Development and Validation of a Multidimensional Score to Predict Long-term Kidney Transplant Outcomes (iBOX)

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

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:

1. To develop a generalizable, transportable, mechanistically and data driven composite surrogate end point in kidney transplantation;
2. 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.

Study Overview

• Status: Completed
• Conditions: Kidney Transplantation
• Intervention / Treatment: Other: No intervention

Detailed Description

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
• Enrollment (Actual): 7557

Contacts and Locations

Study Locations

• Belgium
  • Leuven, Belgium, 3000
    • Department of Nephrology and Renal Transplantation, University Hospitals Leuven
• France
  • Lyon, France, 69002
    • Department of Transplantation, Nephrology and Clinical Immunology, Hospices Civils de Lyon
  • Nantes, France, 44093
    • Centre Hospitalier Universitaire de Nantes
  • Paris, France, 75010
    • Kidney Transplant Department, Saint-Louis Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France ;
  • Paris, France, 7509
    • Kidney Transplant Department, Necker Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France;
  • Suresnes, France, 92150
    • Department of Transplantation, Nephrology and Clinical Immunology, Hôpital Foch, Suresnes, France
  • Toulouse, France, 31059
    • Department of Nephrology and Organ Transplantation, CHU Rangueil
• United States
  • Maryland
    • Baltimore, Maryland, United States, 21205
      • Department of Surgery, Johns Hopkins University School of Medicine
  • Minnesota
    • Rochester, Minnesota, United States, 55905
      • William J. von Liebig Center for Transplantation and Clinical Regeneration
  • Virginia
    • Richmond, Virginia, United States, 980663
      • Virginia Commonwealth University School of Medicine

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: N/A
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

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 for allograft survival assessment as well as RCTs with longitudinal data including baseline and follow-up clinical, functional, immunological and histological data.

Description

Inclusion Criteria:

• Kidney recipient transplanted after 2002
• Kidney recipient over 18 years of age

Exclusion Criteria:

• Combined transplantation

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Allograft survival probability	Allograft survival probability, calculated from a composite score (based on clinical, histological, immunological, and functional variables) assessed at the time of biopsy.	Allograft survival probability at 7 year post transplantation

Collaborators and Investigators

• Sponsor: Paris Translational Research Center for Organ Transplantation
• Investigators: Principal Investigator: Alexandre Loupy, PhD, Paris Translational Research Center for Organ Transplantation; Principal Investigator: Carmen Lefaucheur, PhD, Paris Translational Research Center for Organ Transplantation

Publications and helpful links

General Publications

• Aubert O, Divard G, Pascual J, Oppenheimer F, Sommerer C, Citterio F, Tedesco H, Chadban S, Henry M, Vincenti F, Srinivas T, Watarai Y, Legendre C, Bernhardt P, Loupy A. Application of the iBox prognostication system as a surrogate endpoint in the TRANSFORM randomised controlled trial: proof-of-concept study. BMJ Open. 2021 Oct 7;11(10):e052138. doi: 10.1136/bmjopen-2021-052138.
• Loupy A, Aubert O, Orandi BJ, Naesens M, Bouatou Y, Raynaud M, Divard G, Jackson AM, Viglietti D, Giral M, Kamar N, Thaunat O, Morelon E, Delahousse M, Kuypers D, Hertig A, Rondeau E, Bailly E, Eskandary F, Bohmig G, Gupta G, Glotz D, Legendre C, Montgomery RA, Stegall MD, Empana JP, Jouven X, Segev DL, Lefaucheur C. Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study. BMJ. 2019 Sep 17;366:l4923. doi: 10.1136/bmj.l4923.

Study record dates

Study Major Dates

• Study Start (ACTUAL): January 1, 2002
• Primary Completion (ACTUAL): April 29, 2020
• Study Completion (ACTUAL): April 29, 2020

Study Registration Dates

• First Submitted: March 6, 2018
• First Submitted That Met QC Criteria: March 15, 2018
• First Posted (ACTUAL): March 22, 2018

Study Record Updates

• Last Update Posted (ACTUAL): May 1, 2020
• Last Update Submitted That Met QC Criteria: April 29, 2020
• Last Verified: April 1, 2020

More Information

Terms related to this study

• Keywords: Allograft survival; Score prediction
• Other Study ID Numbers: IBOX001

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No