Data Collection Study From Donors and Recipients to Optimize Donor-recipient Matching in Liver Transplantation (OPTIMATCH-LT)

• ClinicalTrials.gov Identifier: NCT03371264
• Recruitment Status: Completed
• First Posted: December 13, 2017
• Last Update Posted: December 14, 2020
• Sponsor: Assistance Publique - Hôpitaux de Paris
• Collaborator: Agence de La Biomédecine
• Information provided by (Responsible Party): Assistance Publique - Hôpitaux de Paris

Study Description

Brief Summary:

A major limitation of liver transplantation is organ shortage. To avoid exposing patients to death on the waiting list, organs are used that would have been discarded few years ago. Graft allocation is regulated by the "agence de biomedecine" which establishes a national score. Each liver graft is proposed to the patient presenting the higher score. Acceptance or rejection of the graft only depends on the decision of each centre. We propose to submit a more efficient allocation model (enabling each proposed liver graft to be transplanted in the candidate whose transplantation will afford the greatest survival benefit after registration), by collecting and analysing variables from donors and candidates/recipients.

Condition or disease
Liver Transplantation

Study Design

• Study Type: Observational
• Actual Enrollment: 9000 participants
• Observational Model: Cohort
• Time Perspective: Retrospective
• Official Title: Optimizing Donor-recipient Matching to Improve Survival After Registration on the Waiting List for Liver Transplantation: the OPTIMATCH LT Study
• Actual Study Start Date: January 1, 2015
• Actual Primary Completion Date: January 1, 2018
• Actual Study Completion Date: January 1, 2020

Groups and Cohorts

Group/Cohort
Cohort R1 and Cohort T1; Cohort R1 (patients on the waiting list between 2009 and 2013) and Cohort T1 (transplanted patients between 2009 and 2013)
Cohort R2 and Cohort T2; Cohort R2 (patients on the waiting list in 2014) and Cohort T2 (transplanted patients in 2014)

Outcome Measures

Primary Outcome Measures :

1. Survival analysis [ Time Frame: 5 years ]
   In view of the complexity of our project, different parallel approaches will be performed in order to establish predictive models
2. Multi-state models [ Time Frame: 5 years ]
   In view of the complexity of our project, different parallel approaches will be performed in order to establish predictive models
3. Decision tree analysis [ Time Frame: 5 years ]
   In view of the complexity of our project, different parallel approaches will be performed in order to establish predictive models

Secondary Outcome Measures :

1. Number of each criterion of ECD (Donor population) [ Time Frame: 5 years ]
2. Percentage of each criterion of ECD (Donor population) [ Time Frame: 5 years ]
3. Donor scores (DRI, ELTR) (Donor population) [ Time Frame: 5 years ]
4. mean score (Donor population) [ Time Frame: 5 years ]
5. number of ECD criteria (Donor population) [ Time Frame: 5 years ]
6. frequency of ECD criteria (Donor population) [ Time Frame: 5 years ]
7. mean age of donors (Donor population) [ Time Frame: 5 years ]
8. graft failure (Donor population) [ Time Frame: 5 years ]
9. grafts with correct primary function (Donor population) [ Time Frame: 5 years ]
10. epidemiological characteristics (Candidate population) [ Time Frame: 5 years ]
11. indication for transplantation (Candidate population) [ Time Frame: 5 years ]
12. severity of disease (Candidate population) [ Time Frame: 5 years ]
13. comorbidities (Candidate population) [ Time Frame: 5 years ]
14. time on waiting list (Candidate population) [ Time Frame: 5 years ]
15. Proportion of early deaths after transplantation (Candidate population) [ Time Frame: 5 years ]
16. drop-outs for worsening (Candidate population) [ Time Frame: 5 years ]
    Description of events occurring on waiting list
17. deaths on the waiting list (Candidate population) [ Time Frame: 5 years ]
18. median time of occurrence (Candidate population) [ Time Frame: 5 years ]
    Description of events occurring on waiting list
19. number of drop-outs for improvement (Candidate population) [ Time Frame: 5 years ]
20. percentages of drop-outs for improvement (Candidate population) [ Time Frame: 5 years ]

Eligibility Criteria

• Ages Eligible for Study: 18 Years and older (Adult, Older Adult)
• Sexes Eligible for Study: All
• Sampling Method: Non-Probability Sample

Study Population

Population of proposed donors and the population of patients registered on the national waiting list from 2009 to 2014 (Agence de Biomédecine)

Criteria

Inclusion Criteria:

• Liver transplant candidates : All adult LT candidates listed on the French wait list between 2009 and 2014 and followed prospectively by the mean yearly follow-up under the control of ABM.
• Donors : all adults donors registered over the same 2009-2014 period, including donors whose livers were procured and transplanted, whose liver were procured and discarded, and donors in whom liver was not harvested.

Exclusion Criteria:

• Pediatric recipients
• Pediatric donors

Contacts and Locations

Sponsors and Collaborators

Assistance Publique - Hôpitaux de Paris

Agence de La Biomédecine

Investigators

• Principal Investigator: Cyrille Feray, MD/PhD; Assistance Publique - Hôpitaux de Paris

More Information

• Responsible Party: Assistance Publique - Hôpitaux de Paris
• ClinicalTrials.gov Identifier: NCT03371264
• Other Study ID Numbers: P13639
• First Posted: December 13, 2017
• Last Update Posted: December 14, 2020
• Last Verified: December 2020

Individual Participant Data (IPD) Sharing Statement:

• Plan to Share IPD: No

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Assistance Publique - Hôpitaux de Paris:

Liver transplantation; Allocation process; Extended-criteria donors; Survival