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Adequacy of decision-making based on each kidney function estimation method for Japanese living kidney donor candidates: a retrospective observational study

Abstract

Background

Living kidney transplantation comprises the majority of kidney transplantations in Japan. Living kidney donors should be assured of their own health. Therefore, Japanese guidelines define the criterion of kidney function for living donors. Glomerular filtration rates (GFR) ≥ 70 mL/min/1.73 m2 are required for marginal donors. The guidelines require that GFRs of donors be measured by the inulin (In) clearance method (CIn) or the radioisotope method, but these methods can be substituted with the creatinine (Cr) clearance method (CCr). Methods for estimating kidney function are susceptible to error, and decision-making regarding donor eligibility could be affected by the estimation method used. We investigated the adequacy of decision-making based on kidney function estimation methods used in Japanese living kidney donor candidates by comparing CCr or estimated GFR (eGFR), calculated by several equations, and CIn as measured GFR (mGFR).

Methods

In total, 210 people, including 36 actual kidney donor candidates, who had both CIn and CCr measured at Shinshu University Hospital from April 2011 to April 2015, were included. Cr and cystatin C (Cys) levels measured at the same time were used to calculate eGFR (eGFRCr and sGFRCys, respectively). We evaluated the concordance rates of cases whose GFR levels were ≥ 70 mL/min/1.73 m2 in this study and assumed that they were living kidney donor candidates. Only kidney donor candidates underwent an additional sensitivity analysis.

Results

Median CIn and CCr were 55.5 mL/min/1.73 m2 and 68.0 mL/min/1.73 m2, respectively. CCr had the highest tendency to overestimate kidney function. Some participants were incorrectly evaluated as adequate using CCr, despite their mGFR being inadequate for living kidney donors according to the guidelines. These results were independent of sex or actual living kidney donor candidates. The average of eGFRCr and eGFRCys was well correlated with CIn.

Conclusions

Kidney function estimated by CCr is not equal to the mGFR. When using CCr as a kidney function estimation method to determine the adequacy of a living kidney donor, it should be noted that CCr overestimates kidney function. In evaluating adequacy for a marginal donor, GFR estimated by CIn should be assessed.

Background

The number of patients with end-stage kidney disease has been rising, and the number of patients who require kidney transplantation has also been increasing worldwide. Living kidney transplantation comprises the majority of kidney transplantations in Japan because of a lack of cadaveric kidney donors [1]. It is important that the kidney donor be assured of their own health before they are willing to donate a kidney. In particular, they need to be assured that they will not suffer kidney failure after they donate. Therefore, committees of each country performing kidney transplantation have established guidelines for living kidney donors.

The Japanese guidelines for living kidney donation define the criterion of adequate kidney function for the donor as a glomerular filtration rate (GFR) ≥ 80 mL/min/1.73 m2 [2]. If the donor candidate has a lower function than the criterion, a GFR ≥ 70 mL/min/1.73 m2 is allowed as a marginal donor according to the guidelines. Moreover, the guidelines require that the donor candidate GFR be measured by the inulin clearance method (CIn) or the radioisotope method but the creatinine clearance method (CCr) can be substituted [2]. Which method to adopt depends on each kidney transplant center in these circumstances. However, CCr is known to overestimate kidney function among subjects with decreased GFR because creatinine (Cr) can be secreted by renal tubular cells. Therefore, the Consensus Statement of the Amsterdam Forum on the Care of the Live Kidney Donor states that CCr may under or overestimate GFR in patients with normal or near normal kidney function [3].

Other GFR estimation methods based on the estimation formula (eGFR) are simple and widely used but less accurate. An eGFR calculated using the Japanese equation for estimated GFR (eGFRCr) has a standard that 75% of the subjects tested fall within ± 30% of the real GFR [4]. Furthermore, eGFRCr is susceptible to error. Although GFR estimation methods other than eGFRCr exist, differences among these methods and their potential impact regarding donor eligibility testing is not well known. Though CIn is a gold standard method for estimating GFR, it is a challenge because of the required reagent preparation and the need for multiple blood and urine samples. Therefore, only a limited number of facilities conduct CIn testing routinely.

Estimation methods for kidney function of living kidney donor candidates are potentially susceptible to error, and the decision-making regarding donor eligibility could be affected by the estimation method used. But the impact of these differences is not thoroughly known. In addition to this, there is no uniformity as different evaluation methods are used at each transplantation center. The evaluation of donor eligibility may not be a unified standard in Japan for these reasons. We conducted this study to investigate the adequacy of decision-making based on each kidney function estimation method for Japanese living kidney donor candidates through the comparison of CCr or eGFR from several equations and CIn as measured GFR (mGFR).

Methods

Study design

This study was conducted as a single-center retrospective observational study. All subjects who had both their CIn and CCr measured within a 3-day period from April 2011 to April 2015 were included. The data of 210 participants were extracted for this study, which included 36 actual living kidney donor candidates. All 210 participants were included to detect differences between CIn and several GFR estimation methods, because using only actual living kidney donor candidates was insufficient for statistical analysis. To verify whether the results obtained from the analysis of all 210 participants could apply to living kidney donor candidates, we performed a sensitivity analysis limited to actual living kidney donor candidates. Participants’ characteristics and laboratory data were located and extracted from the medical records at Shinshu University Hospital. This study protocol was approved by the Shinshu University Ethical Committee (approval number 3384) and was conducted in accordance with the principles of the Declaration of Helsinki, as revised in 2013.

Methods of measurement

Serum creatinine (Cr) was measured with an enzymatic method using a BM6070 auto biochemical analyzer (JEOL Ltd., Tokyo, Japan). The normal ranges of Cr at our institute were 0.65–1.07 mg/dL (males) and 0.46–0.79 mg/dL (females). Serum cystatin C (Cys) was measured with the latex immunoturbidimetric method using the same analyzer. The normal range of Cys at our institute was 0.60–0.98 mg/L. CCr and eGFR were calculated using the following formula using Cr or Cys.

CIn

CIn was measured using the simple sampling strategy reported previously [5]. Subjects were asked to drink 500 mL water 15 min prior to infusion of inulin. A 1% inulin (Fuji Yakuhin Co. Saitama, Japan) containing saline infusion was started at the pace of 300 mL/h. Thirty minutes after starting inulin administration, the pace of infusion was changed to 100 mL/h. Forty-five minutes after inulin administration, subjects had to urinate completely to empty their bladder and hydrate with 180 mL water orally, after which a blood sample was collected. Blood and urine samples were collected 60 min later (105 min after starting inulin infusion). Measurements of plasma and urine inulin concentrations were performed using an enzymatic method. CIn was calculated using the average of plasma inulin concentration at 45 min and 105 min, as well as urine inulin concentration and urine volume. CIn was calculated per 1.73 m2 body surface area to compare with other kidney function estimating tests as measured GFR. CIn was finally calculated with the following formula.

$$ {\mathrm{C}}_{\mathrm{In}}\;\left(\mathrm{mL}/\min /1.73\;{\mathrm{m}}^2\right)=\frac{\mathrm{Urine}-\mathrm{In}\left(\mathrm{mg}/\mathrm{dL}\right)\times \mathrm{Urine}\kern0.17em \mathrm{Volume}\left(\mathrm{mL}\right)}{\mathrm{Plasma}-\mathrm{In}\left(\mathrm{mg}/\mathrm{dL}\right)\times 60\left(\min \right)}\times \frac{1.73}{\mathrm{BSA}\left({\mathrm{m}}^2\right)} $$

CCr

To calculate the CCr, a 24-h urine collection was performed, and urine volume was recorded. Total amount of Cr evacuation and serum Cr was measured at the same time. The CCr value was calculated per 1.73 m2 body surface area to compare with other kidney function tests. CCr was calculated by the following formula.

$$ {\mathrm{C}}_{\mathrm{C}\mathrm{r}}\;\left(\mathrm{mL}/\min /1.73\;{\mathrm{m}}^2\right)=\frac{\mathrm{Urine}-\mathrm{Cr}\left(\mathrm{mg}/\mathrm{dL}\right)\times \mathrm{Urine}\kern0.17em \mathrm{Volume}\left(\mathrm{mL}/\mathrm{day}\right)}{\mathrm{Serum}-\mathrm{Cr}\left(\mathrm{mg}/\mathrm{dL}\right)\times 1440\left(\min \right)}\times \frac{1.73}{\mathrm{BSA}\left({\mathrm{m}}^2\right)} $$

eGFR

The eGFR was calculated using laboratory data collected at the time CCr and CIn were measured. We used the following formulas to calculate a Cr-based eGFR (eGFRCr) and a Cys-based eGFR (eGFRCys) [6, 7]. These formulas were targeted for Japanese adults and are used most widely in Japan.

eGFRCr (mL/ min /1.73 m2) = 194 × Cr−1.094 ×Age-0.287× 0.739 (if female) [6];

eGFRCys (mL/ min /1.73 m2)

Male eGFRCys = {104 × Cys−1.019 × 0.996Age} − 8 [7]

Female eGFRCys = {104 × Cys−1.019 × 0.996Age×0.929} − 8 [7]

In addition to these equations, the average of eGFRCr and eGFRCys (eGFRCr+Cys) was calculated and used for comparison, because it has been reported that eGFRCr+Cys is more accurate [8].

\( {\mathrm{eGFR}}_{\mathrm{Cr}+\mathrm{Cys}}\;\left(\mathrm{mL}/\min /1.73\;{\mathrm{m}}^2\right)=\frac{\mathrm{eGFR}-\mathrm{Cr}+\mathrm{eGFR}-\mathrm{Cys}}{2} \)

Moreover, we used another Cr-based GFR equation, The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation (eGFR-CKDEPICr) in this study [9].

eGFR − CKDEPICr (mL/ min /1.73 m2)

\( \mathrm{Male},\mathrm{Cr}\le 0.9\ \mathrm{mg}/\mathrm{dL},\mathrm{eGFR}-{\mathrm{CKDEPI}}_{\mathrm{Cr}}=141\times {\left(\frac{\mathrm{Cr}}{0.9}\right)}^{-0.411}\times {0.993}^{\mathrm{Age}} \) [9]

\( \mathrm{Male},\mathrm{Cr}>0.9\ \mathrm{mg}/\mathrm{dL},\mathrm{eGFR}-{\mathrm{CKDEPI}}_{\mathrm{Cr}}=141\times {\left(\frac{\mathrm{Cr}}{0.9}\right)}^{-1.209}\times {0.993}^{\mathrm{Age}} \) [9]

\( \mathrm{Female},\mathrm{Cr}\le \kern0.36em 0.7\ \mathrm{mg}/\mathrm{dL},\mathrm{eGFR}-{\mathrm{CKDEPI}}_{\mathrm{Cr}}=141\times {\left(\frac{\mathrm{Cr}}{0.9}\right)}^{-0.329}\times {0.993}^{\mathrm{Age}} \) [9]

\( \mathrm{Female},\mathrm{Cr}>\kern0.36em 0.7\ \mathrm{mg}/\mathrm{dL},\mathrm{eGFR}-{\mathrm{CKDEPI}}_{\mathrm{Cr}}=141\times {\left(\frac{\mathrm{Cr}}{0.9}\right)}^{-1.209}\times {0.993}^{\mathrm{Age}} \) [9]

All eGFR data were presented as mL/min/1.73 m2 and used for comparison.

Outcome

We compared each kidney function estimate with CIn. Differences between eGFR and CIn were assessed. Moreover, we evaluated the concordance rates of the cases whose GFR was determined to be ≥ 70 mL/min/1.73 m2, which is the Japanese marginal donor criterion, presuming the participants of this study to be kidney donor candidates.

Statistical analysis

All obtained data were statistically analyzed. Continuous variables were presented as medians and ranges (minimum–maximum), and a Mann-Whitney U test or Wilcoxon signed-rank test was used to compare between groups. Categorized variables were presented as percentages, and a chi-squared test or a Fisher’s exact test was used to detect between-group differences. SPSS software (ver. 22; IBM Corp., Armonk, NY USA) was used for these statistical analyses.

Results

Participant characteristics

Table 1 shows the characteristics of the 210 participants. Mean age was 52.5 years, and men accounted for 60% of all participants. Mean body surface area for men was 1.72 m2 and for women was 1.50 m2. Median Cr level was 1.13 mg/dL, and median Cys level was 1.24 mg/L. Median level of excreted urine protein was 0.5 g/day. Median volume of urine Cr excretion was 1025 mg/day. Thirty-six participants were assessed as actual living kidney donor candidates. Although their body weights were significantly lower than all other participants, their serum albumin levels were significantly higher. Their Cr and Cys levels were significantly lower than all participants. In addition to these tendencies, their urinary protein excretion was lower.

Table 1 Patient characteristics

Comparison between CIn and other kidney function estimation tests

Results of the comparison between CIn and other kidney function estimation tests using all participant data are shown in Table 2. Compared with CIn, CCr-estimated kidney function results were the highest among the results of all kidney function estimation tests. Kidney function estimated by eGFRCys and eGFR-CKDEPICr was significantly higher than that estimated by CIn. In contrast, kidney function estimated by eGFRCr was significantly lower than that estimated by CIn. Kidney function estimated by eGFRCr+Cys and CIn showed no significant difference.

Table 2 Comparison of GFR estimation methods to inulin clearance

To evaluate the accuracy of each test method, we calculated the percentage of estimates falling within ± 30% of mGFR (P30), the percentage falling within ± 10% of mGFR (P10), and the absolute error between CIn and the other eGFR methods. eGFRCr+Cys showed the highest accuracy for both P10 and P30 and the lowest error, whereas CCr showed the lowest accuracy for P30 (57%).

Evaluation of kidney donor eligibility data using each kidney function estimation test

Figure 1 shows scatter plots for CIn and other kidney function estimation models. Study participants’ CIn was widely distributed from chronic kidney disease (CKD) stage 1 to stage 5.

Fig. 1
figure 1

Relationships of GFR estimation method and Inulin clearance. Figure 1 shows scatter plots for CIn and other kidney function estimation models. a CIn and CCr, b CIn and eGFRCr, c CIn and eGFRCys, d CIn and eGFRCr+Cys, e CIn and eGFR-CKDEPICr. For reference, auxiliary line which equal to CIn was presented. Abbreviations: GFR glomerular filtration rate; eGFR estimated GFR based on Cr (creatinine) Cys (cystatin C), Cr + Cys (an average of Cr + Cys), or CKDEPICr (a Cr-based equation from The Chronic Kidney Disease Epidemiology Collaboration ([CKD-EPI]); CIn inulin clearance; CCr creatinine clearance

Figure 1a shows the relationship between CIn and CCr. The correlation between CIn and CCr was determined to be good (r = 0.889), but the values of CCr were greater than those of CIn from low GFR to high GFR. This suggests that CCr estimates higher kidney function, without regard to GFR level. The number of cases in which GFR was measured by CIn to be ≥ 70 mL/min/1.73 m2 was 81. However, the number of cases in which GFR was estimated by CCr to be ≥ 70 mL/min/1.73 m2 increased to 100. Among these 100 cases, the number of cases in which the GFR measured by CIn was < 70 mL/min/1.73 m2 was 23. Therefore, 23% of candidates were incorrectly evaluated as adequate using CCr despite the true GFR being inadequate for a living kidney donor. In contrast, lower kidney function was estimated using CCr in six (7%) of the 81 cases in which GFR measured by CIn ≥ 70 mL/min/1.73 m2.

Figure 1b shows the relationship between CIn and eGFRCr. A good correlation was observed between CIn and eGFRCr (r = 0.888). The correlation between CIn and eGFRCr was mostly good in patients with GFR < 60 mL/min/1.73 m2, which was the definition of CKD, but eGFRCr tended to underestimate kidney function in patients with functionally normal kidneys. If eGFRCr was used to evaluate the donor adequacy of the participants in this study, kidney function was overestimated in 7/62 cases (11%) and underestimated in 12/81 cases (15%), compared to that estimated using CIn.

Figure 1c shows the relationship between CIn and eGFRCys. The relationship between CIn and eGFRCys displayed great variation, and the correlation between CIn and eGFRCys was worse than that between the other kidney function tests (r = 0.882). If eGFRCys was used to evaluate the donor adequacy of the participants in this study, kidney function was overestimated in 15/84 cases (18%) and underestimated in 12/81 cases (15%), compared to that estimated using CIn.

Figure 1d shows the relationship between CIn and eGFRCr+Cys. The average of eGFRCr and eGFRCys improved the underestimation due to eGFRCr and the variation due to eGFRCys. The best correlation was observed between CIn and eGFRCr+Cys (r = 0.903). If eGFRCr+Cys was used to evaluate donor adequacy of participants in this study, kidney function was overestimated in 7/77 cases (9%) and underestimated in 10/81 cases (12%), compared to that estimated using CIn.

Figure 1e shows the relationship between CIn and eGFR-CKDEPICr. A good correlation was observed between CIn and eGFR-CKDEPICr (r = 0.890). The accuracy of eGFR-CKDEPICr was mostly good for CKD, but eGFR-CKDEPICr tended to underestimate kidney function in patients with functionally normal kidneys. If eGFR-CKDEPICr was used to evaluate participant donor adequacy in this study, kidney function was overestimated in 8/81 cases (10%) and underestimated in 12/81 cases (16%), compared to that estimated using CIn.

Among the several kidney function estimation tests conducted in this study, CCr had the highest tendency to overestimate kidney function, and CCr showed a tendency to estimate kidney function the highest.

Impact of sex on estimation accuracy

Some GFR estimation formulas use different coefficients in the case of a female, because males and females have different average body sizes and body components, such as muscle volume. Therefore, we investigated whether differences of sex affected relationships between estimated kidney function and CIn (Fig. 2). The results showed that females had greater a variation than males in each relationship. Especially in the relationship between CCr and CIn, females tended to present higher CCr than CIn as well as greater variation.

Fig. 2
figure 2

Impact of sex on GFR estimation accuracy. Figure 2 shows scatter plots for CIn and other kidney function estimation models dividing into sex. a CIn and CCr, male, b CIn and CCr, female, c CIn and eGFRCr, male, d CIn and eGFRCr, female, e CIn and eGFRCys, male, f CIn and eGFRCys, female, g CIn and eGFRCr+Cys, male, h CIn and eGFRCr+Cys, female, i CIn and eGFR-CKDEPICr, male, j CIn and eGFR-CKDEPICr, female. For reference, auxiliary line which equal to CIn was presented. Abbreviations: GFR glomerular filtration rate; eGFR estimated GFR based on Cr (creatinine) Cys (cystatin C), Cr + Cys (an average of Cr + Cys), or CKDEPICr (a Cr-based equation from The Chronic Kidney Disease Epidemiology Collaboration ([CKD-EPI]); CIn inulin clearance; CCr creatinine clearance

Impact of the amount of creatinine excretion on estimation accuracy

Because urine Cr excretion differed widely among participants, we checked whether GFR estimation accuracy is affected by urine Cr excretion. We divided participants into two groups with a median Cr excretion of 1025 mg/day and compared the two groups. Male sex was predominant and body surface area was significantly large in the high Cr excretion group. The relationships between CIn and each GFR estimation method for each group are shown in Appendix A. Since CIn was significantly different between the two groups, we evaluated accuracy by comparing errors between the GFR estimation methods and CIn. The results are presented in Table 3. The kidney function values were higher with CCr than with CIn, regardless of Cr excretion. eGFRCr was significantly lower in the high Cr excretion group. Accuracy of eGFRCys was not affected by Cr excretion. Errors between eGFRCr+Cys and CIn were small regardless of Cr excretion. eGFR-CKDEPICr was underestimated in the high Cr excretion group.

Table 3 Impact of creatinine excretion

Evaluation in living kidney donor candidates

This study included participants with proteinuria or obviously low kidney function, who could not be considered originally as living kidney donors. Therefore, we performed a sensitivity analysis in only living kidney donor candidates (Fig. 3). A total of 36 subjects were included. Median CCr was 87.1 mL/min/1.73 m2, and median CIn was 85.0 mL/min/1.73 m2. Median CCr was significantly higher than that of CIn in these donor candidates. In 15% of these cases, the levels were ≥ 70 mL/min/1.73 m2 when using CCr, but the levels were < 70 mL/min/1.73 m2 when using CIn, illustrating how CCr overestimates kidney function. Median eGFRCr was 66.7 mL/min/1.73 m2, which was significantly lower than that using CIn. Concerning the evaluation of living donor adequacy, kidney function was overestimated in 6% of cases and underestimated in 27% cases. Median eGFRCys was 75.1 mL/min/1.73 m2, which showed no significant difference compared to CIn. Concerning the evaluation of living donor adequacy, kidney function was overestimated in 10% of cases and underestimated in 10% of cases. Median eGFRCr+Cys was 71.4 mL/min/1.73 m2, which presented no significant difference with CIn. Overall, kidney function was overestimated in 5% of cases and underestimated in 18% of cases. Median eGFR-CKDEPICr was 75.6 mL/min/1.73 m2, which did not imply significant differences with CIn. However, concerning the evaluation of living donor adequacy, kidney function was overestimated in 11% and underestimated in 18% of cases.

Fig. 3
figure 3

GFR estimation methods in living kidney donor candidates. Figure 3 shows scatter plots for CIn and other kidney function estimation models in living kidney donor candidates. a CIn and CCr, b CIn and eGFRCr, c CIn and eGFRCys, d CIn and eGFRCr+Cys, e CIn and eGFR-CKDEPICr. For reference, auxiliary line which equal to CIn was presented. Abbreviations: GFR glomerular filtration rate; eGFR estimated GFR based on Cr (creatinine) Cys (cystatin C), Cr + Cys (an average of Cr + Cys), or CKDEPICr (a Cr-based equation from The Chronic Kidney Disease Epidemiology Collaboration ([CKD-EPI]); CIn, inulin clearance; CCr creatinine clearance

CCr had the highest percentage in terms of overestimation of kidney function for classifying adequate donors in actual living kidney donor candidates.

Discussion

In this study, we investigated the relationships between mGFR using CIn and several kidney function estimation tests and evaluated the impact of these tests in determining the adequacy for living kidney donors. Our findings reveal that CCr overestimates kidney function the most when compared with eGFRCr, eGFRCys, eGFRCr+Cys, and eGFR-CKDEPI. Estimated kidney function obtained using CCr is not equal to mGFR. Therefore, there is a risk that living kidney donor candidates with insufficient kidney function are falsely evaluated as adequate for kidney donation when CCr is used. A previous study reported that CCr overestimated the GFR; especially in cases with low GFR, the CCr showed a marked tendency to overestimate the GFR [10]. This phenomenon is thought to occur due to creatinine not only being filtrated through the glomeruli but also excreted by the renal tubules. As for estimating GFR using CCr, the Japanese guidebook for CKD in 2012 described that CCr was 30% higher than mGFR and needed to be multiplied by the coefficient 0.715 for converting to GFR [4]. According to this guidebook, the formula of GFR = 0.715 × CCr can be established. Using this formula could decrease the overestimation using CCr, but the Guidelines for Japanese Living Kidney Donors has not included this conversion [2]. Therefore, it is not known whether or not this converting formula is being used in the clinical setting. If this converting formula is applied to participants of this study, the number of cases of overestimation decreased to 3/59 cases (5%). However, using that same converting formula, the number of cases of underestimation increased to 25/81 cases (31%). The coefficient 0.715 encouraged underestimation for donors in this study. The coefficient 0.715 could be too low for the normal GFR population, so further study is needed. Kidney donations from candidates with insufficient GFR could not only lead to poorer transplanted kidney function but this could also adversely affect the long-time prognosis of an altruistic kidney donor. Revision of the Japanese donor guidelines concerning acceptable estimation methods for GFR is thought to be needed based on the results of this study.

In this study, we revealed the differences among several kidney function estimation methods for the evaluation of the eligibility of potential donors. The tendency of eGFRCr and eGFR-CKDEPICr was to underestimate kidney function and that of eGFRCys was to overestimate kidney function. The method that most closely aligned with mGFR was eGFRCr+Cys. The reason why Cr-based GFR estimation formulas such as eGFRCr and eGFR-CKDEPICr underestimate kidney function could be due to the characteristics of Cr behavior, which are affected by muscle volume and food intake as well as glomerular filtration and tubular secretion. CKD patients whose data were used to create GFR estimation formulas, in general, have lower muscle volume and less food intake than a healthy population. Therefore, it has been reported that applying these equations to groups with high GFR could underestimate their renal function. Actually, errors between CIn and eGFRCr or eGFR-CKDEPICr were significantly large in high Cr excretion participants. Matsuo et al. reported the possibility that eGFRCr might underestimate kidney function in the population with normal kidney function in a report introducing the Japanese GFR equation [6]. Several other studies concerning kidney function of living kidney donor candidates have presented that eGFRCr was lower than mGFR, corroborating our findings in the current study [11,12,13,14]. The risk of underestimation should be considered when healthcare professionals use Cr-based equations as a screening criterion for living kidney donors. Although eGFR-CKDEPICr was intended to increase the accuracy in the higher GFR population by using two types of estimation formulas depending on the Cr value, eGFR-CKDEPICr in this study showed no superiority over eGFRCr, and eGFR-CKDEPICr showed a larger deviation from mGFR in the population with good kidney function. For Cys-based testing, eGFRCys generally showed a higher eGFR value than mGFR, although eGFRCys did show a more accurate GFR value in kidney donor candidates. However, it is recommended that other kidney function estimation tests be checked when applying estimation formulas to actual candidates, because the deviation of eGFRCys was relatively large and it is known that Cys might be affected by thyroid function. eGFRCr+Cys did show a value that was closer to mGFR than Cr-based equations and ameliorated the deviations that were shown by eGFRCys. In fact, eGFRCr+Cys showed the greatest accuracy of all equations investigated in this study. Even though eGFR can be easily checked by a single blood sampling, it is important to know the differences in characteristics between each equation for a more informed and accurate evaluation.

This study suggests that CCr and each GFR estimation formula studied is less accurate in evaluating female participants. One of the reasons is that females, on average, have a significantly smaller body surface area than males. Individuals with smaller body surface areas show larger estimated values than their actual GFR due to the correction factor of 1.73 m2 body surface area. This correction causes tendencies to deviate from mGFR in smaller subjects. If a female with a small body mass is being considered to be a potential living kidney donor candidate, the use of CCr should be avoided for evaluating her kidney function.

This study showed that kidney function could be overestimated or underestimated to varying degrees irrespective of the kidney function estimation method. This finding suggests that it is insufficient to evaluate kidney function using only one estimation method. It is important to use a number of evaluation methods to determine the candidate’s adequacy for donation. For example, it stands to reason that the average of eGFRCr and eGFRCys should be used for screening and that mGFR should be used for confirmation. The guidelines recommend CIn and a radioisotope method for measuring GFR. A radioisotope method is relatively expensive and only limited facilities can perform this testing. Therefore, a more aggressive application of CIn is desired. CIn is one of the most reliable methods for measuring GFR and is considered to be the gold standard. CIn requires no special equipment and can be performed at any facility. Because the CIn measurement method is rather complex, few facilities are performing it currently. However, it is desirable to create an in-hospital system that can measure CIn daily at any facility that performs kidney transplantation.

This study revealed that CCr overestimates kidney function. Therefore, living kidney donors evaluated as adequate for donation using CCr need long-term monitoring to determine whether or not their kidney function worsens after the kidney donation. In particular, as marginal donor cases determined by CCr are considered to have a risk of worsening kidney function, these patients need closer and more long-term follow-up. If cases judged by CCr as marginal donors do not show worsening kidney function through longitudinal observation, de-escalation of the Japanese criteria for living kidney donors might be possible. Longitudinal follow-up of post kidney transplant donors and accumulation of data are required to address this issue definitively.

This study has several limitations. First, it was conducted with data from a single center, and the collected data were obtained from patients visiting our hospital. Therefore, the results cannot be simply applied to living kidney donor candidates who belong to a super healthy population. Second, perfect urine collection is needed in the process of measuring CIn, but residual urine volume in the bladder was not checked in this study. Other GFR affirming methods, such as the radioisotope method, were not conducted in this study because of its retrospective study design. Therefore, there might be some susceptibility to error in the value measured by CIn. In addition, although it is known that Cys is affected by thyroid function, thyroid function could not be checked in all participants because of the retrospective study design. Therefore, this study may contain potential errors.

Conclusions

Kidney function estimated by CCr is not equal to mGFR. When using CCr as a kidney function estimation method to determine the adequacy of a living kidney donor, consideration that CCr might overestimate kidney function is required. It is important to combine multiple eGFR values calculated by each equation to evaluate deviation. Particularly in the case of evaluating the adequacy of marginal donor, GFR estimated by CIn should be required.

Availability of data and materials

The datasets used and analyzed concerning this study are available from the corresponding author on reasonable request.

Abbreviations

CCr :

Creatinine clearance

CIn :

Inulin clearance

CKD:

Chronic kidney disease

CKD-EPI:

The Chronic Kidney Disease Epidemiology Collaboration

Cr:

Creatinine

Cys:

Cystatin C

eGFR:

Estimated GFR

eGFR-CKDEPICr :

eGFR as calculated using the Cr-based CKD-EPI equation

eGFRCr :

eGFR as measured by creatinine

eGFRCr+Cys :

Average of eGFRCr and eGFRCys

eGFRCys :

eGFR as measured by cystatin C

GFR:

Glomerular filtration rate

In:

Inulin

mGFR:

Measured GFR

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Acknowledgments

The authors would like to thank Editage (www.editage.com) for English language editing.

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Authors and Affiliations

Authors

Contributions

KH contributed to the research idea and study design. KH, MH, TM, TO, and IO contributed to the data acquisition. MS contributed to measure collected samples. KH and YY contributed to the data analysis. KH wrote the manuscript. OI and YK corrected the manuscript, tables, and figures. YK is the research director. All authors read and approved the final manuscript.

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Correspondence to Yuji Kamijo.

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The study protocol was approved by the institutional review board of the ethical committee at Shinshu University Hospital (approval no. 3384) and was conducted in accordance with the principles contained within the Declaration of Helsinki as revised in 2013.

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The authors declare that they have no competing interests.

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Appendix

Appendix

Impact of creatinine excretion on estimation accuracy

Appendix shows scatter plots for CIn and other kidney function estimation models dividing into Cr excretion amount. A; CIn and CCr, low Cr excretion group, B; CIn and CCr, high Cr excretion group, C; CIn and eGFRCr, low Cr excretion group, D; CIn and eGFRCr, high Cr excretion group, E; CIn and eGFRCys, low Cr excretion group, F; CIn and eGFRCys, high Cr excretion group, G; CIn and eGFRCr+Cys, low Cr excretion group, H; CIn and eGFRCr+Cys, high Cr excretion group, I; CIn and eGFR-CKDEPICr, low Cr excretion group, J; CIn and eGFR-CKDEPICr, high Cr excretion group. For reference, auxiliary line which equal to CIn was presented. For reference, auxiliary line which equal to CIn was presented.

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Hashimoto, K., Harada, M., Yamada, Y. et al. Adequacy of decision-making based on each kidney function estimation method for Japanese living kidney donor candidates: a retrospective observational study. Ren Replace Ther 6, 6 (2020). https://doi.org/10.1186/s41100-019-0255-2

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