Development and Validation of a Multidimensional Score to Predict Long-term Kidney Transplant Outcomes (iBOX)
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|ClinicalTrials.gov Identifier: NCT03474003|
Recruitment Status : Recruiting
First Posted : March 22, 2018
Last Update Posted : January 13, 2020
To further develop personalized medicine in kidney transplantation and improve transplant patient outcomes, attention has been given to define early surrogate endpoints that might aid therapeutic interventions, clinical trials and clinical decision-making.
Despite a clear pressing need, no population-scale prognostication system exists that will combine traditional factors and biomarker candidates to represent the complete spectrum of risk predicting parameters. To adequately predict transplant patients' individual risks of allograft loss, this would require a complex integration of data, including: donor data, recipient characteristics, transplant characteristics, allograft precision phenotypes, ethnicity, immunosuppressive regimen monitoring, allograft infections, acute kidney injuries, and recipient immune profiles.
This project aims:
- To develop a generalizable, transportable, mechanistically and data driven composite surrogate end point in kidney transplantation;
- To validate several risk scores to predict kidney allograft survival and response to treatment of individual patients;
Eventually, it will provide an easily accessible tool to calculate individual patients' risk profiles after kidney transplantation, by using datasets from prospective cohorts and post hoc analysis of randomized control trial datasets.
|Condition or disease||Intervention/treatment|
|Kidney Transplantation||Other: No intervention|
Background The field of kidney transplantation currently lacks robust models to predict long-term allograft failure, which represents a major unmet need in clinical care and clinical trials. This study aims to generate and validate an accessible scoring system that predicts individual patients' risk of long-term kidney allograft failure.
Main Outcome(s) and Measure(s)
A score based on classical statistical approaches to model determinants of allograft and patient survival (Cox model, multinomial regression). These models will be further completed with statistical approaches derived from artificial intelligence and machine learning.
|Study Type :||Observational|
|Estimated Enrollment :||8000 participants|
|Official Title:||Multicenter International Observational Study to Build and Validate Multidimensional Risk Score in the Clinical Setting of Kidney Allograft Biopsies to Predict Long-term Allograft Survival|
|Actual Study Start Date :||January 2002|
|Estimated Primary Completion Date :||January 2020|
|Estimated Study Completion Date :||January 2020|
- Other: No intervention
Kidney recipients aged over 18 and of all sexes recruited from 2002 in European and North American centers, who have eGFR follow-up and data from protocol and for cause biopsies available for allograft survival assessment; RCT conducted over the past 20 years with available data on protocol biopsy within the first year and follow up clinical, biological and histological data.
- Allograft survival probability [ Time Frame: Allograft survival probability at 7 year post transplantation ]Allograft survival probability, calculated from a composite score (based on clinical, histological, immunological, and functional variables) assessed at the time of biopsy.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03474003
|Contact: Alexandre Loupy, PhDfirstname.lastname@example.org|
|United States, Maryland|
|Department of Surgery, Johns Hopkins University School of Medicine||Enrolling by invitation|
|Baltimore, Maryland, United States, 21205|
|United States, Minnesota|
|William J. von Liebig Center for Transplantation and Clinical Regeneration||Enrolling by invitation|
|Rochester, Minnesota, United States, 55905|
|United States, Virginia|
|Virginia Commonwealth University School of Medicine||Enrolling by invitation|
|Richmond, Virginia, United States, 980663|
|Department of Nephrology and Renal Transplantation, University Hospitals Leuven||Enrolling by invitation|
|Leuven, Belgium, 3000|
|Department of Transplantation, Nephrology and Clinical Immunology, Hospices Civils de Lyon||Enrolling by invitation|
|Lyon, France, 69002|
|Centre Hospitalier Universitaire de Nantes||Enrolling by invitation|
|Nantes, France, 44093|
|Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France ;||Recruiting|
|Paris, France, 75010|
|Contact: Carmen Lefaucheur, PhD email@example.com|
|Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France;||Recruiting|
|Paris, France, 7509|
|Contact: Alexandre Loupy, PhD 0033612491082 firstname.lastname@example.org|
|Department of Transplantation, Nephrology and Clinical Immunology, Hôpital Foch, Suresnes, France||Enrolling by invitation|
|Suresnes, France, 92150|
|Department of Nephrology and Organ Transplantation, CHU Rangueil||Enrolling by invitation|
|Toulouse, France, 31059|
|Principal Investigator:||Alexandre Loupy, PhD||Paris Translational Research Center for Organ Transplantation|
|Principal Investigator:||Carmen Lefaucheur, PhD||Paris Translational Research Center for Organ Transplantation|