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Outcomes of Living Kidney Donor Candidate Evaluations in the Living Donor Collective Pilot Registry

Supplemental Digital Content is available in the text.


INTRODUCTION
Although deceased and living kidney donations have increased in the United States, there remains a shortage of kidneys for transplant. 1 There is an ongoing need to understand barriers to living donation, especially in disadvantaged communities. One potential barrier to living donation is uncertainty over the long-term risk to donors, and potential living donors may decline or be turned down by transplant programs out of fear that the donation may cause long-term harm. The Kidney Disease Improving Global Outcomes clinical practice guideline recommends that each transplant program determine an acceptable end-stage kidney disease (ESKD) risk threshold for living donor candidates. 2,3 Unfortunately, there is little evidence available to estimate the long-term risk of ESKD attributable to donation, 4,5 and acceptance criteria may vary across programs.
The Health Resources and Services Administration (HRSA) contracted with the Scientific Registry of Transplant Recipients (SRTR) to conduct a pilot program exploring the utility of establishing a comprehensive registry to examine decision processes and outcomes of living kidney and liver donation. Such a registry could allow programs to compare their rates of acceptance of candidates and their reasons for not accepting candidates with those of other programs. It could also allow donor candidates and intended recipients to compare programs based on characteristics of accepted donors and thereby help them select programs at which they may seek living donor transplant opportunities. In addition, it could allow long-term follow-up of candidates and donors by linking to other registries and using surveys to compare donors with approved donor candidates who did not donate. However, without first determining the feasibility of collecting such data from individual centers, it would be unreasonable to expect the transplant community to be willing to participate in any widespread deployment or national requirement to provide such data. Thus, to support the HRSA request that a detailed pilot investigation be mounted, the SRTR formed the Living Donor Collective. 22 In this report, we describe the results to date of our pilot registry, made up of 10 kidney transplant programs. Our objective is to inform the transplant community of this ongoing effort, which we anticipate will be expanded to register all living donor candidates in the United States. Our ultimate aim is to remove barriers to donation, including uncertainties over short-and long-term donor outcomes.

Source of Data
We used existing and newly collected SRTR data. The SRTR data system includes data on all donors, waitlisted candidates, and transplant recipients in the United States submitted by the members of the Organ Procurement and Transplantation Network (OPTN) and has been described elsewhere. 23 HRSA, US Department of Health and Human Services, provides oversight for the activities of the OPTN and SRTR contractors. Ten living kidney donor transplant programs collected data, as previously described ( Figure 1). 22 Although programs began enrolling candidates at different times, the first program began enrolling in June 2018, and the last program began in February 2019. Three participating programs uploaded batched data electronically, and the rest entered data using a manual-entry web-based system. Candidates were followed through March 12, 2020, a date chosen to align with the declaration of the coronavirus disease 2019 (COVID-19) emergency in the United States on March 13, 2020.

Linking Candidates to Organ Procurement and Transplantation Network Data
To determine which candidates had donated a kidney by the end of our observation period, we linked our data to OPTN data collected for Living Donor Registration (LDR). Hospitals removing a kidney from a living donor for transplant ("recovery hospitals") are required to submit the LDR to the OPTN within 60 d postrecovery. From the LDR, we were able to ascertain whether the donation occurred with the same program as the one performing the evaluation. In each case, we protected the privacy of candidates so that programs could not know whether a candidate they evaluated was also evaluated by and, in some cases, donated at another program.

Statistical Analysis
We examined differences between candidates who were or were not approved for donation. Univariate analysis for these comparisons included chi-square tests for differences in categorical data, Fisher exact test for differences of small sample size categorical data when necessary, t tests for normally distributed continuous variables that were logarithmically transformed when necessary, and the Wilcoxon rank sum test for differences in medians of continuous variables, when necessary. In addition, we performed multiple logistic regression to determine which variables were significantly different between candidates who were approved versus not approved for donation. Specifically, we first examined by univariate logistic regression which variables were associated with being approved for donation at P < 0.15. We then included these variables in a multiple logistic regression model and conducted stepwise model selection using the Akaike information criterion to see which variables predicted approval for donation independent of other variables.

Evaluation Process
As of March 12, 2020, 2107 kidney donor candidates were registered, and 2099 of 2107 (99.6%) had completed registration ( Figure 2). The candidate or program had made a decision regarding donation in 1578 of 2099 (75.2%), whereas decisions were still pending for 521 of 2099 (24.8%). Of those with a decision, 790 of 1578 (50.1%) were approved to donate, whereas 788 of 1578 (49.9%) were not. The median time between candidate registration completion and the decision to donate or not was 89.5 d (IQR, 27-185.75; Figure 3).
Of the candidates approved for donation, 612 of 790 (77.5%) had donated, according to data from the OPTN, as of March 12, 2020. Of the 612 donated kidneys, all but 4 were recovered at the program at which the donor was evaluated. The time between registration completion and donation was 92 d (IQR, 58-148) for the 612 candidates who had donated ( Figure 4).

Differences Between Candidates Accepted or Not Accepted for Donation
Slightly less than half of the candidates were biologically related to the intended recipient, and the proportions biologically related were not different between those accepted or not accepted (Table S2, SDC, http://links.lww.com/TXD/A319).
More women were evaluated, and proportionally more were accepted for donation than men (Table 1). Age was not different for those accepted or not accepted for donation (Table 1); those approved for donation were (mean ± SD) 45.5 ± 13.6 y old, whereas those not approved were 45.9 ± 12.7 y (P = 0.507). Accepted donors were most likely to be married or have a life partner (Table 1), and White candidates were more likely to be accepted as donors than non-White candidates (Table 1). Those accepted as donors most often had more than a high school education and health insurance (Table 2); however, the proportions working for an income were not different. A history of cigarette smoking was less common among accepted donors than nonaccepted ones (Tables 3). Concentrations of total and low-density lipoprotein cholesterol (LDL-C) were similar in accepted versus nonaccepted donors (Table 4). Total cholesterol was 187 ± 35.9 mg/dL in accepted donors, versus 186 ± 38.6 mg/dL in nonaccepted donors (P = 0.366), whereas LDL-C was 109 ± 28.9 mg/dL, versus 108 ± 31.0 mg/dL (P = 0.594), respectively. High-density lipoprotein cholesterol was higher in those accepted to donate than in those not accepted (69.5 ± 16.9 versus 56.3 ± 17.1 mg/ dL) (P < 0.001) ( Table 4). Triglycerides were lower in those accepted (median, 78 mg/dL; IQR, 60-111) than in those not accepted (median, 91 mg/dL; IQR, 64-131) (P < 0.001 by Wilcoxon rank-sum test). A history of hypertension was slightly less common and blood pressure was lower in accepted donors (Table 5). In those accepted versus not accepted, systolic blood pressure was a mean of 119 ± 13.8 mm Hg, versus 124 ± 15.8 mm Hg (P < 0.001), and diastolic blood pressure was 72.9 ± 9.0 mm Hg, versus 75.1 ± 10.2 mm Hg (P < 0.001).
Body mass index was not significantly different in those accepted to be donors compared with those not accepted ( Table 6). Fasting glucose was slightly lower in those accepted Potential donors selected to be evaluated are considered to be candidates. c Candidates are registered when a participating program enters data on the registration form. d Registration is complete when the form is completed and closed to further data entry. e Before a decision is made, the decision form remains open and pending. f SRTR linked candidate registration data to OPTN data to determine when a candidate donated. g SRTR will collect long-term follow-up data, which are not reported as part of this pilot project. LDC, Living Donor Collective; OPTN, Organ Procurement and Transplantation Network; SRTR, Scientific Registry of Transplant Recipients. versus not accepted (94.0 ± 14.2 versus 95.6 ± 15.9 mg/dL; P = 0.030). The estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Epidemiology Consortium equation 24 was not different in those accepted or not accepted to donate (Table 6) (median, 94.0 ± 17.0 versus 95.5 ± 17.3 mL/ min/1.73 m 2 ) (P = 0.089). Urine albumin-to-creatinine ratio, measured in about half of donor candidates, tended to be lower in those accepted than in those not accepted (Table 6) (median, 5.0; range, 3.0-9.0 versus median, 6.0; range, 3.6-10) (P = 0.059 by Wilcoxon rank sum test). There was no difference in history of kidney stones in those accepted or not accepted for donation (Table 7). Uric acid was lower in those accepted than in those not accepted (4.8 ± 1.2 versus 5.1 ± 1.3 mg/dL) (P = 0.001).
Although female sex and having health insurance were both associated with greater acceptance for donation, this was not the case in a multivariate logistic regression analysis adjusting for other candidate characteristics (Table 8) that demonstrated the following independent correlates of acceptance for donation: marital status, education level, race/ethnicity, smoking history, systolic blood pressure, fasting serum triglycerides, and urine albumin-to-creatinine ratio (Table 8).

Reasons for Not Donating
When the decision regarding suitability for donation was made, 788 candidates did not go on to donate, and 674 of 788 (85.5%) of them had completed their evaluation, 43 of 788 (5.5%) had completed the evaluation except for an imaging study, 23 of 788 (2.9%) lacked an imaging study and some other components of the evaluation, 13 of 788 (1.7%) lacked an imaging study and many other components of the evaluation, 4 of 788 (0.5%) were missing information on completeness of the evaluation, and data entry was still in process for 31 of 788 (3.9%).

DISCUSSION
This pilot project was designed to assess the feasibility of a registry for living donor candidates to assess barriers to donation and provide the foundation for determining longterm outcomes for donors and donor candidates who did not donate. Such pilot feasibility work is critical to ensuring that the transplant community understands what a future national registry would entail in terms of participation and data collection activities. We found that the initial 10 transplant programs could successfully register living kidney donor candidates, collect basic demographic and medical data required for donor evaluation, and determine whether the candidates were acceptable to donate or indicate why they were not. We found important differences between candidates accepted for donation and those not accepted. Specifically, those not accepted for donation were more likely to be of Black race, be less educated, be single, have smoked cigarettes, have higher blood pressure, higher triglycerides, or higher urine albuminto-creatinine ratios, reflecting both psychosocial and medical differences and concerns.
Comparing accepted donor candidates with those not accepted may ultimately help define criteria for acceptance, reduce heterogeneity in these criteria between programs, and remove unnecessary barriers to living donation. Certainly, there will always be differences in the threshold of medical risk that programs are willing to accept. However, understanding the medical risks other programs are willing to accept may help programs refine and calibrate their own acceptable risk. In addition, better understanding nonmedical reasons for not donating may identify barriers to donation amenable to mitigation.
It is not surprising that there were differences in medical risk factors between those approved versus not approved for donation. Concerns that surgery and the effects of reduced kidney function could have adverse effects on donors are legitimate reasons for not accepting candidates for donation. 2,3 Theoretically, the risk of ESKD can be estimated, and if that risk is higher than the threshold risk that the program, the candidate, or the potential recipient will accept, donation may be declined. Unfortunately, there is a paucity of data on the long-term risk attributable to kidney donation, and a recent survey of US transplant programs indicated that few programs currently attempt to estimate this risk. 25 These data limitations may lead centers to accept donor candidates at higher risk and exclude donor candidates who are actually at low risk.
We found that Black candidates were half as likely to be approved for donation as non-Black candidates (Table 8).
Others have reported that Black candidates are less likely to be accepted for donation. [10][11][12][13]15 This pilot study was too small to determine the extent to which differences in medical risk explain the lower acceptance of Black candidates and illustrates the need for a larger, more comprehensive registry to understand the role of risk variants such as APOL1 and how they affect the decision to donate. 26  Education level was also strongly associated with candidate acceptance for donation (Table 8). Of course, education may be a surrogate for other socioeconomic factors (eg, disposable income) that could be major barriers to living donation. [29][30][31][32][33] Recent efforts to expand financial assistance to living donor candidates may help facilitate donations that would otherwise  represent a financial hardship. 34 Based on our pilot data, it is clear that collecting more granular information on potentially remediable barriers to donation must be a major focus of ongoing efforts.
Studies of long-term outcomes after living donation have had inherent flaws and produced conflicting results. 4,5,[35][36][37][38] It has been most challenging to find suitable populations to compare outcomes with those of donors, given their verified    health after a rigorous screening and selection process. 39,40 Also problematic is the fact that outcomes that matter most to patients, such as ESKD, are rare-even with long-term follow-up. 39 Because we cannot conduct a randomized controlled trial to determine the effects of living kidney donation on these important outcomes, the best alternative is to conduct a prospective observational study of adequate sample size and follow-up to measure differences in infrequent but critical events between donors and comparable controls. The best controls might be candidates approved for donation but not donating for reasons unrelated to the potential outcomes of interest. We found that the only reason for 13.9% of candidates not donating was attributable to the recipient and not the donor (Table 9), making these candidates potentially suitable controls for matching to donors. This is comparable with 16% of candidates evaluated in the published literature who did not donate because it became unnecessary (Table S1, SDC, http:// links.lww.com/TXD/A319).
Another potential approach is to include all candidates evaluated for donation but adjust the analysis using a stratified propensity score for donor acceptance. The detailed data on risk factors uniformly collected for controls and donors could enable us to assess the risk of important outcomes attributable to donation. Of course, long-term follow-up would still be needed, but including the whole cohort of candidates could greatly enhance statistical power.
Events that matter to candidates, donors, families, transplant programs, and the general public will need to be further refined over time and, ideally, collected for the lifetime of participants. Deaths and their causes can be obtained with some reliability from the Centers for Disease Control and Prevention, the National Center for Health Statistics, and the National Death Index (https://www.cdc.gov/nchs/ndi/index. htm). Dialysis for ESKD can be ascertained for most patients from the United States Renal Data System. Data on kidney transplant can be obtained from the United States Renal Data System and the OPTN, and other long-term follow-up   information can be obtained by directed surveys. Indeed, a model cohort study that assessed the effects of smoking on long-term health outcomes demonstrated the feasibility of (1) defining a large prospective cohort, (2) conducting periodic surveys for follow-up information, (3) linking to registries for vital status, and (4) continuing follow-up for >50 y. 41 A comprehensive registry with long-term follow-up of candidates and donors is needed to understand the long-term health effects of living donation on donors. Events such as ESKD that are important to donors are uncommon, may take years to occur, and cannot be attributed to donation without appropriate controls. Further, the proposed registry of living donor candidates will provide ideal controls to compare with donors, examining outcomes over many years using linkages to other data sources and surveys. Information from this registry, with its long-term follow-up, will help inform future candidates for living donation and their healthcare providers of the risks of donation. In addition, understanding these risks will be an important first step in future efforts to mitigate them.
There are some important limitations to the current report on the Living Donor Collective pilot. First, the sample size of the pilot is too small to examine important subgroups. It will be important, for example, to examine differences according to race/ethnicity for the evaluation process (Figure 2), risk factors (Tables 2-8), or reasons for not donating ( Table 9). The need for larger numbers of candidates is itself a cogent argument to go forward with the registry. Second, the reasons selected for not donating may not reflect true reasons for not donating. The list of reasons for not donating was selected during an initial in-person meeting of representatives from the 10 pilot sites (April 2017) and then refined in a second in-person follow-up meeting of the same group (July 2019) after a collective experience using the first list. A coordinator can always select "other specify," and the list may be modified as needed over time. Finally, there are as yet no long-term follow-up data to report. If we are successful, the registry will provide unique and valuable information on outcomes important to patients over many years.
The Living Donor Collective pilot has demonstrated the feasibility of collecting comprehensive information on candidates for living kidney donation at 10 participating transplant programs and activating processes to continue following them to monitor their ESKD risk. Understandably, medical risk factors differed in candidates approved or not approved for donation. The threshold for approval varied by the center, and more granular analysis will provide pathways to greater standardization of these decisions. However, socioeconomic differences also suggest that there remain potentially surmountable social barriers to living donation. Reasons for not donating can identify candidates who can be compared with donors to ascertain the long-term risks attributable to donation. Further development of this registry is both clinically and scientifically critical to ensure the safety of living donors. To this end, HRSA has contracted with the SRTR to expand the Living Donor Collective over the next 5 y to include all living donor programs in the United States.
To meet this obligation, the SRTR will gradually expand the number of participating programs while continuing to refine data collection tools suitable for as many different programs as possible. Going forward, there will be an ongoing effort to update data collection items and processes based on input from multiple stakeholders that includes short-and long-term follow-up data using electronic tools. In addition, we will coordinate data collection with data already required and collected by the OPTN to minimize unnecessary duplication. With the support and commitment of HRSA and the transplant community, we are optimistic that the registry we now call "The Living Donor Collective" (https://livingdonorcollective.org/) will enhance living donation in the United States for years to come.