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

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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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

Conditions
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Kidney Transplantation

Intervention / Treatment
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* Other: No intervention


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Kidney recipient transplanted after 2002 Kidney recipient over 18 years of age Exclusion Criteria: Combined transplantation

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|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.|

What is the study measuring?
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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 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Score prediction, Allograft survival