Background: The new deceased donor kidney allocation algorithm uses a Kidney Donor Profile Index (KDPI) based on donor characteristics to predict graft survival and divides kidneys into 4 quality groups (ie, KDPI-A, -B, -C, and -D). Pediatric kidneys constitute 10% to 12% of deceased donor kidneys. We hypothesized that KDPI would not accurately predict pediatric donor graft survival and superior predictive models could be created.
Methods: Scientific Registry of Transplant Recipients data for years 2000 to 2010 for transplants from child (<10 years) and adolescent (10-17 years inclusive) donors into first-time adult recipients were analyzed with graft failure as the principle outcome. Two novel indices, Child Donor Index (CDI) and Adolescent Donor Index (ADI), were developed using stepwise variable deletion to identify significant model covariates in a Cox Regression. Pediatric donor kidneys were then classified into the 4 quality groups based on both KDPI and CDI/ADI scores. The performance of the KDPI, CDI, and ADI models were compared with respect to the 4 quality groups defined by the new allocation system.
Results: The KDPI did not effectively discriminate between quality groups (P > 0.05 for all but 1 comparison) in Kaplan-Meier survival analyses. The CDI and ADI included novel variables (eg, body mass index percentiles) and successfully discriminated between quality groups (P < 0.05 by log rank test). The Net Reclassification Index showed improvement when switching from KDPI to CDI and ADI, with values of 0.09 (P < 0.001) and 0.073 (P < 0.001), respectively.
Conclusions: The KDPI does not accurately predict pediatric kidney graft survival. Alternative indices can improve allocation efficiency.