External Validation of a Predictive Model to Estimate Renal Function After Living Donor Nephrectomy

Background. Transplantation from living donor nephrectomy (LDN) is the best treatment for end-stage renal disease but observed decrease in donor renal function is a major concern. The aim of this study was to externally validate a predictive model to estimate 1-y postdonation estimated glomerular filtration rate (eGFR) and risk of chronic kidney disease (CKD) in living donors. Methods. All LDN performed at Necker Hospital from January 2006 to May 2018 were retrospectively included. Observed eGFR (using CKD-EPI formula) at 1-y post LDN was compared with the predicted eGFR calculated with a formula developed at Toulouse-Rangueil and based on predonation eGFR and age. Pearson correlation, receiver operating characteristics curve (ROC curve), and calibration curve were used to assess external validity of the proposed prognostic model to predict postoperative eGFR and occurrence of CKD in donors. Results. Four hundred donors were evaluated with a mean postoperative eGFR of 62.1 +/- 14mL/min/1.73m(2). Significant correlation (Pearson r=0.66; P < 0.001) and concordance (Bradley-Blackwood F=49.189; P < 0.001) were observed between predicted and observed 1-y eGFR. Area under the receiver operating characteristic curve of the model relevant accuracy was 0.86 (95% CI, 0.82-0.89). Conclusions. This study externally validated the formula to predict 1-y postdonation eGFR. The calculator could be an accurate tool to improve the selection of living kidney donor candidate.

Automated summary

This study externally validated a predictive model for estimating postoperative eGFR in living kidney donors, demonstrating good accuracy and potential for improving the selection of kidney donor candidates.