Impact of the individualized risks of end-stage renal disease on living kidney donor selection

Impact of the individualized risks of end-stage renal disease on living kidney donor selection Abstract Background It is recommended to determine the risks of end-stage renal disease (ESRD) in living donor candidates. The aim of this study was to determine how many candidates would have been cleared for donation according to different thresholds of risks. Methods Four pre-donation and post-donation risks of ESRD were calculated retrospectively using online tools (http://www.transplantmodels.com/) and the calculator of the University of Minnesota for 151 living kidney donors and 27 patients disqualified for living donation based on a glomerular filtration rate (GFR) <80 mL/min/1.73 m2. Results A complete overlap of the pre-donation 15-year ESRD risk, pre-donation projected lifetime ESRD risk, post-donation 15-year ESRD risk and the Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 was observed for the living kidney donors and the disqualified candidates. We next defined different thresholds of pre- and post-donation risks of ESRD that could be used for clearing living donation. In candidates over 61 years of age, the use of a pre-donation 15-year ESRD risk of 0.25% and/or a post-donation 15-year ESRD risk of 50 per 10 000 would increase the percentage of donors by 28.6% and 26.3%, respectively. Conversely, only 22.3% of donors aged 18–35 years would have been selected by using a pre-donation projected lifetime ESRD risk <0.5%. Conclusions The use of these ESRD risks would significantly modify donor selection by increasing the percentage of donors ≥61 years of age with GFR <80 mL/min/1.73 m2 and by decreasing the percentage of donors aged 18–35 years with a high GFR. end-stage renal disease, kidney, living donation, risk, transplantation INTRODUCTION The selection of candidates for living kidney donation is a major challenge. To date, the evaluation of post-donation kidney function is based principally upon glomerular filtration rates (GFRs). National (Australia, France, Japan and the UK) and international guidelines recommend a threshold of GFR <80 mL/min/1.73 m2 for contraindicated living kidney donations [1, 2]. Despite this general rule, recent studies have reported an increased risk of end-stage renal disease (ESRD) in living kidney donors when compared with selected controls [3–5] Recently, an online calculator for assessing the pre-donation 15-year and projected lifetime ESRD risks has been developed by Grams et al. [3], which is based on the assessment of several risk factors of renal disease, including age, gender, race, systolic blood pressure, hypertension medication, body mass index (BMI), non-insulin-dependent diabetes, smoking history and evaluation of renal function. Two other online calculators for assessing the post-donation ESRD risk have also been developed: the first one by Ibrahim et al. at the University of Minnesota [6], followed by Massie et al. from the Scientific Registry of Transplant Recipients (SRTR) [7]. Therefore, the risk of ESRD can be calculated by using these new tools upon evaluation for each living kidney donor candidate. The Kidney Disease: Improving Global Outcomes (KDIGO) guidelines recommend that each transplant centre develops a quantitative threshold of ‘acceptable risk’ for ESRD after donation [8, 9]. However, to date, no consensual threshold of ESRD risk has been identified as acceptable for clearing living kidney donation. We then decided to describe the impact of different thresholds of ESRD risk on both the percentage and the age of candidates cleared for donation. The objectives of our study were then: (i) to retrospectively compare the pre- and post-donation risks of ESRD between a cohort of living kidney donors and a cohort of candidates disqualified based on a GFR <80 mL/min/1.73 m2, so as (ii) to determine how many living kidney candidates would have been cleared for donation for each threshold of ESRD risk and (iii) to determine the impact of different thresholds of ESRD risk on the age of the selected living kidney donors. MATERIALS AND METHODS Study design The 486 kidney donor candidates evaluated at our centre between 2004 and 2015 were retrospectively included (Figure 1). Among them, 220 were excluded for subsequent kidney donation because of ABO incompatibility, the presence of preformed donor-specific antibodies in the recipient or poor HLA matching. According to the French recommendations of the Agence de Biomédecine [1], 88 donors were also excluded from donation. FIGURE 1 View largeDownload slide Study flow chart. FIGURE 1 View largeDownload slide Study flow chart. In France, candidates with a GFR <80 mL/min/1.73 m2 or <2 SDs below the eGFR normal value for age and sex must be excluded for living kidney donation [1]. Based on these recommendations, 151 candidates were considered as having an acceptable level of kidney function for subsequent kidney donation, while 27 were disqualified. This study was approved by the Institutional Review Board of the Bordeaux University Hospital. Evaluation of the GFR Initial evaluation of GFR in living donor candidates was performed using an estimated GFR (eGFR), which was computed using the 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equations [9]. The reference test used at our centre for evaluating their kidney function was a measured GFR (mGFR), performed using urinary or plasma clearance of 51Cr-EDTA. Based on the French recommendations [1], mGFR was not performed in candidates under 50 years of age who had a 2009 CKD-EPI eGFR >100 mL/min/1.73 m2. One hundred and thirty-nine out of the 151 living kidney donors (92%) and 24 out of the 27 disqualified candidates (89%) had an mGFR (P = 0.6). The others only had an eGFR (CKD-EPI). Calculation of the pre- and post-donation risks of kidney failure The pre-donation 15-year and the projected lifetime ESRD risks were calculated retrospectively using the online ESRD Risk Tool for Kidney Donor Candidates (http://www.transplantmodels.com/esrdrisk/) for the 178 candidates [3]. The risk was calculated using the mGFR (51Cr-EDTA), and the systolic blood pressure measured upon the first visit. In the absence of mGFR, the score was calculated with the CKD-EPI eGFR. The SRTR post-donation 15-year ESRD risk was calculated using the online tool of Massie et al. (http://www.transplantmodels.com/donesrd/) [7]. The Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 was calculated using the Excel tool of Ibrahim et al. [6]. The main strengths and limits of those available ESRD risk calculators are depicted in Table 1. Table 1 Strengths and limits of available ESRD risk calculators ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  Table 1 Strengths and limits of available ESRD risk calculators ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  Statistical analysis Variables were expressed using mean and SDs or median and range and then compared using Student’s t-test or the Mann–Whitney U-test, when appropriate. Categorical variables were expressed using percentages and compared using Chi-squared tests. All tests were two-sided and a P-value ≤0.05 was considered statistically significant. Statistical analyses were performed using JMP (SAS, version 11.0). RESULTS Patients’ characteristics Demographic characteristics of the living kidney donors and disqualified candidates are described in Table 2. Briefly, the median GFR of the 151 living kidney donors and the 27 disqualified candidates were 98 mL/min/1.73 m2 (range: 78–156) and 71 mL/min/1.73 m2 (range: 58–81), respectively (Figure 2A). A single donor had an mGFR <80 mL/min/1.73 m2 (78 mL/min/1.73 m2); however, his non-adjusted mGFR was 82 mL/min. Two candidates were disqualified for kidney donation despite an mGFR at 80 and 81 mL/min/1.73 m2. The first candidate was disqualified because he was only 36 years old, and the second candidate because of a non-adjusted mGFR at 69 mL/min. Table 2 Population characteristics   Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)      Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)    Table 2 Population characteristics   Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)      Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)    FIGURE 2 View largeDownload slide GFR distribution for the 151 living kidney donors and the 27 disqualified candidates (A). Distribution of the candidates’ pre-donation 15-year ESRD risk (B). Distribution of the candidates’ pre-donation projected lifetime ESRD risk (C). Distribution of the candidates’ SRTR post-donation 15-year ESRD risk (D). Distribution of the Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (E). Due to insufficient data, the pre-donation 15-year and projected lifetime risks of kidney failure were not calculated for 8 of the 27 disqualified candidates and 4 of the 151 living kidney donors. Also, due to insufficient data, the post-donation risks were not calculated for 2 of the 27 disqualified candidates and 1 of the 151 living kidney donors. FIGURE 2 View largeDownload slide GFR distribution for the 151 living kidney donors and the 27 disqualified candidates (A). Distribution of the candidates’ pre-donation 15-year ESRD risk (B). Distribution of the candidates’ pre-donation projected lifetime ESRD risk (C). Distribution of the candidates’ SRTR post-donation 15-year ESRD risk (D). Distribution of the Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (E). Due to insufficient data, the pre-donation 15-year and projected lifetime risks of kidney failure were not calculated for 8 of the 27 disqualified candidates and 4 of the 151 living kidney donors. Also, due to insufficient data, the post-donation risks were not calculated for 2 of the 27 disqualified candidates and 1 of the 151 living kidney donors. All the patients were Caucasians, except for three living kidney donors. Disqualified candidates were more frequently female (88.9% versus 61%, P = 0.005), older (58 ± 7 versus 48.9 ± 11 years of age, P = 0.0001), with higher systolic blood pressure (133 ± 15 versus 126 ± 14, P = 0.04) and higher BMI (28.5 ± 4.6 versus 25.3 ± 4.0, P = 0.0005) than living kidney donors. Pre- and post-donation ESRD risks As expected, the median pre-donation 15-year ESRD risk was higher in disqualified candidates than in living kidney donors [0.15% (range: 0.07–0.3%) versus 0.08% (range: 0.02–0.31%), respectively, P = 0.0001] (Figure 2B). However, the median pre-donation projected lifetime ESRD risk was similar between disqualified candidates and living kidney donors [0.32% (range: 0.14–1.07%) versus 0.31% (range: 0.04–1.8%), respectively, P = 0.6] (Figure 2C). The correlations between mGFR and both pre-donation 15-year and projected lifetime ESRD risks were poor (r2=0.06, P = 0.0024 and r2=0.13, P < 0.001, respectively). The SRTR post-donation 15-year ESRD risk was higher in disqualified candidates than in living kidney donors, but the difference was not statistically significant [23.7 cases per 10 000 donors (range: 9.6–55.6) versus 17.4 cases per 10 000 donors (range: 3.4–96.2), respectively, P = 0.07] (Figure 2D). The correlation between GFR and the SRTR risk was poor (r2=0.003, P = 0.5). Finally, the Minnesota post-donation 15-year risk of ESRD or GFR < 30 mL/min/1.73 m2 was also higher in disqualified candidates than in living kidney donors [2.1% (range: 0–5.5%) versus 1.7% (range: 0–3.9%), P = 0.009] (Figure 2E). The correlation between GFR and the Minnesota risk was also poor (r2=0.16, P = 0.0001). Testing different thresholds of pre- and post-donation ESRD risks for living donation candidates By using the GFR threshold of 80 mL/min/1.73 m2 recommended in France for the selection of kidney donors, 84.8% of candidates (151/178) were cleared for living donation at our centre (Figure 3). We next defined different thresholds of pre- and post-donation risks of ESRD that could be used for clearing living donations. To determine their impact, we applied these thresholds to our whole cohort of candidates. FIGURE 3 View largeDownload slide Distribution of the candidates cleared for donation according to different thresholds of pre- and post-donation ESRD risks. FIGURE 3 View largeDownload slide Distribution of the candidates cleared for donation according to different thresholds of pre- and post-donation ESRD risks. By using thresholds of pre-donation 15-year ESRD risk at 0.25% and 0.5%, respectively, 95.8% and 100% of donor candidates would have been cleared for living donation. By using thresholds of pre-donation projected lifetime ESRD risk at 0.25, 0.5, 1 and 2%, respectively, 41, 75.3, 96.4 and 100% of donor candidates would have been cleared for kidney donation. By using thresholds of SRTR post-donation 15-year ESRD risk at 25, 50 and 100 per 10 000 donors, respectively, 69.7, 92.6 and 100% of donor candidates would have been cleared for living donation. By using thresholds of Minnesota post-donation 15-year risk at 1, 2, 3 and 6%, respectively, 37, 50, 93 and 100% of donor candidates would have been cleared for living donation. Pre-donation 15-year ESRD risk according to age Our final objective was to determine the impact of these different thresholds of ESRD risk on the age of those candidates cleared for donation. The median pre-donation 15-year ESRD risk increased significantly with age. It was at 0.04, 0.06, 0.10 and 0.12% for candidates aged 18–35, 36–50, 51–60 and ≥61 years, respectively (P = 0.0001). The use of a threshold of pre-donation 15-year ESRD risk at 0.25% was associated with an increase in the percentage of candidates cleared for living donation when compared with the use of the GFR threshold recommended in France, among those aged 36–50 years (98.2% versus 91.7%), 51–60 years (96.9% versus 87.7%) and ≥61 years (86.2% versus 57.6%) (Figure 4A). The use of a threshold at 0.5% was associated with 100% of candidates being cleared for living donation, for each age category. FIGURE 4 View largeDownload slide Distribution of the candidates cleared for donation according to age categories and different thresholds of pre-donation 15-year ESRD risk (A), pre-donation projected lifetime ESRD risk (B), SRTR post-donation 15-year risk of ESRD (C) and Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (D). FIGURE 4 View largeDownload slide Distribution of the candidates cleared for donation according to age categories and different thresholds of pre-donation 15-year ESRD risk (A), pre-donation projected lifetime ESRD risk (B), SRTR post-donation 15-year risk of ESRD (C) and Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (D). Pre-donation projected lifetime ESRD risk according to age Conversely, the pre-donation projected lifetime ESRD risk was higher in younger candidates. It was 0.62, 0.34, 0.26 and 0.21% for candidates aged 18–35, 36–50, 51–60 and ≥61 years, respectively (P = 0.0001). The use of a threshold of pre-donation projected lifetime ESRD risk at 0.25% was associated with a major decrease in the percentages of candidates allowed to donate when compared with the use of the GFR threshold recommended in France, among those aged 18–35 years (5.6% versus 100%), 36–50 years (32.7% versus 91.7%) and 51–60 years (48.4% versus 87.7%) (Figure 4B). The use of a threshold at 0.5% was associated with a decrease in the percentages of candidates cleared for living donation among those aged 18–35 years (22.3% versus 100%) and 36–50 years (70.9% versus 91.7%), but an increase among those aged ≥61 years (86.2% versus 57.6%). The use of a threshold at 1% was associated with a slight decrease in the percentage of candidates cleared for living donation among those aged 18–35 years (83.3% versus 100%), but an increase among those aged 51–60  years (98.4% versus 87.7%) and ≥61 years (100% versus 57.6%). SRTR post-donation 15-year ESRD risk according to age The median SRTR post-donation 15-year ESRD risk increased significantly with age. It was at 15.5, 12.1, 21.2 and 27.1 per 10 000 for candidates aged, respectively, 18–35, 36–50, 51–60 and ≥61 years (P = 0.0001). The use of a threshold of SRTR post-donation 15-year ESRD risk at 25 per 10 000 donors was associated with a decrease in the percentage of candidates cleared for living donation among all age categories (Figure 4C). The use of a threshold at 50 per 10 000 donors was associated with an increase in the percentage of candidates cleared for living donation among those aged ≥61 years (83.9% versus 57.6%). The use of a threshold at 100 per 10 000 donors was associated with 100% of candidates being cleared for living donation, for each age category. Minnesota post-donation 15-year risk of ESRD or GFR < 30mL/min/1.73 m2 according to age The median Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 increased significantly with age (P = 0.0001). The use of a threshold at 1% or 2% was associated with a dramatic decrease in the percentage of candidates cleared for living donation among those aged >35 years (Figure 4D). The use of a threshold at 3% was associated with an increase in the percentage of candidates cleared for living donation among those aged ≥61 years (90% versus 57.6%). The use of a threshold at 6% was associated with 100% of candidates being cleared for living donation, for each age category. DISCUSSION Until recently, most guidelines have considered a GFR threshold of 80 mL/min/1.73 m2 as acceptable for authorizing subsequent living donations. To date, the KDIGO recommend that the evaluation of living donor candidates should include the determination of the pre- and post-donation risks of ESRD, which are based on a composite profile of many risk factors [8, 9]. Our study demonstrates that the use of these ESRD risks would significantly modify donor selection by increasing the percentage of candidates cleared for living donation among those aged ≥61 years and by decreasing the percentage of cleared candidates aged 18–35 years. For assessing individualized pre- and post-donation ESRD risks, we used the tools that have been developed based on seven general population cohorts, the SRTR and at the University of Minnesota [6, 7]. As previously observed by Gaillard et al. [10], we also observed a complete overlap in the pre- and post-donation ESRD risks for living kidney donors and disqualified candidates. Moreover, the median pre-donation projected lifetime ESRD risk was similar for both groups. This last observation demonstrates that risk factors of kidney disease, such as age, race or systolic blood pressure, can increase the level of pre-donation lifetime ESRD risks in patients with high GFR. It also suggests that integration of these risks would significantly influence the selection of candidates, regardless of the particular threshold of ESRD risk chosen for clearing living kidney donations. It has been reported that the estimated 15-year risk of ESRD was 3.9 per 10 000 (95% confidence interval 0.8–8.9) for healthy non-donors [8]. Defining an arbitrary threshold for clearing donations is difficult and raises ethical questions. Choosing donors whose post-donation ESRD risk is comparable to that of the general public is readily accepted, but choosing donors with an acceptable higher risk could also be considered. Moreover, the presence of risk does not necessarily mean that the event will occur. Some candidates could also be less prone than others to accepting the same level of ESRD risk. For instance, it has been observed that 43% of potential donors would accept a 20-year incidence of kidney failure 100 times higher than the estimated risk of ESRD, whereas only 11% of recipients and 6% of transplant professionals would accept donations with such a level of risk [11]. In the absence of any clear threshold for clearing donations, these figures could also be used as an educational tool for improving the quality of donor information and reaching a common decision. However, physicians must keep in mind that statistics or medical risks are sometimes difficult to apprehend for candidates who made the decision to donate prior to having been exposed to this information [12]. The main objective of our study was to determine how many living kidney candidates would be accepted or declined for each threshold of pre- and post-donation ESRD risk. Thresholds of pre-donation 15-year ESRD risk >0.25%, pre-donation projected lifetime ESRD risk at 1% and SRTR post-donation 15-year ESRD risk >50 per 10 000 donors were associated with the clearance of >90% of the candidates. Conversely, thresholds of pre-donation lifetime ESRD risk at 0.25% and SRTR post-donation 15-year ESRD risk at 25 per 10 000 donors led to, respectively, only 41% and 69.7% of candidates being cleared for donation, suggesting that a small variation in the acceptance threshold would significantly modify the proportion of candidates accepted as living kidney donors. It is important to point out that we do not recommend choosing the cut-off for clearing donations based on this utilitarian principle in order to increase the pool of donors. The principle of non-maleficence is of the utmost importance if we want to minimize the long-term ESRD risk in living donor candidates. The pre- and post-donation 15-year ESRD risks were calculated based on retrospective cohorts [3, 7]. Although useful, these estimates may not fully capture the relevant risks among young donors, who may have >60 years of remaining life. For this reason, these 15-year ESRD risks could be interesting only for candidates >60 years of age. Using the pre-donation ESRD risk would increase the percentage of candidates cleared for living donation among those aged ≥61 years by 28.6% for a cut-off at 0.25% and 42.4% for a cut-off at 0.5%. Using the SRTR post-donation, ESRD risk could also increase the percentage of candidates cleared for living donation among those aged ≥61 years by 26.3% for a cut-off at 50 and 42.4% for a cut-off at 100. A similar result would be observed with the Minnesota post-donation risk for a cut-off at 3%. These observations are in accordance with the perspective of the ERA-EDTA DESCARTES working group, which recently proposed encouraging the evaluation of older donors [13]. Grams et al. [3] also provided a projected lifetime risk of kidney failure, with the caveat that this estimate lacks precision. Despite this drawback, the projected lifetime risk has a much stronger clinical relevance than the 15-year risk of kidney failure for young donors. The use of cut-offs <1% would significantly decrease the percentage of candidates cleared for living donation among those aged 18–35 years. For instance, only 5.6% and 22.3% of candidates displayed a pre-donation projected lifetime ESRD risk <0.25% or 0.5%, respectively. These results suggest that most young candidates could not be considered as living kidney donors if the acceptance threshold of pre-donation projected lifetime ESRD risk is set at 0.25% or 0.5% [3, 14]. These data based on the projected lifetime ESRD risk should be interpreted with caution, since Ibrahim et al. reported that 40 years after donation, high post-donation GFRs were also associated with high pre-donation GFRs, suggesting that young donors with a high GFR still had excellent kidney function 40 years after donation [6]. It will take decades to clarify the long-term renal outcome of young donors. In the future, we may suppose that genetics and social or environmental risks could also be considered so as to improve the reliability of the post-donation risk of kidney failure. The genetic background analysis seems particularly important. For instance, the two variants G1 and G2 of the APOL1 gene, which are found primarily in populations with African ancestry, are associated with various forms of kidney disease and kidney disease progression [15]. Although the functional role of APOL1 within the cells of the kidney is still unknown [16], kidneys from African American deceased donors with these two APOL1 nephropathy variants are also associated with a higher risk for allograft failure [17–19]. Moreover, the high risk for chronic kidney disease observed in the potential young African American living donors could be driven in part by these two APOL1 renal-risk variants [20]. Screening of these two high-risk APOL1 alleles in young African American potential living kidney donors may then help to better determine ESRD risk [21, 22]. Finally, the main limitation of this study is its overestimating ESRD risks for French candidates using these online calculators, due to a lower incidence of ESRD in France compared with the USA (150 versus 400 cases per million inhabitants, respectively) [23]. In summary, integrating the pre- and post-donation ESRD risks in the evaluation of candidates would allow older candidates with GFR <80 mL/min/1.73 m2 to be reclassified as living kidney donors, while excluding some young donors despite high GFR. However, defining an acceptance threshold of lifetime ESRD risk is a difficult task, which should not run counter to the principle ‘primum non nocere.’ ACKNOWLEDGEMENTS The authors would like to thank our department’s donor coordinators, Catherine Rio and Sandrine Dumartin, for their precious help and professionalism. AUTHORS’ CONTRIBUTIONS Q.-L.N., P.M. and L.C. designed the study, carried out the analyses, interpreted the data and wrote the manuscript. CONFLICT OF INTEREST STATEMENT None declared. REFERENCES 1 Living kidney donation recommendations - Biomedicine Agency, 2016. https://www.agence-biomedecine.fr/IMG/pdf/2009_reco_formalisees_experts_pvlt_greffe_donneurs_vivants_complet.pdf (16 may 2018, date last accessed) 2 United Kingdom Guidelines. Living Donor Kidney Transplantation. 2011. https://bts.org.uk/wp-content/uploads/2016/09/19_BTS_RA_Living_Donor_Kidney-1.pdf (16 may 2018, date last accessed) 3 Grams ME, Sang Y, Levey AS et al.   Kidney-failure risk projection for the living kidney-donor candidate. N Engl J Med  2016; 374: 411– 421 Google Scholar CrossRef Search ADS PubMed  4 Muzaale AD, Massie AB, Wang M-C et al.   Risk of end-stage renal disease following live kidney donation. JAMA  2014; 311: 579– 586 Google Scholar CrossRef Search ADS PubMed  5 Mjoen G, Hallan S, Hartmann A et al.   Long-term risks for kidney donors. Kidney Int  2014; 86: 162– 167 Google Scholar CrossRef Search ADS PubMed  6 Ibrahim HN, Foley RN, Reule SA et al.   Renal function profile in white kidney donors: the first 4 decades. J Am Soc Nephrol  2016; 27: 2885– 2893 Google Scholar PubMed  7 Massie AB, Muzaale AD, Luo X et al.   Quantifying postdonation risk of ESRD in living kidney donors. J Am Soc Nephrol  2017; 28: 2749– 2755 Google Scholar CrossRef Search ADS PubMed  8 Lentine KL, Kasiske BL, Levey AS et al.   KDIGO clinical practice guideline on the evaluation and care of living kidney donors. Transplantation  2017; 101 (8S Suppl 1): S1– 109 9 Levey AS, Inker LA. GFR evaluation in living kidney donor candidates. J Am Soc Nephrol  2017; 28: 1062– 1071 Google Scholar CrossRef Search ADS PubMed  10 Gaillard F, Baron S, Timsit M-O et al.   What is the significance of end-stage renal disease risk estimation in living kidney donors? Transpl Int  2017; 30: 799– 806 Google Scholar CrossRef Search ADS PubMed  11 Young A, Karpinski M, Treleaven D et al.   Differences in tolerance for health risk to the living donor among potential donors, recipients, and transplant professionals. Kidney Int  2008; 73: 1159– 1166 Google Scholar CrossRef Search ADS PubMed  12 Stothers L, Gourlay WA, Liu L. Attitudes and predictive factors for live kidney donation: a comparison of live kidney donors versus nondonors. Kidney Int  2005; 67: 1105– 1111 Google Scholar CrossRef Search ADS PubMed  13 Maggiore U, Budde K, Heemann U et al.   Long-term risks of kidney living donation: review and position paper by the ERA-EDTA DESCARTES working group. Nephrol Dial Transplant  2017; 32: 216– 223 Google Scholar CrossRef Search ADS PubMed  14 Steiner RW. ‘Normal for Now’ or ‘At Future Risk’: a double standard for selecting young and older living kidney donors. Am J Transplant  2010; 10: 737– 741 Google Scholar CrossRef Search ADS PubMed  15 Foster MC, Coresh J, Fornage M et al.   APOL1 variants associate with increased risk of CKD among African Americans. J Am Soc Nephrol  2013; 24: 1484– 1491 Google Scholar CrossRef Search ADS PubMed  16 O’Toole JF, Schilling W, Kunze D et al.   ApoL1 overexpression drives variant-independent cytotoxicity. J Am Soc Nephrol  2017; 29: 869– 879 Google Scholar PubMed  17 Reeves-Daniel AM, Depalma JA, Bleyer AJ et al.   The APOL1 gene and allograft survival after kidney transplantation. Am J Transplant  2011; 11: 1025– 1030 Google Scholar CrossRef Search ADS PubMed  18 Freedman BI, Julian BA, Pastan SO et al.   Apolipoprotein L1 gene variants in deceased organ donors are associated with renal allograft failure. Am J Transplant  2015; 15: 1615– 1622 Google Scholar CrossRef Search ADS PubMed  19 Freedman BI, Pastan SO, Israni AK et al.   APOL1 genotype and kidney transplantation outcomes from deceased African American donors. Transplantation  2016; 100: 194– 202 Google Scholar CrossRef Search ADS PubMed  20 Locke JE, Sawinski D, Reed RD et al.   Apolipoprotein L1 and chronic kidney disease risk in young potential living kidney donors. Ann Surg  2017; 267 (6): 1161– 1168 21 Freedman BI, Julian BA. Should kidney donors be genotyped for APOL1 risk alleles? Kidney Int  2015; 87: 671– 673 Google Scholar CrossRef Search ADS PubMed  22 Riella LV, Sheridan AM. Testing for high-risk APOL1 alleles in potential living kidney donors. Am J Kidney Dis  2015; 66: 396– 401 Google Scholar CrossRef Search ADS PubMed  23 Levey AS, Coresh J. Chronic kidney disease. Lancet  2012; 379: 165– 180 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nephrology Dialysis Transplantation Oxford University Press

Impact of the individualized risks of end-stage renal disease on living kidney donor selection

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
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0931-0509
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1460-2385
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10.1093/ndt/gfy145
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Abstract

Abstract Background It is recommended to determine the risks of end-stage renal disease (ESRD) in living donor candidates. The aim of this study was to determine how many candidates would have been cleared for donation according to different thresholds of risks. Methods Four pre-donation and post-donation risks of ESRD were calculated retrospectively using online tools (http://www.transplantmodels.com/) and the calculator of the University of Minnesota for 151 living kidney donors and 27 patients disqualified for living donation based on a glomerular filtration rate (GFR) <80 mL/min/1.73 m2. Results A complete overlap of the pre-donation 15-year ESRD risk, pre-donation projected lifetime ESRD risk, post-donation 15-year ESRD risk and the Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 was observed for the living kidney donors and the disqualified candidates. We next defined different thresholds of pre- and post-donation risks of ESRD that could be used for clearing living donation. In candidates over 61 years of age, the use of a pre-donation 15-year ESRD risk of 0.25% and/or a post-donation 15-year ESRD risk of 50 per 10 000 would increase the percentage of donors by 28.6% and 26.3%, respectively. Conversely, only 22.3% of donors aged 18–35 years would have been selected by using a pre-donation projected lifetime ESRD risk <0.5%. Conclusions The use of these ESRD risks would significantly modify donor selection by increasing the percentage of donors ≥61 years of age with GFR <80 mL/min/1.73 m2 and by decreasing the percentage of donors aged 18–35 years with a high GFR. end-stage renal disease, kidney, living donation, risk, transplantation INTRODUCTION The selection of candidates for living kidney donation is a major challenge. To date, the evaluation of post-donation kidney function is based principally upon glomerular filtration rates (GFRs). National (Australia, France, Japan and the UK) and international guidelines recommend a threshold of GFR <80 mL/min/1.73 m2 for contraindicated living kidney donations [1, 2]. Despite this general rule, recent studies have reported an increased risk of end-stage renal disease (ESRD) in living kidney donors when compared with selected controls [3–5] Recently, an online calculator for assessing the pre-donation 15-year and projected lifetime ESRD risks has been developed by Grams et al. [3], which is based on the assessment of several risk factors of renal disease, including age, gender, race, systolic blood pressure, hypertension medication, body mass index (BMI), non-insulin-dependent diabetes, smoking history and evaluation of renal function. Two other online calculators for assessing the post-donation ESRD risk have also been developed: the first one by Ibrahim et al. at the University of Minnesota [6], followed by Massie et al. from the Scientific Registry of Transplant Recipients (SRTR) [7]. Therefore, the risk of ESRD can be calculated by using these new tools upon evaluation for each living kidney donor candidate. The Kidney Disease: Improving Global Outcomes (KDIGO) guidelines recommend that each transplant centre develops a quantitative threshold of ‘acceptable risk’ for ESRD after donation [8, 9]. However, to date, no consensual threshold of ESRD risk has been identified as acceptable for clearing living kidney donation. We then decided to describe the impact of different thresholds of ESRD risk on both the percentage and the age of candidates cleared for donation. The objectives of our study were then: (i) to retrospectively compare the pre- and post-donation risks of ESRD between a cohort of living kidney donors and a cohort of candidates disqualified based on a GFR <80 mL/min/1.73 m2, so as (ii) to determine how many living kidney candidates would have been cleared for donation for each threshold of ESRD risk and (iii) to determine the impact of different thresholds of ESRD risk on the age of the selected living kidney donors. MATERIALS AND METHODS Study design The 486 kidney donor candidates evaluated at our centre between 2004 and 2015 were retrospectively included (Figure 1). Among them, 220 were excluded for subsequent kidney donation because of ABO incompatibility, the presence of preformed donor-specific antibodies in the recipient or poor HLA matching. According to the French recommendations of the Agence de Biomédecine [1], 88 donors were also excluded from donation. FIGURE 1 View largeDownload slide Study flow chart. FIGURE 1 View largeDownload slide Study flow chart. In France, candidates with a GFR <80 mL/min/1.73 m2 or <2 SDs below the eGFR normal value for age and sex must be excluded for living kidney donation [1]. Based on these recommendations, 151 candidates were considered as having an acceptable level of kidney function for subsequent kidney donation, while 27 were disqualified. This study was approved by the Institutional Review Board of the Bordeaux University Hospital. Evaluation of the GFR Initial evaluation of GFR in living donor candidates was performed using an estimated GFR (eGFR), which was computed using the 2009 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equations [9]. The reference test used at our centre for evaluating their kidney function was a measured GFR (mGFR), performed using urinary or plasma clearance of 51Cr-EDTA. Based on the French recommendations [1], mGFR was not performed in candidates under 50 years of age who had a 2009 CKD-EPI eGFR >100 mL/min/1.73 m2. One hundred and thirty-nine out of the 151 living kidney donors (92%) and 24 out of the 27 disqualified candidates (89%) had an mGFR (P = 0.6). The others only had an eGFR (CKD-EPI). Calculation of the pre- and post-donation risks of kidney failure The pre-donation 15-year and the projected lifetime ESRD risks were calculated retrospectively using the online ESRD Risk Tool for Kidney Donor Candidates (http://www.transplantmodels.com/esrdrisk/) for the 178 candidates [3]. The risk was calculated using the mGFR (51Cr-EDTA), and the systolic blood pressure measured upon the first visit. In the absence of mGFR, the score was calculated with the CKD-EPI eGFR. The SRTR post-donation 15-year ESRD risk was calculated using the online tool of Massie et al. (http://www.transplantmodels.com/donesrd/) [7]. The Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 was calculated using the Excel tool of Ibrahim et al. [6]. The main strengths and limits of those available ESRD risk calculators are depicted in Table 1. Table 1 Strengths and limits of available ESRD risk calculators ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  Table 1 Strengths and limits of available ESRD risk calculators ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  ESRD risk  Population  Strengths  Limits  Pre-donation 15-year (Grams et al. [3])  Candidates  Calculated based on a large retrospective multicentric cohort  May not fully capture the relevant risks among young donors  Pre-donation projected lifetime (Grams et al. [3])  Candidates  Capture the long-term ESRD risk  May lack precision  SRTR post-donation 15-year (Massie et al. [7])  Donors  Calculated based on a large retrospective multicentric cohort  Applicable only in patients cleared for donation  May not fully capture the relevant risks among young donors  Minnesota post-donation 15-year (Ibrahim et al. [6])  Donors  Calculated based on a retrospective cohort  Applicable only in patients cleared for donation  Include a risk of reaching a GFR <30 mL/min/1.73 m2  Developed in a single centre  Statistical analysis Variables were expressed using mean and SDs or median and range and then compared using Student’s t-test or the Mann–Whitney U-test, when appropriate. Categorical variables were expressed using percentages and compared using Chi-squared tests. All tests were two-sided and a P-value ≤0.05 was considered statistically significant. Statistical analyses were performed using JMP (SAS, version 11.0). RESULTS Patients’ characteristics Demographic characteristics of the living kidney donors and disqualified candidates are described in Table 2. Briefly, the median GFR of the 151 living kidney donors and the 27 disqualified candidates were 98 mL/min/1.73 m2 (range: 78–156) and 71 mL/min/1.73 m2 (range: 58–81), respectively (Figure 2A). A single donor had an mGFR <80 mL/min/1.73 m2 (78 mL/min/1.73 m2); however, his non-adjusted mGFR was 82 mL/min. Two candidates were disqualified for kidney donation despite an mGFR at 80 and 81 mL/min/1.73 m2. The first candidate was disqualified because he was only 36 years old, and the second candidate because of a non-adjusted mGFR at 69 mL/min. Table 2 Population characteristics   Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)      Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)    Table 2 Population characteristics   Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)      Living kidney donors (n = 151)  Disqualified donor candidates (n = 27)  P-value  Sex, n (%)      0.005   Male  59 (39)  3 (11.1)     Female  92 (61)  24 (88.9)    Age, n (%)   18–35 years old  20 (13.2)  0     36–50 years old  55 (36.4)  5 (18.5)     51–60 years old  57(37.4)  8 (29.6)     ≥61 years old  19 (12.6)  14 (51.8)     Means ± SD  48.9 ± 11  58.0 ± 7  0.0001  Medication for hypertension, n (%)      0.13   Yes  19 (12.6)  6 (22.2)     No  132 (87.4)  19 (70.3)    Systolic blood pressure at the first visit (mmHg)   Mean ± SD  126 ± 14  133 ± 15  0.04   No data, n (%)  16 (10.6)  6 (22.2)    Diastolic blood pressure at the first visit (mmHg)   Mean ± SD  79.4 ± 10  82.8 ± 8  0.12   No data, n (%)  17 (11.2)  6 (22.2)    Body mass index         Mean ± SD  25.3 (±4.0)  28.5 (±4.6)  0.0005   No data, n (%)  1 (<0.1)  2 (7.4)    Smoking history n (%)      0.57   No  84 (55.6)  16 (59.2)     Current  35 (23.2)  4 (14.8)     Former  31 (20.5)  4 (14.8)     No data  1 (<0.1)  3 (11.1)    Urine protein to creatinine ratio (mg/mmol)   Mean ± SD  4.0 (±4.6)  7.0 (±4.7)  0.007   No data, n (%)  1 (<1)  6 (22.2)    FIGURE 2 View largeDownload slide GFR distribution for the 151 living kidney donors and the 27 disqualified candidates (A). Distribution of the candidates’ pre-donation 15-year ESRD risk (B). Distribution of the candidates’ pre-donation projected lifetime ESRD risk (C). Distribution of the candidates’ SRTR post-donation 15-year ESRD risk (D). Distribution of the Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (E). Due to insufficient data, the pre-donation 15-year and projected lifetime risks of kidney failure were not calculated for 8 of the 27 disqualified candidates and 4 of the 151 living kidney donors. Also, due to insufficient data, the post-donation risks were not calculated for 2 of the 27 disqualified candidates and 1 of the 151 living kidney donors. FIGURE 2 View largeDownload slide GFR distribution for the 151 living kidney donors and the 27 disqualified candidates (A). Distribution of the candidates’ pre-donation 15-year ESRD risk (B). Distribution of the candidates’ pre-donation projected lifetime ESRD risk (C). Distribution of the candidates’ SRTR post-donation 15-year ESRD risk (D). Distribution of the Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (E). Due to insufficient data, the pre-donation 15-year and projected lifetime risks of kidney failure were not calculated for 8 of the 27 disqualified candidates and 4 of the 151 living kidney donors. Also, due to insufficient data, the post-donation risks were not calculated for 2 of the 27 disqualified candidates and 1 of the 151 living kidney donors. All the patients were Caucasians, except for three living kidney donors. Disqualified candidates were more frequently female (88.9% versus 61%, P = 0.005), older (58 ± 7 versus 48.9 ± 11 years of age, P = 0.0001), with higher systolic blood pressure (133 ± 15 versus 126 ± 14, P = 0.04) and higher BMI (28.5 ± 4.6 versus 25.3 ± 4.0, P = 0.0005) than living kidney donors. Pre- and post-donation ESRD risks As expected, the median pre-donation 15-year ESRD risk was higher in disqualified candidates than in living kidney donors [0.15% (range: 0.07–0.3%) versus 0.08% (range: 0.02–0.31%), respectively, P = 0.0001] (Figure 2B). However, the median pre-donation projected lifetime ESRD risk was similar between disqualified candidates and living kidney donors [0.32% (range: 0.14–1.07%) versus 0.31% (range: 0.04–1.8%), respectively, P = 0.6] (Figure 2C). The correlations between mGFR and both pre-donation 15-year and projected lifetime ESRD risks were poor (r2=0.06, P = 0.0024 and r2=0.13, P < 0.001, respectively). The SRTR post-donation 15-year ESRD risk was higher in disqualified candidates than in living kidney donors, but the difference was not statistically significant [23.7 cases per 10 000 donors (range: 9.6–55.6) versus 17.4 cases per 10 000 donors (range: 3.4–96.2), respectively, P = 0.07] (Figure 2D). The correlation between GFR and the SRTR risk was poor (r2=0.003, P = 0.5). Finally, the Minnesota post-donation 15-year risk of ESRD or GFR < 30 mL/min/1.73 m2 was also higher in disqualified candidates than in living kidney donors [2.1% (range: 0–5.5%) versus 1.7% (range: 0–3.9%), P = 0.009] (Figure 2E). The correlation between GFR and the Minnesota risk was also poor (r2=0.16, P = 0.0001). Testing different thresholds of pre- and post-donation ESRD risks for living donation candidates By using the GFR threshold of 80 mL/min/1.73 m2 recommended in France for the selection of kidney donors, 84.8% of candidates (151/178) were cleared for living donation at our centre (Figure 3). We next defined different thresholds of pre- and post-donation risks of ESRD that could be used for clearing living donations. To determine their impact, we applied these thresholds to our whole cohort of candidates. FIGURE 3 View largeDownload slide Distribution of the candidates cleared for donation according to different thresholds of pre- and post-donation ESRD risks. FIGURE 3 View largeDownload slide Distribution of the candidates cleared for donation according to different thresholds of pre- and post-donation ESRD risks. By using thresholds of pre-donation 15-year ESRD risk at 0.25% and 0.5%, respectively, 95.8% and 100% of donor candidates would have been cleared for living donation. By using thresholds of pre-donation projected lifetime ESRD risk at 0.25, 0.5, 1 and 2%, respectively, 41, 75.3, 96.4 and 100% of donor candidates would have been cleared for kidney donation. By using thresholds of SRTR post-donation 15-year ESRD risk at 25, 50 and 100 per 10 000 donors, respectively, 69.7, 92.6 and 100% of donor candidates would have been cleared for living donation. By using thresholds of Minnesota post-donation 15-year risk at 1, 2, 3 and 6%, respectively, 37, 50, 93 and 100% of donor candidates would have been cleared for living donation. Pre-donation 15-year ESRD risk according to age Our final objective was to determine the impact of these different thresholds of ESRD risk on the age of those candidates cleared for donation. The median pre-donation 15-year ESRD risk increased significantly with age. It was at 0.04, 0.06, 0.10 and 0.12% for candidates aged 18–35, 36–50, 51–60 and ≥61 years, respectively (P = 0.0001). The use of a threshold of pre-donation 15-year ESRD risk at 0.25% was associated with an increase in the percentage of candidates cleared for living donation when compared with the use of the GFR threshold recommended in France, among those aged 36–50 years (98.2% versus 91.7%), 51–60 years (96.9% versus 87.7%) and ≥61 years (86.2% versus 57.6%) (Figure 4A). The use of a threshold at 0.5% was associated with 100% of candidates being cleared for living donation, for each age category. FIGURE 4 View largeDownload slide Distribution of the candidates cleared for donation according to age categories and different thresholds of pre-donation 15-year ESRD risk (A), pre-donation projected lifetime ESRD risk (B), SRTR post-donation 15-year risk of ESRD (C) and Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (D). FIGURE 4 View largeDownload slide Distribution of the candidates cleared for donation according to age categories and different thresholds of pre-donation 15-year ESRD risk (A), pre-donation projected lifetime ESRD risk (B), SRTR post-donation 15-year risk of ESRD (C) and Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 (D). Pre-donation projected lifetime ESRD risk according to age Conversely, the pre-donation projected lifetime ESRD risk was higher in younger candidates. It was 0.62, 0.34, 0.26 and 0.21% for candidates aged 18–35, 36–50, 51–60 and ≥61 years, respectively (P = 0.0001). The use of a threshold of pre-donation projected lifetime ESRD risk at 0.25% was associated with a major decrease in the percentages of candidates allowed to donate when compared with the use of the GFR threshold recommended in France, among those aged 18–35 years (5.6% versus 100%), 36–50 years (32.7% versus 91.7%) and 51–60 years (48.4% versus 87.7%) (Figure 4B). The use of a threshold at 0.5% was associated with a decrease in the percentages of candidates cleared for living donation among those aged 18–35 years (22.3% versus 100%) and 36–50 years (70.9% versus 91.7%), but an increase among those aged ≥61 years (86.2% versus 57.6%). The use of a threshold at 1% was associated with a slight decrease in the percentage of candidates cleared for living donation among those aged 18–35 years (83.3% versus 100%), but an increase among those aged 51–60  years (98.4% versus 87.7%) and ≥61 years (100% versus 57.6%). SRTR post-donation 15-year ESRD risk according to age The median SRTR post-donation 15-year ESRD risk increased significantly with age. It was at 15.5, 12.1, 21.2 and 27.1 per 10 000 for candidates aged, respectively, 18–35, 36–50, 51–60 and ≥61 years (P = 0.0001). The use of a threshold of SRTR post-donation 15-year ESRD risk at 25 per 10 000 donors was associated with a decrease in the percentage of candidates cleared for living donation among all age categories (Figure 4C). The use of a threshold at 50 per 10 000 donors was associated with an increase in the percentage of candidates cleared for living donation among those aged ≥61 years (83.9% versus 57.6%). The use of a threshold at 100 per 10 000 donors was associated with 100% of candidates being cleared for living donation, for each age category. Minnesota post-donation 15-year risk of ESRD or GFR < 30mL/min/1.73 m2 according to age The median Minnesota post-donation 15-year risk of ESRD or GFR <30 mL/min/1.73 m2 increased significantly with age (P = 0.0001). The use of a threshold at 1% or 2% was associated with a dramatic decrease in the percentage of candidates cleared for living donation among those aged >35 years (Figure 4D). The use of a threshold at 3% was associated with an increase in the percentage of candidates cleared for living donation among those aged ≥61 years (90% versus 57.6%). The use of a threshold at 6% was associated with 100% of candidates being cleared for living donation, for each age category. DISCUSSION Until recently, most guidelines have considered a GFR threshold of 80 mL/min/1.73 m2 as acceptable for authorizing subsequent living donations. To date, the KDIGO recommend that the evaluation of living donor candidates should include the determination of the pre- and post-donation risks of ESRD, which are based on a composite profile of many risk factors [8, 9]. Our study demonstrates that the use of these ESRD risks would significantly modify donor selection by increasing the percentage of candidates cleared for living donation among those aged ≥61 years and by decreasing the percentage of cleared candidates aged 18–35 years. For assessing individualized pre- and post-donation ESRD risks, we used the tools that have been developed based on seven general population cohorts, the SRTR and at the University of Minnesota [6, 7]. As previously observed by Gaillard et al. [10], we also observed a complete overlap in the pre- and post-donation ESRD risks for living kidney donors and disqualified candidates. Moreover, the median pre-donation projected lifetime ESRD risk was similar for both groups. This last observation demonstrates that risk factors of kidney disease, such as age, race or systolic blood pressure, can increase the level of pre-donation lifetime ESRD risks in patients with high GFR. It also suggests that integration of these risks would significantly influence the selection of candidates, regardless of the particular threshold of ESRD risk chosen for clearing living kidney donations. It has been reported that the estimated 15-year risk of ESRD was 3.9 per 10 000 (95% confidence interval 0.8–8.9) for healthy non-donors [8]. Defining an arbitrary threshold for clearing donations is difficult and raises ethical questions. Choosing donors whose post-donation ESRD risk is comparable to that of the general public is readily accepted, but choosing donors with an acceptable higher risk could also be considered. Moreover, the presence of risk does not necessarily mean that the event will occur. Some candidates could also be less prone than others to accepting the same level of ESRD risk. For instance, it has been observed that 43% of potential donors would accept a 20-year incidence of kidney failure 100 times higher than the estimated risk of ESRD, whereas only 11% of recipients and 6% of transplant professionals would accept donations with such a level of risk [11]. In the absence of any clear threshold for clearing donations, these figures could also be used as an educational tool for improving the quality of donor information and reaching a common decision. However, physicians must keep in mind that statistics or medical risks are sometimes difficult to apprehend for candidates who made the decision to donate prior to having been exposed to this information [12]. The main objective of our study was to determine how many living kidney candidates would be accepted or declined for each threshold of pre- and post-donation ESRD risk. Thresholds of pre-donation 15-year ESRD risk >0.25%, pre-donation projected lifetime ESRD risk at 1% and SRTR post-donation 15-year ESRD risk >50 per 10 000 donors were associated with the clearance of >90% of the candidates. Conversely, thresholds of pre-donation lifetime ESRD risk at 0.25% and SRTR post-donation 15-year ESRD risk at 25 per 10 000 donors led to, respectively, only 41% and 69.7% of candidates being cleared for donation, suggesting that a small variation in the acceptance threshold would significantly modify the proportion of candidates accepted as living kidney donors. It is important to point out that we do not recommend choosing the cut-off for clearing donations based on this utilitarian principle in order to increase the pool of donors. The principle of non-maleficence is of the utmost importance if we want to minimize the long-term ESRD risk in living donor candidates. The pre- and post-donation 15-year ESRD risks were calculated based on retrospective cohorts [3, 7]. Although useful, these estimates may not fully capture the relevant risks among young donors, who may have >60 years of remaining life. For this reason, these 15-year ESRD risks could be interesting only for candidates >60 years of age. Using the pre-donation ESRD risk would increase the percentage of candidates cleared for living donation among those aged ≥61 years by 28.6% for a cut-off at 0.25% and 42.4% for a cut-off at 0.5%. Using the SRTR post-donation, ESRD risk could also increase the percentage of candidates cleared for living donation among those aged ≥61 years by 26.3% for a cut-off at 50 and 42.4% for a cut-off at 100. A similar result would be observed with the Minnesota post-donation risk for a cut-off at 3%. These observations are in accordance with the perspective of the ERA-EDTA DESCARTES working group, which recently proposed encouraging the evaluation of older donors [13]. Grams et al. [3] also provided a projected lifetime risk of kidney failure, with the caveat that this estimate lacks precision. Despite this drawback, the projected lifetime risk has a much stronger clinical relevance than the 15-year risk of kidney failure for young donors. The use of cut-offs <1% would significantly decrease the percentage of candidates cleared for living donation among those aged 18–35 years. For instance, only 5.6% and 22.3% of candidates displayed a pre-donation projected lifetime ESRD risk <0.25% or 0.5%, respectively. These results suggest that most young candidates could not be considered as living kidney donors if the acceptance threshold of pre-donation projected lifetime ESRD risk is set at 0.25% or 0.5% [3, 14]. These data based on the projected lifetime ESRD risk should be interpreted with caution, since Ibrahim et al. reported that 40 years after donation, high post-donation GFRs were also associated with high pre-donation GFRs, suggesting that young donors with a high GFR still had excellent kidney function 40 years after donation [6]. It will take decades to clarify the long-term renal outcome of young donors. In the future, we may suppose that genetics and social or environmental risks could also be considered so as to improve the reliability of the post-donation risk of kidney failure. The genetic background analysis seems particularly important. For instance, the two variants G1 and G2 of the APOL1 gene, which are found primarily in populations with African ancestry, are associated with various forms of kidney disease and kidney disease progression [15]. Although the functional role of APOL1 within the cells of the kidney is still unknown [16], kidneys from African American deceased donors with these two APOL1 nephropathy variants are also associated with a higher risk for allograft failure [17–19]. Moreover, the high risk for chronic kidney disease observed in the potential young African American living donors could be driven in part by these two APOL1 renal-risk variants [20]. Screening of these two high-risk APOL1 alleles in young African American potential living kidney donors may then help to better determine ESRD risk [21, 22]. Finally, the main limitation of this study is its overestimating ESRD risks for French candidates using these online calculators, due to a lower incidence of ESRD in France compared with the USA (150 versus 400 cases per million inhabitants, respectively) [23]. In summary, integrating the pre- and post-donation ESRD risks in the evaluation of candidates would allow older candidates with GFR <80 mL/min/1.73 m2 to be reclassified as living kidney donors, while excluding some young donors despite high GFR. However, defining an acceptance threshold of lifetime ESRD risk is a difficult task, which should not run counter to the principle ‘primum non nocere.’ ACKNOWLEDGEMENTS The authors would like to thank our department’s donor coordinators, Catherine Rio and Sandrine Dumartin, for their precious help and professionalism. AUTHORS’ CONTRIBUTIONS Q.-L.N., P.M. and L.C. designed the study, carried out the analyses, interpreted the data and wrote the manuscript. CONFLICT OF INTEREST STATEMENT None declared. REFERENCES 1 Living kidney donation recommendations - Biomedicine Agency, 2016. https://www.agence-biomedecine.fr/IMG/pdf/2009_reco_formalisees_experts_pvlt_greffe_donneurs_vivants_complet.pdf (16 may 2018, date last accessed) 2 United Kingdom Guidelines. Living Donor Kidney Transplantation. 2011. https://bts.org.uk/wp-content/uploads/2016/09/19_BTS_RA_Living_Donor_Kidney-1.pdf (16 may 2018, date last accessed) 3 Grams ME, Sang Y, Levey AS et al.   Kidney-failure risk projection for the living kidney-donor candidate. N Engl J Med  2016; 374: 411– 421 Google Scholar CrossRef Search ADS PubMed  4 Muzaale AD, Massie AB, Wang M-C et al.   Risk of end-stage renal disease following live kidney donation. JAMA  2014; 311: 579– 586 Google Scholar CrossRef Search ADS PubMed  5 Mjoen G, Hallan S, Hartmann A et al.   Long-term risks for kidney donors. Kidney Int  2014; 86: 162– 167 Google Scholar CrossRef Search ADS PubMed  6 Ibrahim HN, Foley RN, Reule SA et al.   Renal function profile in white kidney donors: the first 4 decades. J Am Soc Nephrol  2016; 27: 2885– 2893 Google Scholar PubMed  7 Massie AB, Muzaale AD, Luo X et al.   Quantifying postdonation risk of ESRD in living kidney donors. J Am Soc Nephrol  2017; 28: 2749– 2755 Google Scholar CrossRef Search ADS PubMed  8 Lentine KL, Kasiske BL, Levey AS et al.   KDIGO clinical practice guideline on the evaluation and care of living kidney donors. Transplantation  2017; 101 (8S Suppl 1): S1– 109 9 Levey AS, Inker LA. GFR evaluation in living kidney donor candidates. J Am Soc Nephrol  2017; 28: 1062– 1071 Google Scholar CrossRef Search ADS PubMed  10 Gaillard F, Baron S, Timsit M-O et al.   What is the significance of end-stage renal disease risk estimation in living kidney donors? Transpl Int  2017; 30: 799– 806 Google Scholar CrossRef Search ADS PubMed  11 Young A, Karpinski M, Treleaven D et al.   Differences in tolerance for health risk to the living donor among potential donors, recipients, and transplant professionals. Kidney Int  2008; 73: 1159– 1166 Google Scholar CrossRef Search ADS PubMed  12 Stothers L, Gourlay WA, Liu L. Attitudes and predictive factors for live kidney donation: a comparison of live kidney donors versus nondonors. Kidney Int  2005; 67: 1105– 1111 Google Scholar CrossRef Search ADS PubMed  13 Maggiore U, Budde K, Heemann U et al.   Long-term risks of kidney living donation: review and position paper by the ERA-EDTA DESCARTES working group. Nephrol Dial Transplant  2017; 32: 216– 223 Google Scholar CrossRef Search ADS PubMed  14 Steiner RW. ‘Normal for Now’ or ‘At Future Risk’: a double standard for selecting young and older living kidney donors. Am J Transplant  2010; 10: 737– 741 Google Scholar CrossRef Search ADS PubMed  15 Foster MC, Coresh J, Fornage M et al.   APOL1 variants associate with increased risk of CKD among African Americans. J Am Soc Nephrol  2013; 24: 1484– 1491 Google Scholar CrossRef Search ADS PubMed  16 O’Toole JF, Schilling W, Kunze D et al.   ApoL1 overexpression drives variant-independent cytotoxicity. J Am Soc Nephrol  2017; 29: 869– 879 Google Scholar PubMed  17 Reeves-Daniel AM, Depalma JA, Bleyer AJ et al.   The APOL1 gene and allograft survival after kidney transplantation. Am J Transplant  2011; 11: 1025– 1030 Google Scholar CrossRef Search ADS PubMed  18 Freedman BI, Julian BA, Pastan SO et al.   Apolipoprotein L1 gene variants in deceased organ donors are associated with renal allograft failure. Am J Transplant  2015; 15: 1615– 1622 Google Scholar CrossRef Search ADS PubMed  19 Freedman BI, Pastan SO, Israni AK et al.   APOL1 genotype and kidney transplantation outcomes from deceased African American donors. Transplantation  2016; 100: 194– 202 Google Scholar CrossRef Search ADS PubMed  20 Locke JE, Sawinski D, Reed RD et al.   Apolipoprotein L1 and chronic kidney disease risk in young potential living kidney donors. Ann Surg  2017; 267 (6): 1161– 1168 21 Freedman BI, Julian BA. Should kidney donors be genotyped for APOL1 risk alleles? Kidney Int  2015; 87: 671– 673 Google Scholar CrossRef Search ADS PubMed  22 Riella LV, Sheridan AM. Testing for high-risk APOL1 alleles in potential living kidney donors. Am J Kidney Dis  2015; 66: 396– 401 Google Scholar CrossRef Search ADS PubMed  23 Levey AS, Coresh J. Chronic kidney disease. Lancet  2012; 379: 165– 180 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Nephrology Dialysis TransplantationOxford University Press

Published: May 28, 2018

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