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Updated: May 25, 2026

Mouse Kidney Transplantation: Models of Allograft Rejection
Published on: October 11, 2014
Prediction of long-term kidney failure in renal transplant with chronic allograft dysfunction using stage-specific
Hamid Reza Khalkhali1, Ali Ghafari
1Department of Epidemiology and Biostatistics, Faculty of Medicine, Urmia University of Medical Sciences, Urmia, Iran. khalkhali@umsu.ac.ir
Objectives:
The process of kidney failure in renal transplant recipients with chronic allograft dysfunction is characterized by a progressive decline in glomerular filtration rate over time that it is determined by the 5-stage model. This study used stage-based statistical survival analysis to predict graft survival in renal transplant recipients with chronic allograft dysfunction.
Materials And Methods:
In a single-center, retrospective study, 214 renal transplant recipients with chronic allograft dysfunction were investigated at a university hospital in Iran from 1997 to 2005. At each patient visit, kidney function was assessed using glomerular filtration rate and stage of disease.
Results:
The estimated stage-specific hazard rates of disease progression are stage one, 453.936; stage two, 485.040; stage three, 545.808; and stage four; 649.488 per 1000 person-years. The estimated mean times in each stage were as follows: kidney damage with normal or increased glomerular filtration rate, 26.43 months; kidney damage with mildly decreased glomerular filtration rate, 24.74 months; moderate kidney disease, 21.98 months; and severe kidney disease; 18.48 months. These estimates yield a mean time from stage 1 to kidney failure of 91.63 months. The probability of graft survival was predicted using estimated stage-specific hazard rates. The 18th, 58th, 118th, and 155th months death-censored graft survival probabilities were 0.99, 0.75, 0.25, and 0.10.
Conclusions:
In this method of survival analysis, we can determine a statistical model according to a real clinical model in renal transplant recipients with chronic allograft dysfunction. It enables us to determine the stage-specific hazard rates of disease progression. These findings can help nephrologists to understand the kidney disease process and better predict graft survival.
Related Concept Videos
Kidney Transplant I: Introduction
Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration
Chronic Kidney Disease I: Introduction
Acute Kidney Injury III: Clinical Manifestations
Acute Kidney Injury I: Introduction
Kidney Transplant II: Surgical Procedure