Published online Oct 24, 2017. doi: 10.5500/wjt.v7.i5.260
Peer-review started: December 25, 2016
First decision: February 17, 2017
Revised: March 31, 2017
Accepted: May 3, 2017
Article in press: May 5, 2017
Published online: October 24, 2017
To compare the performance of 3 published delayed graft function (DGF) calculators that compute the theoretical risk of DGF for each patient.
This single-center, retrospective study included 247 consecutive kidney transplants from a deceased donor. These kidney transplantations were performed at our institution between January 2003 and December 2012. We compared the occurrence of observed DGF in our cohort with the predicted DGF according to three different published calculators. The accuracy of the calculators was evaluated by means of the c-index (receiver operating characteristic curve).
DGF occurred in 15.3% of the transplants under study. The c index of the Irish calculator provided an area under the curve (AUC) of 0.69 indicating an acceptable level of prediction, in contrast to the poor performance of the Jeldres nomogram (AUC = 0.54) and the Chapal nomogram (AUC = 0.51). With the Irish algorithm the predicted DGF risk and the observed DGF probabilities were close. The mean calculated DGF risk was significantly different between DGF-positive and DGF-negative subjects (P < 0.0001). However, at the level of the individual patient the calculated risk of DGF overlapped very widely with ranges from 10% to 51% for recipients with DGF and from 4% to 56% for those without DGF. The sensitivity, specificity and positive predictive value of a calculated DGF risk ≥ 30% with the Irish nomogram were 32%, 91% and 38%.
Predictive models for DGF after kidney transplantation are performant in the population in which they were derived, but less so in external validations.
Core tip: In this single centre, retrospective study we compared the incidence of observed delayed graft function (DGF) in 247 consecutive kidney transplant recipients with the predicted risk of DGF according to 3 different nomograms. Although the Irish nomogram provided an acceptable predictive value for the global study population, this calculator did not allow to make an accurate prediction of DGF at the individual level. Our study suggests that currently available predictive models for the risk of DGF after kidney transplantation are predictive in the population in which they were derived, but they lose their predictive value in external validations.