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A predictive model to estimate post-donation glomerular filtration rate (eGFR) and risk of CKD at 1-year was developed from a Toulouse-Rangueil cohort in 2017 and showed an excellent correlation to the observed 1-year post-donation eGFR. We retrospectively analyzed all living donor kidney transplants performed at a single center from 1998 to 2020. Observed eGFR using CKD-EPI formula at 1-year post-donation was compared to the predicted eGFR using the formula eGFR (CKD-EPI, mL/min/1.73 m2) = 31.71+ (0.521 × preoperative eGFR) − (0.314 × age). 333 donors were evaluated. A good correlation (Pearson
Living donor kidney transplant is the best treatment for ESRD patients eligible for transplant (
The evaluation of a living donor candidate is a multidisciplinary task to minimize the risk for the donor while ensuring the organ’s suitability for the recipient (
Current Clinical practice guidelines on the evaluation and care of living kidney donors from Kidney Disease Improving Global Outcomes (KDIGO) recommend a comprehensive approach to risk assessment that should replace decisions based on assessments of single risk factors evaluation (
A predictive model to estimate the donor 1-year post-donation estimated glomerular filtration rate (eGFR) and risk of CKD was developed from a Toulouse-Rangueil cohort in 2017 (
We sought to externally validate this predictive tool in a different, large European cohort of patients who underwent a living donor kidney transplant at our center.
This external validation study was conducted according to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnostics (TRIPOD) guidelines (
We retrospectively reviewed the clinical data of all (
Following international guidelines, all donors were subjected to a standard evaluation protocol. Baseline demographic, anthropomorphic, analytical, and clinical data were collected from the living kidney donors. Serum creatinine Serum creatinine-based CKD-EPI equation (
Hypertension was defined by blood pressure in the consultation >140/90 mmHg, ABPM > 135/85 mmHg, and past diagnosis of hypertension or antihypertensive medication. Uncontrolled hypertension or evidence of end-organ damage were criteria of exclusion. Potential donors with a history of malignancy, obesity, or diabetes were excluded. Although a lower limit of eGFR was not established by Unit protocol, potential donors with eGFR below 80 m mL/min/1.73 m2 were usually discarded. The final approval for kidney donation was reviewed in a multidisciplinary meeting and the ethical approval was mandatory.
Left-side procurement was preferred for anatomical reasons except for complex vessels anatomy or when a significant renal asymmetry was found, and the right kidney had the lower clearance. A transperitoneal laparoscopic approach was performed in most donors. Lifetime annual follow-up appointments are available for all donors.
For validation of the predictive model, eGFR was calculated using the CKD-EPI Chronic Kidney Disease Epidemiology pre-donation and 1 year (±30 days) after donation.
Data are presented as mean (and standard deviations for continuous variables and frequency (and percentages) for categorical variables.
Observed eGFR using CKD-EPI formula at 1-year post-donation was compared to the predicted eGFR using the formula developed in Toulouse-Rangueil: postoperative eGFR (CKD-EPI, mL/min/1.73 m2) = 31.71 + (0.521 × preoperative eGFR) − (0.314 × age).
The ability of this formula to predict the observed GFR was analyzed by Pearson correlation, and agreement was explored by the Bland-Altman plot. The discriminative ability to predict CKD3-5 was evaluated by the area under the receiver operating characteristic (ROC) curve and using sensitivity, specificity, and positive, or negative predictive values (PPV or NPV). Furthermore, the accuracy of the predictive model was depicted by constructing a calibration plot and assessed through the calibration slope and the calibration in the large.
A 2-sided
The baseline donors’ characteristics for the cohort of 333 patients are presented in
Patients’ characteristics of the 333 living donors.
N = 333 | |
---|---|
Age, mean ± SD | 47.3 ± 10.6 |
Sex F:M, n (%) | 236 (71):97 (29) |
BMI, mean ± SD (Kg/m2) | 25.3 ± 3.4 |
Smoking habits, n (%) | 51 (15) |
Hypertension, n (%) | 50 (15) |
Pre-donation SCr, mean ± SD (mg/dL) | 0.75 ± 0.16 |
Pre- donation eGFR, mean ± SD | 100.3 ± 14.7 |
1-year postdonation SCr, mean ± SD (mg/dL) | 1.05 ± 0.23 |
1-year postdonation eGFR, mean ± SD | 71.4 ± 16.2 |
Predicted 1-year postdonation eGFR, mean ± SD | 69.1 ± 10.0 |
eGFR: mL/min/1.73 m2.
Eighty-five donors (25.5%) reached the definition of CKD at 1-year after donation as depicted in
ROC: McNemar's exact test for optimal cutoff and for CKD cutoff.
Observed eGFR | Total | |||
---|---|---|---|---|
<60 | ≥60 | |||
Predicted eGFR | <65.25 | 65 (76) | 61 (25) | 126 |
≥65.25 | 20 (24) | 187 (75) | 207 | |
Total | 85 | 248 | 333 | |
McNemar’s exact test |
||||
Predicted eGFR | <60 | 40 (47) | 17 (7) | 57 |
≥60 | 45 (53) | 231 (93) | 276 | |
Total | 85 | 248 | 333 | |
McNemar’s exact test |
eGFR: mL/min/1.73 m2.
A significant correlation was observed between calculated and observed 1-year eGFR (
Correlation between observed eGFR using CKD-EPI formula at 1-year post-donation and predicted eGFR using the formula developed in Toulouse-Rangueil.
Bland-Altman plot: Agreement evaluation, correlation coefficient between the difference and the mean of observed and predicted eGFR.
Furthermore, the model showed a good discriminative ability of the formula in predicting observed CKD at 1-year post-donation, with the area under the receiver operating characteristic (ROC) curve of 0.83 (95% CI: 0.78–0.88;
Receiver operating characteristic (ROC) curve for predicted eGFR for the detection of CKD (eGFR < 60 mL/min/1.73 m2). Diagonal line is the reference line: AUC = 0.83. Optimal cutoff: 65.25 mL/min/1.73 m2.
The Calibration curves illustrated the model’s accuracy in the prediction of eGFR <60 mL/min/1.73 m2 at 1 year. The calibration curve, shown in
Calibration curves to predict 1-year postoperative eGFR. The
In this study, the predictive model developed at Toulouse-Rangueil (
LDKT is considered safe, but some donors will develop CKD. And, rarely, ESRD. Two landmark studies in the living kidney donation (
The evaluation of the glomerular filtration rate is a crucial point in LKD. We used eGFR based on serum creatinine determinations because it is feasible and is the most common method worldwide (
The risk of ESRD in living donors, although marginal, was evidenced in two studies in comparison with healthy controls (
Benoit et al. (
At the original cohort (
Most of our living donors were females (71%). Women are more likely than men to become living kidney donors (
We must recognize the limitations associated with this study, beginning with its retrospective and observational design. Thirty-one donors were excluded from the study because 1-year serum creatinine was unavailable to calculate eGFR. Still, later creatinine values were available and were not different from the rest of the cohort. We assume it would not compromise the results of our validation cohort. All patients were Caucasians, but they were representative of the Portuguese population. Other races and ethnic origins are not represented. We used CKD-EPI to calculate eGFR and not an isotopic method. However, we must point out the unsuitability of the latter in clinical practice, as it is not recommended as a standard of care by current guidelines (
The primary goal in assessing a living donor candidate must ensure minimal risk to the donor. Hence, the prediction of postoperative renal function is a critical point in their evaluation and, in our population, can be achieved with this tool. Furthermore, the required variables are low-cost and easily assessed, so its potential as a counseling tool is undeniable. We recall, however, that validation out of Europe is lacking and that further studies are necessary to validate prognostic models for longer-term prediction of donor kidney function.
The formula developed in Toulouse-Rangueil was successfully validated in our cohort, a different European population than previously described. We must, anyway, emphasize that the optimal value of predicted eGFR was around 5 mL/min higher than the equality cutoff for CKD detection at 1 year. This model represents a simple and accurate tool that may be used to assist in the evaluation of potential donors, particularly in the current setting of increasing donor age, donors with minor comorbidities, or renal function close to the accepted threshold.
The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.
The studies involving human participants were reviewed and approved by the Ethics board of Centro Hospitalar Universitario do Porto (CHUPorto) [Ref.: 147-21 (119-DEFI/122-CE)]. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.
MA, CC, and JM: Research design, data acquisition, data analysis, and paper writing. CS, CF, SV, JS, SC, and SP were engaged in the data acquisition and analysis. MR and LM were involved in the research design and data analysis. All the authors approved the submitted version.
This work was supported by
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
AUC, area under the curve; BMI, body mass index; CI, confidence interval; CITL, calibration in the large; CKD, chronic kidney disease; CKD-EPI, chronic kidney disease epidemiology collaboration; ESRD, end-stage renal disease; eGFR, estimated glomerular filtration rate; GFR, glomerular filtration rate; LKD, living kidney donor; MDRD, modification of diet in renal disease; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating characteristic; SD, standard deviation.