Impact of measured versus estimated glomerular filtration rate-based screening on living kidney donor characteristics: A study of multiple cohorts.

BACKGROUND: Most transplant centers in the Netherlands use estimated glomerular filtration rate (eGFR) for evaluation of potential living kidney donors. Whereas eGFR often underestimates GFR, especially in healthy donors, measured GFR (mGFR) allows more precise kidney function assessment, and therefore holds potential to increase the living donor pool. We hypothesized that mGFR-based donor screening leads to acceptance of donors with lower pre-donation eGFR than eGFR-based screening.
METHODS: In this longitudinal cohort study, we compared eGFR (CKD-EPI) before donation in one center using mGFR-based screening (mGFR-cohort, n = 250) with two centers using eGFR-based screening (eGFR-cohort1, n = 466 and eGFR-cohort2, n = 160). We also compared differences in eGFR at five years after donation.
RESULTS: Donor age was similar among the cohorts (mean±standard deviation (SD) mGFR-cohort 53±10 years, eGFR-cohort1 52±13 years, P = 0.16 vs. mGFR-cohort, and eGFR-cohort2 53±9 years, P = 0.61 vs. mGFR-cohort). Estimated GFR underestimated mGFR by 10±12 mL/min/1.73m2 (mean±SD), with more underestimation in younger donors. In the overall cohorts, mean±SD pre-donation eGFR was lower in the mGFR-cohort (91±13 mL/min/1.73m2) than in eGFR-cohort1 (93±15 mL/min/1.73m2, P<0.05) and eGFR-cohort2 (94±12 mL/min/1.73m2, P<0.05). However, these differences disappeared when focusing on more recent years, which can be explained by acceptance of more older donors with lower pre-donation eGFR over time in both eGFR-cohorts. Five years post-donation, mean±SD eGFR was similar among the centers (mGFR-cohort 62±12 mL/min/1.73m2, eGFR-cohort1 61±14 mL/min/1.73m2, eGFR-cohort2 62±11 mL/min/1.73m2, P = 0.76 and 0.95 vs. mGFR-cohort respectively). In the mGFR-cohort, 38 (22%) donors were excluded from donation due to insufficient mGFR with mean±SD mGFR of 71±9 mL/min/1.73m2.
CONCLUSIONS: Despite the known underestimation of mGFR by eGFR, we did not show that the routine use of mGFR in donor screening leads to inclusion of donors with a lower pre-donation eGFR. Therefore eGFR-based screening will be sufficient for the majority of the donors. Future studies should investigate whether there is a group (e.g. young donors with insufficient eGFR) that might benefit from confirmatory mGFR testing.

Introduction

Living kidney donor transplantation currently represents ~50% of the total kidney transplantations in the Netherlands [1]. The main goal of living kidney donor evaluation is to assess whether a donor is healthy enough to undergo surgery and maintain good health after the nephrectomy [2, 3]. An important part of screening consists of estimation and/or measurement of the glomerular filtration rate (GFR) before donation to determine whether the donor will retain sufficient kidney function after donation for life long safe kidney function. Glomerular filtration rate can easily be estimated (eGFR) by various equations based on serum creatinine or cystatin C, but the gold standard is assessment of the GFR by measuring the clearance of exogenous filtration markers (mGFR) [4]. The latter is expensive and laborious and therefore much less widespread in use in the Netherlands [5].

There is no consensus regarding the best method for kidney function assessment during the selection of living donors [2, 3, 6]. Some guidelines advise eGFR based on the chronic kidney disease epidemiology collaboration (CKD-EPI) equation, others advise use of 24h creatinine clearance or even mGFR. Due to cost and time advantages, most centers in the Netherlands estimate GFR based on creatinine clearance. The University Medical Center Groningen is the only center in the Netherlands that routinely performs mGFR measurements in every (potential) donor.

Even though mGFR is considered the gold standard, it is unclear whether its use is advantageous over the use of eGFR for living kidney donor screening. A well-known limitation in white populations of kidney function estimation equations based on serum creatinine is that in the higher ranges of GFR, true GFR is underestimated [7-13]. Consequently, donors with normal to high kidney function might be mistakenly classified as having insufficient kidney function when eGFR is used, possibly leading to exclusion from donation. This study aimed to compare pre- and post-donation eGFR of living kidney donors between two centers that base the decision to accept a donor based on eGFR and a center that uses mGFR for decision making. We hypothesized that mGFR-based screening allows acceptance of donors with lower mean pre-donation eGFR compared to the population from centers that use eGFR-based screening. In addition, post-donation safety was studied by comparing kidney function five years after donation in donors who have been evaluated using mGFR and eGFR.

Materials and methods

Study design

In this longitudinal cohort study in the Netherlands, we compared effective living kidney donors between one center that used mGFR-based donor evaluation (University Medical Center Groningen, mGFR-cohort) and two centers that used eGFR-based donor evaluation (eGFR-cohort1 = Erasmus MC, University Medical Center Rotterdam, and eGFR-cohort2 = Radboud University Medical Center Nijmegen,). The study was approved by the institutional ethical review board of each participating center. For the mGFR-cohort, the study underwent ethical review in accordance with current ethical guidelines in 2014 as the TransplantLines biobank and cohort study (2014/077). The study was registered at clinicaltrials.gov under identifier NCT0327284 [14]. All donors included in the study signed informed consent for the use of their medical data for scientific research. In eGFR-cohort1 the study was approved by the EMC Medical Ethical Committee MEC-2019-0737. In eGFR-cohort1 and eGFR-cohort2, all donors have given written informed consent for the use of their medical data for scientific research. All procedures were conducted in accordance with the Declaration of Helsinki, Declaration of Istanbul, and the Dutch Scientific Guidelines.

Study population and measurements mGFR-cohort

In the University Medical Center Groningen, the selection criteria according to Dutch Living Kidney Donor guidelines (based on international guidelines) were used [3]. Instead of the recommended eGFR, mGFR was used to assess renal function before and after donation. A total of 1,113 potential living kidney donors were screened between 2006 and 2018 in Groningen. In this group, 977 donors were accepted for donation, of which 250 donated and had data for five-year follow-up available. The mGFR, measured as the urinary clearance of 125I-iothalamate (S1 File), and eGFR (based on serum creatinine) were measured before donation in every (potential) donor and five years after donation. Measured GFR was corrected for body surface area (BSA, calculated according to Dubois et al.) [15]. Clinical decision making was based on pre-donation mGFR. Estimated GFR was retrospectively determined according to the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation to enable comparison with the eGFR-cohorts and according to the Modification of Diet in Renal Disease (MDRD) equation and the Cockcroft-Gault (CG) equation for secondary analyses [12, 16, 17]. Twenty-four-hour urine samples were used to calculate the 24h creatinine clearance (CrCl). Besides kidney function measurements, clinical parameters such as weight, height, and blood pressure were measured during the visits. Blood pressure was measured three times while seated with an interval of three minutes and a fourth time after standing straight for one minute using an automatic device as described previously [14].

Study population and measurements eGFR-cohort1

Between 1981 and 2019, 4,801 potential donors were screened for donation at the Erasmus MC, University Medical Center Rotterdam, the Netherlands. Of these donors, 2,144 donors eventually donated. For 647 donors, five-year follow-up was available. In order to enable comparison with the mGFR-cohort, donors that were screened before 2006 were excluded, rendering 466 donors eligible for this study. Glomerular filtration rate was assessed by equations based on serum creatinine, measured by enzymatic creatinine determination. In potential donors with unexpectedly low eGFR, 24-hour urine collection was performed to calculate endogenous creatinine clearance. When CrCl was adequate donation was allowed. Besides kidney function measurements, clinical parameters such as weight, height and blood pressure were measured during the visits.

Study population and measurements eGFR-cohort2

Between 2006 and 2014, 970 potential donors were screened for donation in the Radboud University Medical Center in Nijmegen, the Netherlands. Of these donors, 603 donors donated in these years. For 160 donors, five-year follow-up was available. Glomerular filtration rate was assessed by the equations based on serum creatinine and two 24-hour urine collection allowing calculation of the endogenous creatinine clearance. Serum creatinine was measured by enzymatic method. Besides kidney function measurements, clinical parameters such as weight, height and blood pressure were measured during the visits. The office blood pressure measurement was included in this study.

Statistical analyses

Data are presented as mean±standard deviation (SD) for normally distributed variables and as median (first quartile–third quartile) for non-normally distributed variables. The distribution was tested using histograms and probability plots. Binary variables are shown as ‘number (%)’. Measured GFR data are reported as absolute values (mL/min) and corrected for body surface area according to Dubois et al. (mL/min/1.73m2) [15]. To maintain consistency and enable comparison, eGFR was recalculated according to the CKD-EPI equation for all centers. Differences in characteristics of donors between the mGFR-cohort and eGFR-cohort1 and between the mGFR-cohort and eGFR-cohort2 were tested using the independent Student’s t-test for normally distributed variables, the Mann-Whitney U-test for non-normally distributed variables, and the chi-square test for proportions. To characterize donors with low pre-donation eGFR, we compared characteristics of 10% of donors with the lowest pre-donation eGFR to the other 90% of the donors using the tests mentioned above. Similarly, we compared donors with an underestimation of mGFR ≥10 and ≥20 mL/min/1.73m2 by eGFR to donors with no underestimation or an underestimation <10 and <20 mL/min/1.73m2, in order to identify donors at risk of underestimation by eGFR. Bias between pre- and post-donation eGFR and mGFR was calculated as the mean difference between both parameters. Because reason of exclusion from donation was mostly multifactorial and rarely solely dependent GFR, we did not analyze the number of donors excluded based on kidney function per center. SPSS version 23 for Windows (IBM, Armonk, NY) and Graphpad Prism 8 for Windows (Graphpad, San Diego, CA) were used to perform the analyses. P values <0.05 were considered statistically significant.

Results

Bias between eGFR and mGFR

The known underestimation of pre-donation mGFR by pre-donation eGFR (CKD-EPI) was also present in the mGFR-cohort (mean±SD bias = -10±12 mL/min/1.73m2, S1 Table). This underestimation was visualized in a Bland-Altman plot (Fig 1). This bias became smaller five years after donation (-5±9 mL/min/1.73m2). Pre-donation 24h CrCl overestimated pre-donation mGFR with a bias of 26±29 mL/min (S2 Table). Five years after donation, this overestimation was still present, although it was slightly reduced (18±19 mL/min).

Fig 1

Bland-altman plot of pre-donation eGFR and pre-donation mGFR.

Bias between pre-donation eGFR and pre-donation mGFR is shown on the X-axis, the average between pre-donation eGFR and pre-donation mGFR is shown on the Y-axis. Mean±SD bias was -10.38 mL/min/1.73m2, the 95% confidence interval of the mean bias was -33.48 to 12.72 mL/min/1.73m2.

Donors in whom pre-donation GFR was underestimated

The mGFR-cohort of donors was split into a group in which eGFR underestimated mGFR (≥10 mL/min/1.73m2 difference) and a group in which eGFR did not underestimate mGFR (<10 mL/min/1.73m2 difference), as shown in Table 1. Besides differences in kidney function, there were no statistically significant differences in clinical characteristics between donors in whom mGFR was underestimated by eGFR and donors in whom mGFR was not underestimated by eGFR. Donors in whom eGFR underestimated mGFR ≥20 mL/min/1.73m2 were significantly younger than donors in whom the difference between eGFR and mGFR was <20 mL/min/1.73m2 (mean±SD 50±8 vs. 54±10 years respectively, P = 0.02). A low eGFR compared to 24h CrCl was mainly limited to donors with higher height, weight, BMI and BSA (S3 Table). Difference between eGFR and 24h CrCl was more commonly <10 mL/min in female donors (S3 Table). An overestimation of mGFR by eGFR was present in 45 donors (S4 Table).

Table 1

Pre-donation characteristics of donors from the mGFR-cohort with an underestimation of mGFRBSA by eGFR ≥10 mL/min/1.73m2.

	Underestimation ≥10 mL/min/1.73m 2	Underestimation <10 mL/min/1.73m 2	P value
Number, n (%)	121 (49)	127 (51)	-
CKD-EPI, mL/min/1.73m2	88 ±13	94 ±12	<0.001
CrCl, mL/min	131 ±32	124 ±35	<0.001
mGFR, mL/min	122 ±24	109 ±19	<0.001
mGFR/BSA, mL/min/1.73m2	108 ±16	96 ±12	<0.001
Age, years	52 ±9	53 ±10	0.31
Sex, n (%) female	61 (50)	72 (57)	0.32
Race, n (%) Caucasian	121 (100)	127 (100)	-
Weight, kg	80 ±13	81 ±14	0.55
Height, cm	174 ±9	174 ±9	0.98
BMI, kg/m2	26 ±3	27 ±4	0.38
BSA, m2	1.95 ±0.20	1.96 ±0.20	0.70
SBP, mmHg	128 ±14	127 ±14	0.45
DBP, mmHg	77 ±9	76 ±9	0.48
Serum creat, μmol/L	78 ±13	70 ±12	<0.001
	Underestimation ≥20 mL/min/1.73m 2	Underestimation <20 mL/min/1.73m 2	P value
Number, n (%)	53 (21)	195 (79)	-
CKD-EPI, mL/min/1.73m2	89 ±14	92 ±12	0.20
CrCl, mL/min	139 ±28	124 ±34	0.01
mGFR, mL/min	133 ±23	110 ±20	<0.001
mGFR/BSA, mL/min/1.73m2	116 ±15	98 ±12	<0.001
Age, years	50 ±8	54 ±10	0.02
Sex, n (%) female	23 (43)	110 (56)	0.09
Race, n (%) Caucasian	195 (100)	53 (100)	-
Weight, kg	82 ±13	81 ±14	0.46
Height, cm	176 ±10	174 ±9	0.28
BMI, kg/m2	26 ±3	26 ±4	0.99
BSA, m2	1.98 ±0.20	1.95 ±0.20	0.32
SBP, mmHg	127 ±14	128 ±14	0.62
DBP, mmHg	76 ±9	77 ±9	0.43
Serum creat, μmol/L	79 ±15	73 ±12	<0.001

Binary variables presented as n (%), continuous variables presented as mean ±SD

Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; SD: Standard deviation.

Comparison of kidney function and clinical characterestics before donation

The characteristics of the living kidney donor populations before donation are shown in Table 2. Mean±SD age before donation was 53±10 (mGFR-cohort (Groningen)), 53±12 (eGFR-cohort1 (Rotterdam)), and 54±10 (eGFR-cohort2 (Nijmegen)) years and 54%, 54%, and 45%, respectively were female. Mean±SD eGFR (CKD-EPI) before donation was 91±13 mL/min/1.73m2 in the mGFR-cohort, which was lower than in eGFR-cohort1 (93±15 mL/min/1.73m2, P = 0.20) and eGFR-cohort2 (94±12 mL/min/1.73m2, P = 0.01) where eGFR formed the basis for screening. Distributions of pre-donation eGFR (CKD-EPI) for the different centers are shown in Fig 2. Mean±SD mGFR/BSA before donation was 101±15 mL/min/1.73m2 in the mGFR-cohort. Pre-donation systolic blood pressure (SBP) was higher in eGFR-cohort2 (137±16 mmHG) compared to the mGFR-cohort (128±14 mmHg, P<0.001) and slightly different between eGFR-cohort1 (130±16 mmHg) and the mGFR-cohort (P = 0.05). This difference is probably explained by the use of office blood pressure in eGFR-cohort2. Body size measurements (height, weight, BMI and BSA) did not show major differences before and after donation between the cohorts.

Table 2

Characteristics of the living kidney donors during screening.

	mGFR-cohort	eGFR-cohort1	P vs. mGFR-cohort	eGFR-cohort2	P vs. mGFR-cohort
Number, n (%)	250	466	-	160	-
CKD-EPI, mL/min/1.73m2	91 ±13	93 ±15	0.20	94 ±12	0.02
CrCl, mL/min	127 ±33	-	-	129 ±28	0.50
mGFR, mL/min	115 ±22	-	-	-	-
mGFR/BSA, mL/min/1.73m2	101 ±15	-	-	-	-
Age, years	53 ±10	53 ±12	0.91	54 ±10	0.41
Female sex, n (%)	134 (54)	252 (54)	0.90	72 (45)	0.89
Caucasian race, n (%)	250 (100)	450 (97)	-	160 (100)	-
Weight, kg	80 ±14	79 ±14	0.12	78 ±14	0.05
Height, cm	174 ±9	172 ±9	<0.001	173 ±8	0.13
BMI, kg/m2	26 ±3	27 ±4	0.38	26 ±4	0.13
BSA, m2	1.96 ±0.20	1.92 ±0.20	0.01	1.92 ±0.19	0.04
SBP, mmHg	128 ±14	130 ±16	0.05	137 ±16	<0.001
DBP, mmHg	76 ±9	78 ±9	0.07	81 ±8	<0.001
Use of antihypertensive medication, n (%)	43 (17)	79 (17)	0.93	24 (15)	0.56
Smoking, n (%)	59 (24)	-	-	52 (33)	0.05
Serum creat, μmol/L	74 ±13	74 ±14	0.62	72 ±12	0.18

Binary variables presented as n (%), continuous variables presented as mean ±SD

Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; SD: Standard deviation.

Fig 2

Distribution of pre-donation eGFR (CKD-EPI) per center.

Differences between mean pre-donation eGFR were tested using the independent sample T-test, P-values are shown in the Fig. Distribution of mGFR in the mGFR-cohort was added on the right in the Fig.

Analysis of differences in eGFR over time

Because this study included donors that were screened during a large timeframe (especially in eGFR-cohort1), we performed secondary analyses to investigate whether the differences in pre-donation eGFR were consistent over time. We therefore split the cohort in two equal parts, which resulted in a group that was screened before 01-01-2009, and a group that was screened after 01-01-2009. Fig 3 shows the distribution of pre-donation eGFR (CKD-EPI) before and after 2009 and shows that the differences that were seen in the total cohort, mainly depended on differences in pre-donation eGFR before 2009 (mean±SD eGFR in mGFR-cohort: 90±12 mL/min/1.73m2, eGFR-cohort1: 94±15 mL/min/1.73m2, eGFR-cohort2: 97±11 mL/min/1.73m2). When focusing on data after 2009, the differences in pre-donation eGFR seem to disappear (mGFR-cohort: 92±13 mL/min/1.73m2, eGFR-cohort1: 92±15 mL/min/1.73m2, eGFR-cohort2: 93±12 mL/min/1.73m2). When looking at age before and after 2009 (Fig 4), our data show that both eGFR-cohort1 and eGFR-cohort2 accepted older donors after 2009 compared to before 2009, although only significant in eGFR-cohort2 (mean±SD age eGFR-cohort1: 52±12 years before and 53±13 years after 2009 (P = 0.16), eGFR-cohort2: 51±10 before and 55±9 after 2009 (P = 0.01)), whereas in mGFR-cohort there does not seem to be a difference in age over time (before 2009 53±9 years vs. after 2009 53±10 years, P = 0.99). Mean BMI did not differ before and after 2009 in the three centers (S1 Fig).

Fig 3

Distribution of pre-donation eGFR (CKD-EPI) before and after 2009 per center.

Differences between mean pre-donation eGFR were tested using the independent sample T-test, P-values are shown in the Fig. Distribution of mGFR in the mGFR-cohort was added on the right in the Fig.

Fig 4

Distribution of age before and after 2009 per center.

Differences between mean age were tested using the independent sample T-test, P-values are shown in the Fig.

Living kidney donor characteristics five years after donation

Five years after donation, there was no difference in mean±SD eGFR (CKD-EPI) in the total cohort (mGFR-cohort: 62±12 mL/min/1.73m2, eGFR-cohort1: 60±14 mL/min/1.73m2 (P = 0.15 vs. mGFR-cohort), eGFR-cohort2: 61±11 mL/min/1.73m2 (P = 0.65 vs. mGFR-cohort) Table 3 and S2 Fig). When looking at differences between the centers for the groups that were screened before 2009 and after 2009, we see no differences between the centers, but for all centers five-year post-donation eGFR was lower (mGFR-cohort: 64±12 mL/min/1.73m2 before and 60±12 mL/min/1.73m2 after 2009 (P = 0.01), eGFR-cohort1: 61±14 mL/min/1.73m2 before and 59±13 mL/min/1.73m2 after 2009 (P = 0.07), eGFR-cohort2: 63±11 mL/min/1.73m2 before and 60±11 mL/min/1.73m2 after 2009 (P = 0.04), S3 Fig).

Table 3

Characteristics of the living kidney donors five years after donation.

	mGFR-cohort	eGFR-cohort1	P vs. mGFR-cohort	eGFR-cohort2	P vs. mGFR-cohort
Number, n	250	466	-	160	-
CKD-EPI, mL/min/1.73m2	62 ±12	60 ±14	0.15	61 ±11	0.65
ΔCKD-EPI, mL/min/1.73m2*	-29 ±10	-32 ±10	<0.001	-33 ±8	<0.001
CrCl, mL/min	85 ±22	-	-	-	-
mGFR, mL/min	76 ±16	-	-	-	-
mGFR/BSA, mL/min/1.73m2	67 ±11	-	-	-	-
Age, years	58 ±10	58 ±12	0.74	59 ±10	0.29
Weight, kg	83 ±15	81 ±15	0.17	80 ±16	0.15
BMI, kg/m2	27 ±4	27 ±4	0.34	27 ±4	0.36
BSA, m2	1.98 ±0.21	1.94 ±0.20	0.02	1.94 ±0.21	0.10
SBP, mmHg	127 ±14	133 ±16	<0.001	133 ±15	<0.001
DBP, mmHg	76 ±10	79 ±9	<0.001	79 ±7	0.01
Use of antihypertensive medication, n (%)	67 (27)	141 (30)	0.33	58 (36)	0.04
Smoking, n (%)	69 (28)	-	-	46 (29)	0.80
Serum creat, μmol/L	103 ±20	106 ±21	0.09	104±18	0.48

Binary variables presented as n (%), continuous variables presented as mean ±SD

*Calculated as: CKD-EPI 5 years after donation minus pre-donation CKD-EPI

Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; SD: Standard deviation.

Secondary analyses of pre-donation kidney function

Mean±SD pre-donation 24-hour creatinine clearance (24h CrCl) was 127±33 mL/min in the mGFR-cohort and 129±28mL/min in eGFR-cohort2 (P = 0.50); eGFR-cohort1 did not routinely determine CrCl (S4 Fig). These results were similar before 2009 compared to after 2009. We also compared pre-donation eGFR according to the CG and MDRD equation before and after 2009, which yielded similar results to the CKD-EPI comparison (S5 and S6 Figs).

Comparison of donors with marginal pre-donation eGFR

We subsequently focused on the 10% of donors with lowest pre-donation eGFR in the three cohorts (Table 4). In these donors from the mGFR-cohort, mean±SD pre-donation eGFR was 70±3 mL/min/1.73m2 and mean±SD five-year post-donation eGFR was 48±6 mL/min/1.73m2 (Table 4). Pre-donation mGFR/BSA was 86±9 mL/min/1.73m2 and only decreased to 59±9 mL/min/1.73m2 five years after donation. The 10% donors from eGFR-cohort1 and eGFR-cohort2 with lowest pre-donation eGFR were older than the corresponding donors from the mGFR-cohort (65±9 years and 60±8 years respectively vs. 56±6 years (P<0.001 and P = 0.09 respectively)). Furthermore, BSA tended to be higher in these donors from the mGFR-cohort versus eGFR-cohort1 and eGFR-cohort2 (1.94±0.19 m2 vs. 1.89±0.15 m2 and 1.89±0.17 m2 (P = 0.13 and P = 0.30, respectively), but power might be too limited to draw conclusions. The same applies to blood pressure (132±21 mmHg for the mGFR-cohort vs. 136±17 mmHg for eGFR-cohort1 and 138±22 mmHg for eGFR-cohort2 (P = 0.34 and P = 0.52, respectively). In the mGFR-cohort, 5% of the donors had a pre-donation eGFR below the age-adapted threshold versus 3% in eGFR-cohort1 (P = 0.13) and 1% in eGFR-cohort2 (P = 0.04) (S5 Table). None of these donors had poor outcomes at five years after donation.

Table 4

Pre- and 5 year post-donation characteristics of 10% of the donors with lowest pre-donation eGFR per center.

	mGFR-cohort		eGFR-cohort1		eGFR-cohort2
	Pre-donation	5 year post-donation	Pre-donation	5 year post-donation	Pre-donation	5 year post-donation
Number, n (%)	25	25	51	51	16	16
CKD-EPI, mL/min/1.73m2	70 ±3	48 ±6	67 ±5	43 ±8	72 ±5	48 ±6
CrCl, mL/min	107 ±20	73 ±17	-	-	106 ±22	-
mGFR, mL/min	98 ±15	67 ±15	-	-	-	-
mGFR/BSA, mL/min/1.73m2	87 ±9	59 ±9	-	-	-	-
Age, years	56 ±6	62 ±7	65 ±9	71 ±9	60 ±8	66 ±8
Female sex, n (%)	15 (60)	15 (60)	29 (57)	29 (57)	9 (56)	9 (56)
Caucasian race, n (%)	25 (100)	25 (100)	51 (100)	51 (100)	16 (100)	16 (100)
Weight, kg	80 ±12	82 ±13	77 ±9	79 ±11	76 ±12	79 ±14
Height, cm	173 ±9	173 ±9	171 ±8	171 ±8	172 ±9	172 ±9
BMI, kg/m2	27 ±3	27 ±3	26 ±3	27 ±3	26 ±3	27 ±3
BSA, m2	1.94 ±0.19	1.97 ±0.19	1.89 ±0.15	1.90 ±0.16	1.89 ±0.17	1.91 ±0.22
SBP, mmHg	132 ±21	130 ±18	136 ±17	135 ±16	138 ±22	131 ±10
DBP, mmHg	79 ±9	77 ±13	79 ±8	77 ±10	81 ±7	78 ±5
Serum creat, μmol/L	90 ±12	121 ±21	90 ±12	127 ±22	87 ±11	119 ±18

Binary variables presented as n (%), continuous variables presented as mean ±SD

Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure.

Donors that were excluded from donation in the mGFR-cohort

From 2006 to 2018, 173 potential donors were excluded from donation (Table 5). Mean±SD eGFR of these donors was 81±14 mL/min/1.73m2 compared to 91±13 mL/min/1.73m2 in the accepted group (P<0.001). In 16 of these donors, insufficient mGFR was the main reason for disapproval. In 20 donors, insufficient mGFR was one of multiple reasons for disapproval. In two donors, mGFR was considered too low for the recipient. The characteristics of the donors that were declined due to insufficient mGFR (N = 38) are also shown in Table 5. Mean±SD mGFR of these donors was 70±12 mL/min/1.73m2 (P<0.001 vs. accepted donors). Female donors were more likely to be declined fordonation due to low GFR (84% female in the “declined due to GFR” group vs.54% female in the accepted group (P<0.001)). Declined donors were also significantly older with smaller body size measurements compared to accepted donors.

Table 5

Characteristics of “accepted”, “declined” and “declined due to low mGFR” donors in the mGFR-cohort.

	Accepted*	Declined	P vs. accepted	Declined due to mGFR	P vs. accepted
Number, n	250	173	-	38	-
CKD-EPI, mL/min/1.73m2	91 ±13	81 ±14	<0.001	70 ±12	<0.001
CrCl, mL/min	127 ±33	106 ±31	<0.001	77 ±23	<0.001
mGFR, mL/min	115 ±22	96 ±22	<0.001	72 ±8	<0.001
mGFR/BSA, mL/min/1.73m2	101 ±15	88 ±18	<0.001	71 ±9	<0.001
Age, years	53 ±10	60 ±11	<0.001	66 ±6	<0.001
Female sex, n (%)	134 (54)	100 (8)	0.39	32 (84)	<0.001
Caucasian race, n (%)	250 (100)	173 (100)	-	38 (100)	-
Weight, kg	80 ±14	78 ±14	0.06	69 ±9	<0.001
Height, cm	174 ±9	171 ±9	0.001	167 ±6	<0.001
BMI, kg/m2	26 ±3	27 ±4	0.73	25 ±3	0.01
BSA, m2	1.96 ±0.20	1.90 ±0.20	0.01	1.77 ±12	<0.001
SBP, mmHg	128 ±14	131 ±14	0.02	129 ±10	0.50
DBP, mmHg	76 ±9	77 ±10	0.90	76 ±9	0.89
Use of antihypertensive medication, n (%)	43 (17)	46 (27)	0.02	11 (29)	0.08
Serum creat, μmol/L	74 ±13	79 ±13	<0.001	82 ±15	0.002

*Donors who were accepted, donated and had 5-year follow-up available

Binary variables presented as n (%), continuous variables presented as mean ±SD

Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; SD: Standard deviation.

Discussion

This study aimed to compare pre- and post-donation eGFR of living kidney donors between two centers that base the decision to accept a donor based on eGFR and a center that uses mGFR for decision making. We hypothesized that, due to systematic underestimation of mGFR by eGFR, mGFR-based screening allows acceptance of donors with lower pre-donation eGFR than a center that only uses eGFR. Findings confirm that pre-donation eGFR can indeed underestimate pre-donation mGFR, especially in younger donors. In the overall cohort, we found lower pre-donation eGFR in a center that uses mGFR for donor screening than in centers that use eGFR. However, when focusing on more recent data, these differences disappear, and therefore, routine use of mGFR for living kidney donor screening does not seem to add value compared to using eGFR on population level. Lastly, we did not find differences in five-year post-donation eGFR between centers that use eGFR- or mGFR-based donor screening.

Measuring the clearance of exogenous filtration markers is the best available method to assess GFR [18]. Because mGFR has cost and availability issues, eGFR equations are most widely used. In line with the literature, our results show an underestimation of mGFR by eGFR [7-13]. Mean pre-donation eGFR was lower in the mGFR-cohort, where clinical decision making was based on mGFR, than in centers that only used eGFR. However, when taking time into account, we saw that both eGFR-cohort1 and eGFR-cohort2 accepted donors with lower pre-donation eGFR after 2009 compared to before 2009, resulting in disappearance of the differences in pre-donation eGFR. A reasonable explanation for this is that both centers accepted older donors after 2009 compared to before 2009, whereas in the mGFR-cohort there was no difference in eGFR and age before and after 2009. The increase in age and the consistency of BMI over time that we found in this study are consistent with previous results [19]. The introduction of a national living kidney donor guideline in the Netherlands in 2008, in which age-adapted thresholds for pre-donation eGFR were introduced might have contributed to more uniformity in donor selection policies resulting in more similarity in recent donor characteristics [3]. Our findings are in line with a previous study by Gaillard et al., who concluded that mGFR is the most efficient method for living donor screening, but when not available, age-adapted thresholds for eGFR are also convenient [20]. Furthermore, we did not find differences in five-year post-donation eGFR, despite differences in pre-donation GFR assessment methods, which further supports the impression that routine use of mGFR does not have an effect on mean eGFR on population level.

While routinely using mGFR in donor screening does not have an effect on the total population characteristics, we did find that in half of the donors from the mGFR-cohort, mGFR was underestimated by eGFR ≥10 mL/min/1.73m2 and in 20% of the donors even >20 mL/min/1.73m2. Reasons for donor exclusion are mostly multifactorial and rarely solely based on insufficient kidney function. Still, kidney function plays a major role in the decision-making process of accepting a potential donor, and played an important role in the decision of 22% of the declined donors in the mGFR-cohort. If insufficient eGFR is a decisive factor in the decision to decline a potential donor, confirmative GFR assessment might be needed, especially in younger donors. This is supported by the finding that donors with the lowest 10% eGFR were younger in the mGFR-cohort (where mGFR was used) than in eGFR-cohort1 and eGFR-cohort2 (where eGFR was used). Measuring creatinine clearance (CrCl) from 24-hour urine samples might be an alternative. However, besides the sampling errors that could cause measurement inaccuracy, 24h CrCl tends to overestimate mGFR [21]. This overestimation increases in the lower ranges of GFR, possibly due to an increased tubular secretion of creatinine, causing an increased error in donors with marginal kidney function. For the majority of potential donors, 24h CrCl combined with eGFR will be sufficient to assess kidney function, because the mGFR will likely be in between those values. However for borderline cases with for example a too low eGFR and acceptable 24h CrCl, it is dangerous to assume that the 24h CrCl will be closer to the mGFR value than the eGFR value. In such cases additional mGFR testing would be useful.

The current guidelines do not clearly specify how GFR should be assessed before living kidney donation [2, 3, 6]. This study supports the concept that assessment of mGFR is not needed in every donor, but could be considered for a selected group of potential donors, for example young donors with an insufficient eGFR, consistent with previous results [20]. The previously developed online calculator from Huang et al., that calculates the probability to reach a specific pre-donation mGFR threshold based on pre-donation eGFR, age, sex and race, could be a supportive tool to distinguish between donors who could and who likely do not benefit from confirmatory mGFR testing [22]. In our study, only age was associated with an underestimation of mGFR by eGFR >20 mL/min/1.73m2, and we did not identify other characteristics that led to underestimation of mGFR. Future studies should focus on more detailed characterization of donors in whom eGFR is inaccurate.

Strengths of this study include the extensive renal function measurements with 125I-Iothalamate in the mGFR-cohort. Furthermore, the comparisons were made in relatively large populations throughout the whole country with long-term follow-up. Also, consistent use of methods for kidney function determination in the centers limits confounding by indication. Yet, our study also has several limitations. First of all, the decision to accept a donor is multifactorial, and does not only rely on pre-donation GFR. Yet, we were able to identify 16 donors that were declined due to insufficient GFR and another 22 in whom GFR was one of multiple reasons for disapproval. Both estimated and measured GFR of these donors were lower than in the accepted donors. Data on declined donors in the other centers were not available. Lastly, the three populations mainly consisted of Caucasian donors. It is known that people of African ancestry (i.e. African Americans, Black U.K. people) on average have higher muscle mass, possibly leading to larger underestimation of GFR by the creatinine-based equations [23]. However, because end-stage kidney disease is more prevalent among African and African American ethnicities [23], extra caution might be needed when accepting donors from these ancestries with lower pre-donation eGFR. Recently, it has been suggested to remove the racial correction factors in the eGFR equations, which led to more underestimation of GFR in black individuals in the general population as compared to white individuals. How these equations affect the applicability of the results of the current study (i.e. in a population with higher GFR than the general population) remains to be investigated.

In conclusion, this study shows that routinely measuring GFR using exogenous filtration markers did not lead to a detectable difference in the donor population compared to using eGFR. These results suggest that the routine use of mGFR does not seem to result in acceptance of donors with lower pre-donation eGFR on the population level, neither does it result in differences in five year post-donation eGFR. For the majority of potential donors eGFR and/or 24h CrCl may provide sufficient guidance. Future studies are needed to confirm our results and investigate whether a group could be identified (e.g. young donors) that might benefit from confirmatory mGFR testing.

Distribution of pre-donation BMI before and after 2009 per center.

Differences between mean pre-donation BMI were tested using the independent sample T-test, P-values are shown in the figure.

(DOCX)

Click here for additional data file.

Distribution of five-year post-donation eGFR (CKD-EPI) per center.

Differences between mean five-year post-donation eGFR were tested using the independent sample T-test, P-values are shown in the figure. Five-year post-donation mGFR in the mGFR-cohort was added on the right in the figure.

(DOCX)

Click here for additional data file.

Distribution of five-year post-donation eGFR (CKD-EPI) before and after 2009 per center.

Differences between mean five-year post-donation eGFR were tested using the independent sample T-test, P-values are shown in the figure. Five-year post-donation mGFR before and after 2009 in the mGFR-cohort was added on the right in the figure.

(DOCX)

Click here for additional data file.

Distribution of pre-donation 24hCrCl before and after 2009 in the mGFR-cohort and eGFR-cohorteGFR-cohort2.

Differences between mean pre-donation 24hCrCl were tested using the independent sample T-test, P-values are shown in the figure. Pre-donation mGFR in the mGFR-cohort was added on the right in the figure.

(DOCX)

Click here for additional data file.

Distribution of pre-donation eGFR (CG) before and after 2009 per center.

Differences between mean pre-donation eGFR were tested using the independent sample T-test, P-values are shown in the figure. Pre-donation mGFR in the mGFR-cohort was added on the right in the figure.

(DOCX)

Click here for additional data file.

Distribution of pre-donation eGFR (MDRD) before and after 2009 per center.

Differences between mean pre-donation eGFR were tested using the independent sample T-test, P-values are shown in the figure. Pre-donation mGFR in the mGFR-cohort was added on the right in the figure.

(DOCX)

Click here for additional data file.

Pre- and five year post-donation bias between eGFR and mGFR/BSA in the mGFR-cohort.

Bias calculated as mGFR/BSA−eGFR. Abbreviations: eGFR: Estimated glomerular filtration rate; mGFR/BSA: Measured glomerular filtration rate corrected for BSA; BSA: Body surface area; IQR: Interquartile range.

(DOCX)

Click here for additional data file.

Pre- and post-donation bias between CrCl and mGFR/BSA in the mGFR-cohort.

Bias calculated as CrCl–mGFR/BSA. Abbreviations: CrCl: 24 hour creatinine clearance; mGFR/BSA: Measured glomerular filtration rate corrected for BSA; BSA: Body surface area; SD: Standard deviation; IQR: Interquartile range.

(DOCX)

Click here for additional data file.

Pre-donation characteristics of donors from the mGFR-cohort and eGFR-cohorteGFR-cohort2 with an underestimation of CrCl by eGFR ≥10 mL/min.

Binary variables presented as n (%), continuous variables presented as mean ±SD. Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; SD: Standard deviation.

(DOCX)

Click here for additional data file.

Pre-donation characteristics of donors from the mGFR-cohort with an overestimation of mGFR/BSA by eGFR.

Binary variables presented as n (%), continuous variables presented as mean ±SD. Abbreviations: CKD-EPI: Chronic kidney disease epidemiology collaboration equation; CrCl: Creatinine clearance; mGFR: Measured GFR; BMI: Body mass index; BSA: Body surface area; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; SD: Standard deviation.

(DOCX)

Click here for additional data file.

Number of donors with eGFR above and under age-adapted threshold according to the Dutch Living Kidney Donor Guidelines.

Abbreviations: eGFR: Estimated glomerular filtration rate.

(DOCX)

Click here for additional data file.

GFR measurement mGFR-cohort.

(DOCX)

Click here for additional data file.

3 Feb 2022

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Reviewers' comments:

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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**********

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Reviewer #1: Thank you for asking me to review this paper. I’m afraid I don’t think the study as presented is well designed to answer the questions posed in the title and introduction, as no assessment of the e/mGFR result on decision making regarding donor acceptance is made. e/mGFR results for screened but non-proceeding donors are not presented. The cohorts compared are not directly comparable (e.g., donors from different time periods from different centres with different decision makers are being compared, no attempt is made to undertake or present an analysis adjusted for potential confounders). I have provided further detailed comments below.

Title

1. 'Impact of measured versus estimated glomerular filtration rate-based screening on living kidney donor characteristics: A multicenter cohort study.' - The study is not a multicenter single cohort study as implied. It appears to be a study of multiple cohorts?

Abstract

2. Line 23: ‘Most transplant centers use estimated glomerular filtration rate (eGFR) for evaluation of potential living kidney donors.’ – This statement isn’t true for centers outside the Netherlands e.g., in the USA and UK kidney function is measured prior to donation. Suggest edit this sentence to read ‘Most transplant centers in the Netherlands’

3. Line 24: ‘eGFR underestimates GFR’ – This statement isn’t true for all. eGFR is likely to overestimate kidney function in those with low BMI, and individuals from certain ethnic groups e.g., Chinese, East Asian. Suggest reword as ‘eGFR can underestimate GFR’ or ‘eGFR often underestimates GFR in healthy donors’.

4. Line 27: I think the word ‘acceptation’ should be ‘acceptance’.

5. Abstract results section: you need to state what results are being presented. You state that ‘Donor age was similar among the cohorts mGFR-cohort 53+/- 10 years’ but you don’t state whether this is mean age with standard deviation, or median age with IQR presented. The same is true for the GFR results – are you presenting means? If so state this and state what the +/- relates to, presumably standard deviation?

6. Line 38: Please can you give the specific p value, not ‘p<0.05’. It is difficult to interpret whether there is strong evidence to support a difference e.g., p=0.001 vs weak evidence to support a difference e.g., p=0.048. There is nothing special about a p value of 0.05 that makes something significant or not, it’s an arbitrary threshold. See: https://www.tandfonline.com/doi/full/10.1080/00031305.2019.1583913 This point applies to the methods in which it is stated that a p value <0.05 is 'statistically significant'.

7. Lines 44 – 46: ‘we did not show that the routine use of mGFR in donor screening leads to inclusion of donors with a lower pre-donation eGFR’ – This finding hasn’t been presented in the results section of the abstract and should be if it is to be referenced here. Suggest adding proportion of those not donating due to inadequate e/mGFR added to each cohort?

8. Line 47: ‘but young donors with insufficient eGFR might benefit from confirmatory mGFR testing’ – There’s no evidence presented in the abstract to justify this statement. Suggest adding to results or removing the statement.

Introduction

9. Lines 51-53: ‘The main goal of living kidney donor evaluation is to assess whether a donor will retain sufficient kidney function after donation for a life-long safe kidney function.’ – This sentence isn’t quite true. The main goal is not just to assess whether a donor will be left with adequate kidney function after donation, but also to determine if they will survive the nephrectomy operation (people may have more than adequate kidney function but be unsuitable for other medical reasons) and to determine if they are psychologically fit to donate.

10. Line 57: ‘The latter is expensive and laborious and therefore much less widespread in use’ is not true. Iohexol is cheap and iohexol mGFR is easy to do. Please also state that you are still only talking about the Netherlands, in the UK and USA kidney function is measured prior to donation.

11. Line 69: ‘higher ranges of GFR, true GFR is underestimated’ please edit this to either state ‘in most White populations’ or ‘most White and Black populations’– I think all the references provided to support this present evidence from largely White European and White American populations, which aren’t the Global majority.

12. Line 75: ‘long-term safety was studied by comparing kidney function five years after donation’ – 5 years after donation is not long-term. In living kidney donation the 20 year follow up data is considered medium term so 5 years is really short term.

Methods

13. Lines 89-90 – please state whether the mGFR cohort have also given written informed consent.

14. Lines 98 and 116 and 126: Why are cohorts for different time periods being compared? As indicated the time/year of assessment may have influenced acceptance of the kidney donors. The cohorts compared should be for the same time periods. This is a major issue – like is not being compared with like.

15. Line 148: ‘mGFR>10’ later in the results you state ‘mGFR ≥10’ – please correct whichever is wrong.

16. Line 148: ‘mGFR>20’ do you mean ‘mGFR≥20’? If so you need to change this in the results as well (e.g., line 173)

17. Lines 152-154: ‘Because reason of exclusion from donation was mostly multifactorial and rarely solely dependent GFR, we did not analyze the number of donors excluded based on kidney function per center.’ – It seemed that the point of the study was to determine if people with low eGFR were being inappropriately prevented from donating because of their inadequate kidney function, therefore this question of reason for exclusion is critical. Otherwise there is little point studying this in donors specifically – you could have simply compared eGFR and mGFR in the same healthy population. The whole aim of the study is to determine the impact of measured versus estimated GFR based screening on living kidney donor acceptance – without presenting data regarding this question the study adds little to existing knowledge re. the performance of m and eGFR measurements.

Results

18. I’m surprised not to see any Bland-Altman plots comparing m and eGFR measurements?

19. Table 1 lacks units in the first column, and an indication of what is being presented outside and within brackets– these need to be added e.g., ‘CKD-EPI’ should be replaced with ‘mean CKD-EPI eGFR +/- standard deviation (ml/min/1.7m2)’; ‘Age’ should be replaced with ‘mean/median age in years +/- SD/IQR’ ‘Sex’ should have ‘Female sex, n (%)’ in the table. All GFRs needs units, as does weight, length, BMI, BSA, SBP, DBP, serum creat etc.

The same is true for Table 2 which needs indications as to whether the results are means, medians etc.

19. Table 2: Why are no tests for difference presented to compare these groups? This isn’t an RCT so it is justifiable to test how comparable the different cohorts are – differences between the groups is important to identify. If they are not comparable then to compare e and mGFRs between the groups without adjustment is not meaningful.

20. I also expected data to presented on those SCREENED for donation, given the title of the paper and the question of the e/mGFR on acceptance of the donor, yet I can’t see any data on those screened who didn’t donate.

21. The analysis of differences in eGFR over time doesn’t address the original question of the paper, and without knowing the impact on the donor (i.e. did donors post 2009 with lower eGFRs get accepted more than before 2009) it adds little to the analysis.

22. Lines 235 and 236: What are the p values attached to? What comparison is being made? It appears to be that you are comparing the eGFR cohorts to the mGFR cohort?

23. Table 3: Table 3 is just presenting data on the same individuals as in Table 2 – so there is no point reproducing variables that won’t change e.g. sex, race.

Discussion

24. Line 271: ‘This study aimed to investigate the effect of using mGFR versus eGFR on donor selection and long-term post-donation kidney function’ – I am afraid the study has not achieved its aims. The analysis presented doesn’t tell me anything about the impact of the e/mGFR on SELECTION and 5 years follow up data is not long-term.

25. I’m afraid a fully adjusted analysis is required to conclude that ‘mGFR based screening allows acceptance of donors with lower pre-donation eGFR than a center that only uses eGFR’.

26. Lines 337-339: ‘It is known that people of African ancestry on average have higher muscle mass, possibly leading to larger underestimation of GFR by the creatinine-based equations.’ – This statement is not correct. This has only really been well described in African ‘migrant’ populations e.g., African Americans, Black UK, and not been well described in African populations in Africa.

Reviewer #2: thank you for asking me to review this paper which confirms that in most cases measuring mGFR did not lead to a detectable difference in donor population compared to using eGFR.

the paper is useful as mGFR is time consuming and expensive and therefore demonstrating that in most cases the additional effort is nor justified.

I wondered if you might give the manuscript to a native English speaker as whilst it is very well written there are a few anomalies in the use of English

the sentence in lines 306-7 has become scrambled

the authors comment on possible differences in estimation of GFR in different racial groups - the authors may want to briefly review the most recent American and British guidance on this which suggests removing correction factors due to race as this is now considered to be an over simplistic classification

the important point about possible continued utility in younger donors is well made

I wondered if the paper might emphasise more the long term safety data comparing kidney function 5 years after donation an not demonstrating any difference depending on original method of GFR measurement for donation

**********

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18 Apr 2022

See response letter in attached files

12 Jun 2022

20 Jun 2022

Reviewers' comments:

Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Author reply: Thank you for reviewing our revised manuscript. We now included a data availability statement at the end of the manuscript.

Review Comments to the Author

Reviewer #1: Thank you for addressing my concerns, and making significant changes to the analysis and manuscript. The paper is much improved, and the more cautious conclusions more appropriate given the limitations of the study.

Table 2 and Table 3 'P vs. mGFRcohort1' should this be 'vs mGFR-cohort' as there's only one.

Table 2 and Table 4: Length should be height

Author reply: We changed “mGFR-cohort1” to “mGFR-cohort” and “Length” to “Height” throughout the manuscript and supplementary data accordingly.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

21 Jun 2022

Impact of measured versus estimated glomerular filtration rate-based screening on living kidney donor characteristics: A study of multiple cohorts.

PONE-D-22-00925R2

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Academic Editor

PLOS ONE

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Reviewers' comments:

27 Jun 2022

PONE-D-22-00925R2

Impact of measured versus estimated glomerular filtration rate-based screening on living kidney donor characteristics: A study of multiple cohorts.

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