MO971: External Validation of the Toulouse-Rangueil Predictive Model to Estimate Donor Renal Function After Living Donor Nephrectomy

Abstract

Abstract BACKGROUND AND AIMS Living donor kidney transplantation (LDKT) is the best treatment for end-stage kidney disease and is associated with better recipient outcomes than deceased donor transplantation. Living kidney donors (LKD), however, seem to be at increased risk of chronic kidney disease (CKD), which mandates a careful selection to reduce the chances of selecting a donor at risk of developing CKD. A predictive model to estimate the 1-year post-donation estimated glomerular filtration rate (eGFR) and risk of CKD was developed from a Toulouse-Rangueil cohort in 2017 [1] and has been shown to have significant correlation to the observed 1-year post-donation eGFR [2]. We aimed to externally validate this predictive tool in a cohort of patients who underwent LDKT at our center. METHOD Retrospective analysis of the 210 LKD at Centro Hospitalar Universitário do Porto from 2008 to 2017. Observed eGFR using CKD-EPI formula at 1-year post-donation was compared with the predicted eGFR using the formula developed in Toulouse-Rangueil. This predictive model is based in pre-donation eGFR and age: Postoperative eGFR (CKD-EPI, mL/min/1.73m2) = 31.71 ± (0.521 × preoperative eGFR)—(0.314 × age). Pearson correlation coefficient was used to estimate correlation between predicted and observed eGFR. Agreement was evaluated by the Bland-Altman plot. Discriminative ability to predict CKD (defined as eGFR <60 mL/min/1.73 m2) was calculated with the area under the receiver operating characteristic (ROC) curve. The accuracy of the formula in predicting eGFR <60 mL/min/1.73 m2 at 1-year post-donation was assessed by the calibration slope and calibration in the large (CITL) curves. Statistical significance was defined at P <0.05. RESULTS From 2008 to 2017, 210 LDKT were performed. Six donors were excluded from the study for lacking evaluation of eGFR at 1-year. Mean donor age was 48.1 ± 10.5. Mean pre-donation eGFR was 100.2 ± 14.1 mL/min/1.73 m2. Mean 1-year post-donation observed and predicted eGFR were respectively 70.8 ± 14.5 mL/min/1.73 m2 and 68.8 ± 9.6 mL/min/1.73 m2. Significant correlation (Pearson r = 0.66; P <0.001) and concordance (Bland-Altman plot with mean difference of observed-predicted eGFR = +1.96 mL/min/1.73 m2; 95% limits of agreement = −19.39/23.32) were seen between predicted and observed 1-year post-donation eGFR, as shown in Figures 1 and 2. Area under ROC curve (AUC) showed a good discriminative ability of the model in predicting CKD at 1-year post-donation (AUC = 0.83; 95% CI: 0.77–0.90; P < 0.001), shown in Figure 3, with optimal cutoff at predicted eGFR of 65.7 mL/min/1.73 m2 with sensibility and specificity of 83% and 91%, respectively (Table 1). This model allowed to predict CKD with a sensitivity and a specificity of respectively 43% and 94%. Calibration curve (Figure 4) exhibited an excellent prediction with slope = 1.000 and CITL = 0.000, except for observed eGFR values <60 mL/min/1.73 m2 in which there was a trend for its overestimation by the predicted eGFR. CONCLUSION In this external validation of the formula developed in Toulouse-Rangueil, we found it to have a good correlation, agreement and accuracy for the prediction of the donors 1-year post-donation eGFR. Moreover, a good discriminative ability was also observed with significant sensitivity and specificity, allowing for a pertinent prediction of CKD. This model may be used to assist in the evaluation of potential donors.