roma, , Italy
Department of Surgery, Tokyo Women's Medical University
Shinjuku-Ku, , Japan
Erasmus MC Transplant Institute, University Medical Center Rotterdam, Department of Surgery, Division of Hepato-Pancreato-Biliary and Transplant Surgery
Rotterdam, , Netherlands
Cirugia General y del A. Digestivo, Hospital Universitario La Paz
Madrid, , Spain
Department of Transplant Surgery, Edinburgh Transplant Centre, Royal Infirmary of Edinburgh
Edinburgh, , United Kingdom
Countries
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Central Contacts
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Facility Contacts
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References
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Agopian VG, Harlander-Locke MP, Markovic D, Dumronggittigule W, Xia V, Kaldas FM, Zarrinpar A, Yersiz H, Farmer DG, Hiatt JR, Busuttil RW. Evaluation of Early Allograft Function Using the Liver Graft Assessment Following Transplantation Risk Score Model. JAMA Surg. 2018 May 1;153(5):436-444. doi: 10.1001/jamasurg.2017.5040.
Agopian VG, Markovic D, Klintmalm GB, Saracino G, Chapman WC, Vachharajani N, Florman SS, Tabrizian P, Haydel B, Nasralla D, Friend PJ, Boteon YL, Ploeg R, Harlander-Locke MP, Xia V, DiNorcia J, Kaldas FM, Yersiz H, Farmer DG, Busuttil RW. Multicenter validation of the liver graft assessment following transplantation (L-GrAFT) score for assessment of early allograft dysfunction. J Hepatol. 2021 Apr;74(4):881-892. doi: 10.1016/j.jhep.2020.09.015. Epub 2020 Sep 23.
Avolio AW, Franco A, Schlegel A, Lai Q, Meli S, Burra P, Patrono D, Ravaioli M, Bassi D, Ferla F, Pagano D, Violi P, Camagni S, Dondossola D, Montalti R, Alrawashdeh W, Vitale A, Teofili L, Spoletini G, Magistri P, Bongini M, Rossi M, Mazzaferro V, Di Benedetto F, Hammond J, Vivarelli M, Agnes S, Colledan M, Carraro A, Cescon M, De Carlis L, Caccamo L, Gruttadauria S, Muiesan P, Cillo U, Romagnoli R, De Simone P. Development and Validation of a Comprehensive Model to Estimate Early Allograft Failure Among Patients Requiring Early Liver Retransplant. JAMA Surg. 2020 Dec 1;155(12):e204095. doi: 10.1001/jamasurg.2020.4095. Epub 2020 Dec 16.
Avolio AW, Lai Q, Cillo U, Romagnoli R, De Simone P. L-GrAFT and EASE scores in liver transplantation: Need for reciprocal external validation and comparison with other scores. J Hepatol. 2021 Sep;75(3):729-731. doi: 10.1016/j.jhep.2020.12.009. Epub 2020 Dec 17. No abstract available.
Avolio AW, Contegiacomo A, Spoletini G, Moschetta G, Bianco G, Agnes S, Melcher ML, Burra P. Toward a novel evidence-based definition of early allograft failure in the perspective of liver retransplant. Transpl Int. 2021 Dec;34(12):2905-2907. doi: 10.1111/tri.14162. Epub 2021 Dec 6. No abstract available.
Croome KP, Mathur AK, Aqel B, Yang L, Taner T, Heimbach JK, Rosen CB, Paz-Fumagalli R, Taner CB. Classification of Distinct Patterns of Ischemic Cholangiopathy Following DCD Liver Transplantation: Distinct Clinical Courses and Long-term Outcomes From a Multicenter Cohort. Transplantation. 2022 Jun 1;106(6):1206-1214. doi: 10.1097/TP.0000000000003928. Epub 2022 Aug 30.
Chen S, Wang T, Luo T, He S, Huang C, Jia Z, Zhan L, Wang D, Zhu X, Guo Z, He X. Prediction of Graft Survival Post-liver Transplantation by L-GrAFT Risk Score Model, EASE Score, MEAF Scoring, and EAD. Front Surg. 2021 Nov 19;8:753056. doi: 10.3389/fsurg.2021.753056. eCollection 2021.
Lai Q, Magistri P, Lionetti R, Avolio AW, Lenci I, Giannelli V, Pecchi A, Ferri F, Marrone G, Angelico M, Milana M, Schinnina V, Menozzi R, Di Martino M, Grieco A, Manzia TM, Tisone G, Agnes S, Rossi M, Di Benedetto F, Ettorre GM; Sarco-Model Study Group. Sarco-Model: A score to predict the dropout risk in the perspective of organ allocation in patients awaiting liver transplantation. Liver Int. 2021 Jul;41(7):1629-1640. doi: 10.1111/liv.14889. Epub 2021 Apr 22.
Martins PN, Rizzari MD, Ghinolfi D, Jochmans I, Attia M, Jalan R, Friend PJ; ILTS Special Interest Group "DCD, Preservation and Machine Perfusion". Design, Analysis, and Pitfalls of Clinical Trials Using Ex Situ Liver Machine Perfusion: The International Liver Transplantation Society Consensus Guidelines. Transplantation. 2021 Apr 1;105(4):796-815. doi: 10.1097/TP.0000000000003573.
Pareja E, Cortes M, Hervas D, Mir J, Valdivieso A, Castell JV, Lahoz A. A score model for the continuous grading of early allograft dysfunction severity. Liver Transpl. 2015 Jan;21(1):38-46. doi: 10.1002/lt.23990. Epub 2014 Nov 24.
Olthoff KM, Kulik L, Samstein B, Kaminski M, Abecassis M, Emond J, Shaked A, Christie JD. Validation of a current definition of early allograft dysfunction in liver transplant recipients and analysis of risk factors. Liver Transpl. 2010 Aug;16(8):943-9. doi: 10.1002/lt.22091.
Patrono D, Cussa D, Sciannameo V, Montanari E, Panconesi R, Berchialla P, Lepore M, Gambella A, Rizza G, Catalano G, Mirabella S, Tandoi F, Lupo F, Balagna R, Salizzoni M, Romagnoli R. Outcome of liver transplantation with grafts from brain-dead donors treated with dual hypothermic oxygenated machine perfusion, with particular reference to elderly donors. Am J Transplant. 2022 May;22(5):1382-1395. doi: 10.1111/ajt.16996. Epub 2022 Feb 22.
Petrowsky H, Rana A, Kaldas FM, Sharma A, Hong JC, Agopian VG, Durazo F, Honda H, Gornbein J, Wu V, Farmer DG, Hiatt JR, Busuttil RW. Liver transplantation in highest acuity recipients: identifying factors to avoid futility. Ann Surg. 2014 Jun;259(6):1186-94. doi: 10.1097/SLA.0000000000000265.
Schlegel A, van Reeven M, Croome K, Parente A, Dolcet A, Widmer J, Meurisse N, De Carlis R, Hessheimer A, Jochmans I, Mueller M, van Leeuwen OB, Nair A, Tomiyama K, Sherif A, Elsharif M, Kron P, van der Helm D, Borja-Cacho D, Bohorquez H, Germanova D, Dondossola D, Olivieri T, Camagni S, Gorgen A, Patrono D, Cescon M, Croome S, Panconesi R, Carvalho MF, Ravaioli M, Caicedo JC, Loss G, Lucidi V, Sapisochin G, Romagnoli R, Jassem W, Colledan M, De Carlis L, Rossi G, Di Benedetto F, Miller CM, van Hoek B, Attia M, Lodge P, Hernandez-Alejandro R, Detry O, Quintini C, Oniscu GC, Fondevila C, Malago M, Pirenne J, IJzermans JNM, Porte RJ, Dutkowski P, Taner CB, Heaton N, Clavien PA, Polak WG, Muiesan P; DCD Collaborator Group. A multicentre outcome analysis to define global benchmarks for donation after circulatory death liver transplantation. J Hepatol. 2022 Feb;76(2):371-382. doi: 10.1016/j.jhep.2021.10.004. Epub 2021 Oct 14.
Spoletini G, Ferri F, Mauro A, Mennini G, Bianco G, Cardinale V, Agnes S, Rossi M, Avolio AW, Lai Q. CONUT Score Predicts Early Morbidity After Liver Transplantation: A Collaborative Study. Front Nutr. 2022 Jan 7;8:793885. doi: 10.3389/fnut.2021.793885. eCollection 2021.
Aby ES, Lee E, Saggi SS, Viramontes MR, Grotts JF, Agopian VG, Busuttil RW, Saab S. Pretransplant Sarcopenia in Patients With NASH Cirrhosis Does Not Impact Rehospitalization or Mortality. J Clin Gastroenterol. 2019 Oct;53(9):680-685. doi: 10.1097/MCG.0000000000001109.
Other Identifiers
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4571
Identifier Type: -
Identifier Source: org_study_id
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