TY - JOUR
T1 - Validation of a prediction system for risk of kidney allograft failure in pediatric kidney transplant recipients
T2 - An international observational study
AU - Hogan, Julien
AU - Divard, Gillian
AU - Aubert, Olivier
AU - Garro, Rouba
AU - Boyer, Olivia
AU - Donald Cooper, Lee Alex
AU - Farris, Alton Brad
AU - Fila, Marc
AU - Seifert, Michael
AU - Sellier-Leclerc, Anne Laure
AU - Smith, Jody
AU - Fichtner, Alexander
AU - Tönshoff, Burkhard
AU - Twombley, Katherine
AU - Warady, Bradley
AU - Pearl, Meghan
AU - Zahr, Rima S.
AU - Lefaucheur, Carmen
AU - Patzer, Rachel
AU - Loupy, Alexandre
N1 - Publisher Copyright:
© 2023
PY - 2023/10
Y1 - 2023/10
N2 - Predicting long-term kidney allograft failure is an unmet need for clinical care and clinical trial optimization in children. We aimed to validate a kidney allograft failure risk prediction system in a large international cohort of pediatric kidney transplant recipients. Patients from 20 centers in Europe and the United States, transplanted between 2004 and 2017, were included. Allograft assessment included estimated glomerular filtration rate, urine protein-to-creatinine ratio, circulating antihuman leukocyte antigen donor-specific antibody, and kidney allograft histology. Individual predictions of allograft failure were calculated using the integrative box (iBox) system. Prediction performances were assessed using discrimination and calibration. The allograft evaluations were performed in 706 kidney transplant recipients at a median time of 9.1 (interquartile range, 3.3-19.2) months posttransplant; mean estimated glomerular filtration rate was 68.7 ± 28.1 mL/min/1.73 m2, and median urine protein-to-creatinine ratio was 0.1 (0.0-0.4) g/g, and 134 (19.0%) patients had antihuman leukocyte antigen donor-specific antibodies. The iBox exhibited accurate calibration and discrimination for predicting the outcomes up to 10 years after evaluation, with a C-index of 0.81 (95% confidence interval, 0.75-0.87). This study confirms the generalizability of the iBox to predict long-term kidney allograft failure in children, with performances similar to those reported in adults. These results support the use of the iBox to improve patient monitoring and facilitate clinical trials in children.
AB - Predicting long-term kidney allograft failure is an unmet need for clinical care and clinical trial optimization in children. We aimed to validate a kidney allograft failure risk prediction system in a large international cohort of pediatric kidney transplant recipients. Patients from 20 centers in Europe and the United States, transplanted between 2004 and 2017, were included. Allograft assessment included estimated glomerular filtration rate, urine protein-to-creatinine ratio, circulating antihuman leukocyte antigen donor-specific antibody, and kidney allograft histology. Individual predictions of allograft failure were calculated using the integrative box (iBox) system. Prediction performances were assessed using discrimination and calibration. The allograft evaluations were performed in 706 kidney transplant recipients at a median time of 9.1 (interquartile range, 3.3-19.2) months posttransplant; mean estimated glomerular filtration rate was 68.7 ± 28.1 mL/min/1.73 m2, and median urine protein-to-creatinine ratio was 0.1 (0.0-0.4) g/g, and 134 (19.0%) patients had antihuman leukocyte antigen donor-specific antibodies. The iBox exhibited accurate calibration and discrimination for predicting the outcomes up to 10 years after evaluation, with a C-index of 0.81 (95% confidence interval, 0.75-0.87). This study confirms the generalizability of the iBox to predict long-term kidney allograft failure in children, with performances similar to those reported in adults. These results support the use of the iBox to improve patient monitoring and facilitate clinical trials in children.
KW - allograft failure
KW - Banff classification
KW - children
KW - kidney transplantation
KW - predictive model
UR - https://www.scopus.com/pages/publications/85166353125
U2 - 10.1016/j.ajt.2023.07.004
DO - 10.1016/j.ajt.2023.07.004
M3 - Article
C2 - 37453485
AN - SCOPUS:85166353125
SN - 1600-6135
VL - 23
SP - 1561
EP - 1569
JO - American Journal of Transplantation
JF - American Journal of Transplantation
IS - 10
ER -