Kidney Transplant Failure Clinical Trial
Official title:
Multicenter International Observational Study to Identify eGFR Trajectories and Their Determinants, and to Build a Multidimensional Prediction System to Predict the Probabilities of Belonging to eGFR Trajectories
The gold standard for characterizing chronic kidney disease (CKD) is the glomerular
filtration rate (GFR), which is commonly estimated in both native and transplanted kidneys
for patient monitoring and therapeutic management and ultimately guides decision-making about
whether a patient needs renal replacement therapy. In particular, the National Kidney
Foundation has defined CKD stages according to estimated GFR (eGFR) values and in several
studies, the eGFR slope or change has been found to be strongly associated with end stage
renal disease (ESRD).
However, little is known about the heterogeneity of eGFR evolution in time - i.e. eGFR
trajectories - and the related progression to ESRD and death. To date, no studies have
investigated eGFR trajectories in diversified cohorts and populations worldwide, although
this approach could provide a better understanding of CKD evolution and hence improve risk
stratification. In addition, determinants of eGFR trajectories remain poorly described.
An unsupervised approach could allow examining eGFR trajectories over time and could lead to
the identification of patient groups according to the probability of the progression of their
kidney disease.
Therefore, this study aims:
1. To identify the long-term eGFR trajectories after kidney transplantation using latent
class mixed models;
2. To identify the clinical, immunological, histological and functional determinants of the
eGFR trajectories using multinomial regressions;
3. To investigate the associations of the eGFR trajectories with the progression to ESRD
and death.
Based on the results, the investigators will provide an easily accessible tool to calculate
personalized probabilities of belonging to eGFR trajectories after kidney transplantation, by
using datasets from prospective cohorts and post hoc analysis of randomized control trial
datasets.
Background
Chronic kidney disease (CKD) now affects 850 million individuals worldwide, exceeding the
global prevalence of diabetes, cancer and HIV/AIDS. In addition, end-stage renal disease
affects 7.4 million individuals and mortality rate for individuals burdened by kidney disease
is now estimated at 5 to 10 million individuals each year. Therefore, developing better
diagnostic and treatment approaches for the kidney disease epidemic is a global priority, as
leading professional societies and health agencies have emphasized (the US Food & Drug
Administration, the National Kidney Foundation, the European Medicines Agency, the European
Society of Organ Transplantation, the American Society for Transplantation and the American
Society of Transplant Surgeons).
However, current approaches for investigating the relationship between eGFR course and
outcomes such as ESRD and mortality have been limited by registries with an overall lack on
granular data, including infrequent eGFR measurements for a single patient and convenience
clinical samples. An unsupervised longitudinal approach to determine patient eGFR evolution
may bring an original perspective to the traditional clinical interpretation of kidney
function based on limited eGFR measurements, short-term follow-up, and standard statistical
approach.
Main Outcome(s) and Measure(s)
- eGFR trajectories
- Determinants of eGFR trajectories
- Associations of eGFR trajectories with ESRD and death
- Prediction system that will provide the personalized probabilities of belonging to eGFR
trajectories
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