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
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 7,557
- 试验地点
- 10
- 主要终点
- Allograft survival probability
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Kidney recipient transplanted after 2002
- •Kidney recipient over 18 years of age
排除标准
- •Combined transplantation
结局指标
主要结局
Allograft survival probability
时间窗: 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.
次要结局
未报告次要终点
研究者
Professor Alexandre Loupy
Professor Alexandre Loupy
Paris Translational Research Center for Organ Transplantation
