Abstract
Introduction:
Kidney Allocation System (KAS) was implemented by United Network for Organ Sharing in 2014 to reduce allocation disparities.
Research Questions:
Outcomes of highly sensitized patients (calculated panel reactive antibody (cPRA) ≥ 97%) before and after KAS were compared to low-risk recipients (cPRA <10%) in the post-KAS era were examined. The impact on racial disparities was determined.
Design:
This was a retrospective study of national registry data. Two cohorts of adult candidates waitlisted for deceased donor transplantation during 3-year periods before and after KAS were identified.
Results:
Highly sensitized patients (N = 1238 and 4687) received a deceased donor kidney transplant between January 1, 2011 and December 31, 2013 and between January 1, 2015 and December, 31, 2017. Racial disparity for highly sensitized patients improved, yet remained significant (P < 0.001), with Black patients comprising 40% and 41% of the highly sensitized candidates and 28% and 34% of the recipients pre- and post-KAS. While posttransplant death-censored graft failure for highly sensitized recipients was similar overall, post-KAS was associated with improved graft survival in the first year after transplant (HR 0.56, 95% CI 0.40–0.78). When compared to contemporaneous low-risk recipients, both death-censored and all-cause graft failure were similar for highly sensitized recipients and was associated with increased risk for death-censored graft failure beyond the first year (HR 1.39, 95% CI 1.11–1.73).
Conclusion:
The allocation system led to an increase in transplantation in highly sensitized candidates without compromising outcomes. Although KAS has led to more balanced transplant rates between highly sensitized Black and White patients, racial inequalities persist.
Keywords: quality, performance improvement, systems, health, research, quantitative methods, descriptive comparative, clinical outcomes, education, general, clinical outcomes, rejection outcomes
Introduction
There are significant disparities in access to kidney transplantation in the United States. Some of the disparities are socioeconomic in nature (differences in education, economic background, and family networks),1–3 while others are related to structural factors (dialysis unit education, referral practices, distance from nearest transplant center, donor service area)2,4–6 or biological barriers such as blood type and human leukocyte antigen (HLA) sensitization.7–9 The presence of preformed antibodies to the HLA has been one of the major immunological barriers to transplantation.9 Prior to introduction of the new kidney allocation system (KAS) in December 2014, moderately sensitized patients needed to wait 1.5–2 times as long to receive a deceased donor kidney while patients with panel reactive anti-body (PRA) > 80% had much longer waiting time, and the median time to transplantation for the latter could not be calculated.10 Due to differences in the distribution of HLA types and differences in sensitization risk, HLA sensitization is one of the complex reasons for racial disparities in access to kidney transplantation that includes genetic, biological, social, economic, and system-level factors.1,11
One of the main aims of the 2014 KAS changes was to mitigate the variability in access to kidney transplant for candidates who are harder to match due to biologic reasons, and an increase in transplant rates in patients with high calculated PRA (cPRA) has been well documented since its implementation.12–14 However, posttransplant outcomes for highly sensitized recipients and changes in racial disparities in access to kidney transplantation under KAS over the long-term are as yet unreported.
The aims of the current study were: 1. to compare posttransplant outcomes for highly sensitized recipients (cPRA ≥97%) before and after 2014 KAS changes; 2. to compare the rates of death-censored and all-cause graft failure, and acute rejection of highly sensitized recipients to a control group of contemporaneous low-risk patients (cPRA <10%) post-KAS; and 3. to determine the impact of the policy change on racial disparities in deceased donor kidney transplantation (DDKT) rates.
Methods
Design
This study was approved by the Institutional Review Board. A retrospective analysis of national registry data from the United Network for Organ Sharing (UNOS) Standard Transplant Analysis and Research Files based on the Organ Procurement and Transplantation Network (OPTN) database as of March 20, 2020 was performed.
Setting and Population
To compare posttransplant outcomes for highly sensitized recipients before and after the introduction of the KAS changes in 2014, 2 cohorts of all adult (age ≥18 years) candidates on the waiting list for a kidney transplant in the United States during a 3-year period before KAS (2011–2013) and a 3-year period after KAS (2015–2017) were identified.
Sampling
The 2 cohorts of candidates were further classified based on whether they received a DDKT within their 3-year cohort period, and by their cPRA at the time of the transplant or waitlist removal, or by their most recent waitlist reported cPRA.
Data Collection
Demographic characteristics examined were age, gender, and combined race/ethnicity as reported by transplant centers in the UNOS registry. Clinical characteristics captured were primary diagnosis at listing (diabetes, hypertension, glomerulonephritis, cystic kidney disease, re-transplant, or other/unknown), estimated posttransplant survival (EPTS) score calculated using the OPTN guide and 2017 mapping tables, prior transplant recipient status, preemptive listing status, and time on dialysis if not preemptive. For those who received a kidney transplant, additional variables examined were HLA mismatch, kidney donor profile index (KDPI) calculated using the OPTN guide and 2017 mapping tables, and cold ischemia time (CIT). All variables had less than 1% missing data, and patients with missing values were excluded from the analyses unless otherwise noted in categorization (eg other/unknown primary diagnosis). The subgroups compared in analyses are shown in Figure 1.
Figure 1.
Counts of waitlisted kidney transplant candidates and deceased donor kidney transplant recipients, before and after the 2014 changes to the Kidney Allocation System, and by cPRA. Dashed lines indicate groups compared in the study. KAS, Kidney Allocation System; DD, deceased donor; cPRA, calculated panel reactive antibody.
Procedure
The presence of acute rejection was defined using 4 possible variables originating from recipient follow-up data reported by the transplant centers: acute rejection episodes prior to discharge, graft failure cause codes, and treatment for rejection within 6 months and within 1-year posttransplant. Recipients were followed until an event of either graft failure or death (all-cause graft failure), or until graft failure was censored at death (death-censored graft failure). Other censoring events included the recipient’s last recorded follow-up date as reported by the transplant centers (if no event was documented), and administrative censoring at 4 years posttransplantation or on 3/11/2020, when the World Health Organization declared COVID-19 a pandemic.
Data Analysis
Demographic and clinical characteristics between subgroups of candidates and recipients were compared using chi-squared tests for categorical variables and Wilcoxon rank-sum tests for continuous variables. Rates of reported acute rejection events within 3 years posttransplantation across 3 cPRA groups (≤10%, 11–96%, and ≥97%) for the pre-KAS and post-KAS cohorts were compared using chi-squared tests. Death-censored and all-cause graft failure for highly sensitized recipients (cPRA ≥97%) pre-KAS versus post-KAS, and for highly sensitized recipients versus low-risk recipients (cPRA ≤10%) in the post-KAS era were compared using Kaplan-Meier curves and the log-rank test. Unadjusted and adjusted hazard ratios were calculated using Cox models to control for potential confounding by variables of clinical significance (time on dialysis, kidney donor risk index (KDRI), prior transplant, HLA mismatch, CIT, race, gender, and age). The proportional hazards assumption was tested using Schoenfeld residuals. Non-proportional hazards were addressed by examining the hazards of graft failure from 0–1-year posttransplant separately from the time period beyond 1 year. Analyses were performed using Stata MP 17.0 (StataCorp, College Station, TX). Two-sided alpha of 0.05 was used to determine statistical significance.
Results
Recipient and Donor Characteristics
Adult DDKT recipients with cPRA ≥97% were identified, and those transplanted from January 1, 2011 – December 31, 2013 (pre-KAS; N = 1238) were compared to those transplanted from January 1, 2015 – December 31, 2017 (post-KAS; N = 4687). The characteristics of the study patients are shown in Table 1. There were no significant differences between the 2 groups for gender, EPTS at the time of transplant, the percentage of patients who received a preemptive transplant, duration of dialysis before transplant, and the median KDPI.
Table 1.
Characteristics of Highly Sensitized (cPRA ≥97%) Deceased Donor Kidney Transplant Recipients Before and After Implementation of the 2014 Kidney Allocation System Changes.
| Characteristics | Pre-KAS (N = 1238) | Post-KAS (N = 4687) | P-value |
|---|---|---|---|
|
| |||
| Median [IQR] |
Median [IQR] |
||
| Age at transplant (years) | 48 (39–57) | 49 (40–58) | 0.037 |
| N (%) | N (%) | ||
|
|
|||
| Female gender | 759 (61) | 2962 (63) | 0.222 |
| Cause of ESKD | 360 (29) | 1564 (33) | 0.006 |
| Re-transplant | |||
| Diabetes | 173 (14) | 677 (14) | |
| Hypertension | 177 (14) | 730 (16) | |
| Glomerulonephritis | 253 (20) | 825 (18) | |
| Cystic kidney disease | 82 (7) | 271 (6) | |
| Other/Unknown | 193 (16) | 620 (13) | |
| Prior solid organ transplant | 753 (61) | 2768 (59) | 0.260 |
| Preemptive transplant | 57 (5) | 274 (6) | 0.091 |
| Median [IQR] | Median [IQR] | ||
|
|
|||
| EPTS at transplant* | |||
| Median | 40 [20–67] | 42 [21–69] | 0.162 |
| Top 20 EPTS | 317 (26%) | 1126 (24%) | 0.233 |
| Dialysis duration (years) if not preemptive | 4.6 [2.7–7.7] | 4.5 [2.5–7.5] | 0.261 |
| Donor KDPI* | |||
| Median | 36 [17–58] | 35 [17–56] | 0.539 |
| KDPI >85% | 43 (3%) | 98 (2%) | 0.004 |
| Cold ischemia time (hours)* | 17 [12–23] | 19 [14–24] | <0.001 |
Abbreviations: cPRA, calculated panel reactive antibody; EPTS, estimated post-transplant survival; ESKD, end stage kidney disease; IQR, interquartile range; KAS, Kidney Allocation System (December 2014); KDPI, kidney donor profile index.
14 (0.24%) missing EPTS, 5 (0.08%) missing KDPI, and 19 (0.32%) missing CIT were excluded.
Race and Access to Transplantation
Pre-KAS, White patients represented 38% of highly sensitized (cPRA ≥97%) waitlisted patients and 49% of the highly sensitized DDKT recipients (Table 2). Black patients represented 40% of highly sensitized waitlisted patients but only 28% of the DDKT recipients. Following KAS, this racial difference in DDKT among highly sensitized candidates declined. Post-KAS, White patients represented 34% of the waitlisted patients and 38% of the DDKT recipients, while Black patients represented 41% of the waitlisted patients and 34% of the DDKT recipients. Highly sensitized Hispanic patients represented 17% of the DDKT pre-KAS and 20% post-KAS. While the racial disparity between waitlisted and transplanted highly sensitized patients was attenuated following KAS, it remained statistically significant (P < 0.001). In comparison, the racial differences between waitlisted candidates and transplant recipients were of lower magnitude in patients with cPRA <10% and were less impacted by KAS implementation (Table S1).
Table 2.
Race and Ethnicity of Highly Sensitized (cPRA ≥97%) Waitlisted Kidney Transplant Candidates and Deceased Donor Kidney Transplant Recipients Before and After Implementation of the 2014 Kidney Allocation System Changes.
| Pre-KAS (2011–2013): Candidates and Recipients with cPRA ≥97% | |||
|---|---|---|---|
|
| |||
| All Candidates (N = 19 676) | Recipients (N = 1238) | ||
| Race/Ethnicity | N (%) | N (%) | P-value |
|
| |||
| Black | 7795 (40) | 351 (28) | <0.001 |
| Hispanic | 2919 (15) | 213 (17) | |
| Other* | 1491 (8) | 62 (5) | |
| White | 7471 (38) | 612 (49) | |
|
| |||
| Post-KAS (2015–2017): Candidates and Recipients with cPRA ≥97% | |||
|
| |||
| Race/Ethnicity | All Candidates (N = 20 779) | Recipients (N = 4687) | P-value |
|
| |||
| Black | 8572 (41) | 1574 (34) | |
| Hispanic | 3314 (16) | 928 (20) | |
| Other* | 1816 (9) | 410 (9) | |
| White | 7077 (34) | 1775 (38) | <0.001 |
P-value column compares race/ethnicity distributions of recipients versus non-recipients among candidates in each era. Additional comparison of the race/ethnicity distribution of recipients pre-KAS versus post-KAS was p < 0.001.
Other category includes: Asian (n = 1110 candidates pre-KAS, n = 1370 candidates post-KAS), American Indian/Alaska Native (n = 189 pre-KAS, n = 190 post-KAS), Native Hawaiian/Other Pacific Islander (n = 81 pre-KAS, n = 82 post-KAS) and Multiracial (n = 111 pre-KAS, n = 174 post-KAS).
cPRA, calculated panel reactive antibody; KAS, Kidney Allocation System (December 2014).
HLA Mismatch Between Donors and Recipients
Prior to KAS, the rate of 0-HLA mismatch DDKT was 38% for highly sensitized candidates (data available upon request). While this decreased to 10% following KAS (P < 0.001), the number of 0-HLA mismatch DDKT performed was 474 and 459 in the pre- and post-KAS groups, respectively – a reflection of the large increase in the number of 1- to 6-HLA mismatch DDKT following KAS (763 pre-KAS vs 4227 post-KAS).
Death-Censored Graft Failure by Era
The median time from transplantation to end of follow up was 4.0 and 2.9 years in the pre- and post-KAS groups, respectively. For highly sensitized recipients, 4-year death-censored graft failure was similar in the post-KAS era compared to the pre-KAS era (unadjusted hazard ratio [HR]: 0.85, 95% CI: 0.69–1.04) (Figure 2A). To avoid violating the proportional hazard assumption of the Cox regression analysis, the adjusted analyses were performed in 2 separate periods: prior to 1-year and after 1-year posttransplant. Compared with the pre-KAS era, DDKT after KAS was associated with improved death-censored graft survival in the first year (adjusted HR: 0.56 [0.40–0.78]) while higher KDRI and dialysis vintage were associated with adverse graft outcomes (Table 3). Beyond the first year posttransplant, there was no significant difference in death-censored graft failure for highly sensitized recipients comparing the post-KAS era with the pre-KAS era (adjusted HR: 1.08 [0.81–1.45]). Higher KDRI and Black race were associated with increased graft failure risk beyond the first year.
Figure 2.
Death-censored graft survival after deceased donor kidney transplantation. (A) Among high cPRA recipients before versus after 2014 changes to the kidney allocation system. (B) Comparing recipients in the Post-KAS Era with high versus low cPRA. KAS, Kidney Allocation System; cPRA, calculated panel reactive antibody.
Table 3.
Hazard of 4-year Death-Censored Graft Failure Among Highly Sensitized (cPRA ≥97%) Deceased Donor Kidney Transplant Recipients Before and After Implementation of the 2014 Kidney Allocation System Changes, Adjusted for Recipient and Transplant Characteristics.
| Years After Transplant | Variable | Hazard Ratio | 95% Confidence Interval | P-value |
|---|---|---|---|---|
|
| ||||
| 0–1 | Post-KAS (ref = pre-KAS) | 0.56 | (0.40, 0.78) | 0.001 |
| KDRI | 3.08 | (2.03, 4.67) | <0.001 | |
| Dialysis vintage (per 1 year) | 1.04 | (1.02, 1.07) | 0.002 | |
| Prior transplant | 1.33 | (0.94, 1.89) | 0.106 | |
| HLA mismatch (ref = 0) | ||||
| 1–3 | 1.14 | (0.74, 1.75) | 0.559 | |
| 4–6 | 1.14 | (0.73, 1.79) | 0.568 | |
| Cold ischemia time (per hour) | 1.01 | (0.99, 1.03) | 0.268 | |
| Race/Ethnicity (ref = White) | ||||
| Black | 0.86 | (0.61, 1.21) | 0.385 | |
| Hispanic | 0.73 | (0.47, 1.13) | 0.156 | |
| Other | 0.76 | (0.41, 1.40) | 0.372 | |
| Female gender (ref = male) | 1.26 | (0.90, 1.76) | 0.179 | |
| Age (per 1 year) | 1.00 | (0.99, 1.01) | 0.923 | |
| 1–4 | Post-KAS (ref = pre-KAS) | 1.08 | (0.81, 1.45) | 0.591 |
| KDRI | 3.09 | (2.15, 4.46) | < 0.001 | |
| Dialysis vintage (yr) | 0.98 | (0.95, 1.01) | 0.165 | |
| Prior transplant | 1.16 | (0.87, 1.56) | 0.307 | |
| HLA mismatch (ref = 0) | ||||
| 1–3 | 1.28 | (0.86, 1.90) | 0.222 | |
| 4–6 | 1.45 | (0.97, 2.18) | 0.071 | |
| Cold ischemia time (per hour) | 1.00 | (0.98, 1.01) | 0.888 | |
| Race/Ethnicity (ref = White) | ||||
| Black | 1.46 | (1.11, 1.94) | 0.008 | |
| Hispanic | 0.89 | (0.62, 1.28) | 0.530 | |
| Other | 0.63 | (0.35, 1.16) | 0.141 | |
| Female gender (ref = male) | 1.10 | (0.84, 1.45) | 0.482 | |
| Age (per 1 year) | 0.96 | (0.95, 0.97) | < 0.001 | |
Abbreviations: cPRA, calculated panel reactive antibody; HLA, human leukocyte antigen; KAS, Kidney Allocation System; KDRI, kidney donor risk index; ref, reference group.
Death-Censored Graft Failure by cPRA
Between January 1, 2015 and December 31, 2017, 25 608 waitlisted candidates with cPRA <10% received DDKT compared to 4687 highly sensitized candidates. The median follow-up time from time of transplantation to end of follow-up was 2.8 years for the cPRA <10% group and 2.9 years for highly sensitized recipients. Death-censored graft failure was similar for cPRA <10% and highly sensitized recipients (unadjusted HR: 1.10, 95% CI: [0.98–1.24]) (Figure 2B). As the proportional hazards assumption was violated, the analyses were reperformed separately for prior to 1-year and after 1-year posttransplant. During the first year, higher KDRI, dialysis vintage, prior transplant, higher CIT, and HLA mismatch were associated with worse graft outcomes (Table S2). Highly sensitized status was associated with increased risk for allograft failure only beyond the first year (adjusted HR: 1.39 [1.11–1.73]).
All-Cause Graft Failure
All-cause graft failure was similar for highly sensitized candidates who were transplanted pre-KAS and post-KAS (unadjusted HR: 0.93, 95% CI: [0.80–1.09]) (Figure 3A). In multivariable analysis, increasing age at the time of transplant, prior transplant, higher CIT, higher KDRI, and dialysis vintage were significantly associated with worse outcomes (Table S3). The post-KAS era was associated with better graft outcomes (adjusted HR: 0.71 [0.55–0.92]) in the first year, but no significant difference in all-cause graft failure for years 1–4 posttransplant (adjusted HR: 1.09 [0.88–1.35]). Comparing contemporaneous cohorts in the post-KAS era, highly sensitized patients had similar all-cause graft failure than those with a cPRA <10% on unadjusted analysis (Figure 3B) and when adjusted for age, gender, race, KDRI, dialysis vintage, prior transplant, and degree of HLA mismatch in the first year (adjusted HR: 0.88 [0.73–1.06]) and in years 1–4 posttransplant (adjusted HR: 1.14 [0.98–1.33]).
Figure 3.
All-cause graft failure after deceased donor kidney transplantation. (A) Among high cPRA recipients before versus after 2014 changes to the Kidney Allocation System. (B) Comparing recipients in the Post-KAS Era with high versus low cPRA. KAS, Kidney Allocation System; cPRA, calculated panel reactive antibody.
Acute Rejection Rates
Ideally, pairing deceased donors to recipients based on their acceptable HLA would result in lower risk of rejection. Three-year acute rejection rates for patients with cPRA <10%, 11–96%, and ≥97% before and after KAS were 14%, 14%, 16% and 11%, 13%, 16%, respectively (P = 0.076 and P < 0.001, respectively, across cPRA groups) (data available upon request). Although higher cPRA was associated with more acute rejection in the post-KAS era, this appears to be driven by lower rates of acute rejection among less-sensitized recipients in the post-KAS era rather than an increase in acute rejection rates among highly sensitized recipients.
Discussion
Kidney transplantation is the treatment of choice for most patients with end-stage kidney disease (ESKD) as it significantly reduces mortality and improves the quality of life when compared with dialysis.15–17 Although kidney transplantation from living donors offers greater benefit than DDKT due to decreased waiting period on the transplantation list and longer graft survival, the majority of patients with ESKD are reliant on deceased donation.17
The Kidney Allocation System was implemented by the UNOS in December 2014 with the major goals to improve kidney allocation disparities among different race/ethnicities on the waiting list and to optimize access to DDKT for highly sensitized candidates.7,18 Prior to implementation of KAS, highly sensitized candidates had as much as a fivefold lower rate of DDKT and 21% higher waitlist mortality.12 Since the KAS implementation, several studies have demonstrated the short-term increase in DDKT rate for highly sensitized candidates.12–14 Early analysis after the first 9 months post-KAS showed that the DDKT rate increased especially for young Black and Hispanic candidates and highly sensitized patients.13,19 At the same time, the proportion of recipients with cPRA = 99% and cPRA = 100% increased from 1.3% to 3.6% and 1.0% to 10.3%, respectively. In the absence of a review of longer-term trends, it was unclear, whether this large change represented merely a bolus effect in the immediate post-KAS period. Jackson and colleagues demonstrated in their study that KAS has led to more balanced access to DDKT for highly sensitized candidates 3 years after its implementation.12 While cPRA 99.5–99.9% candidates experienced a significantly improved DDKT rate post-KAS, those with cPRA >99.9% continued to be transplanted at a lower rate than non-highly sensitized candidates, albeit improved. One-year posttransplant patient survival was similar for highly sensitized patients pre- and post-KAS while 1-year death-censored graft survival was higher for cPRA = 98% and cPRA = 99% recipients post KAS compared to pre-KAS.12
In this nationwide study of DDKT rates and outcomes for highly sensitized patients before and after KAS, the change in kidney allocation policy was associated with improved early graft survival in the first year for these patients and similar outcomes beyond the first 12 months – with the donor organ quality continuing to be the primary factor influencing outcomes. Also, post-KAS, highly sensitized patients with cPRA ≥97% had increased risk for death-censored graft failure only beyond the first year when compared to contemporaneous low-risk recipients. One plausible explanation for the latter observation is that by listing unacceptable antigens for deceased kidney donor allocation, highly sensitized candidates are receiving kidneys only from donors against whom they may have very low levels of preformed donor-specific antibodies (DSA). These may allow for the avoidance of severe, early acute antibody-mediated rejection (ABMR), however, may still result in long-term graft failure through the development of chronic active ABMR.20–23 The current analysis suggests that following KAS implementation, transplant centers are performing more HLA mismatched DDKT for highly sensitized candidates compared to the pre-KAS era. This may have also contributed to the observed differences in longer-term outcomes.
Kulkarni and colleagues reported that since KAS, no difference in transplant probability was noted among races/ethnicities for candidates with cPRA <80%.24 However, for highly sensitized candidates with cPRA ≥80% and ≥90%, there was an advantage in transplant probability for White and Hispanic patients over Black individuals, respectively. In this study, the implementation of KAS was associated with an improvement in access to DDKT for highly sensitized Black candidates. While this result is certainly encouraging, there still remains significant racial disparity between waitlisted and transplanted patients with high cPRA.
Limitation of this study include its retrospective nature and use of national registry data, with the potential for data entry error, misclassification and residual confounding. Secondly, the post-KAS cohort in the study has a median of only 3 years of posttransplant follow-up data. Additional follow-up data are needed to confirm longer-term effects of the 2014 KAS changes.
Conclusions
In summary, the implementation of 2014 KAS changes led to higher rates of DDKT in highly sensitized candidates without compromising transplant outcomes. The observation that for highly sensitized recipients, there were no differences in both death-censored graft failure and all-cause graft failure by era as well as in death-censored graft failure when compared to contemporaneous low-risk recipients makes this conclusion even more compelling. The current analysis validates the goal of the 2014 KAS implementation to prioritize highly sensitized patients and suggests that this goal to be preserved in future iterations of the allocation system.
Although racial inequalities in access to kidney transplantation continue to exist, KAS has led to more balanced DDKT rates between Black and White ESKD patients even among the most highly sensitized patients. Additionally, in the recent study by Kadatz and colleagues, patients with at least 6.5 years of dialysis vintage prior to waitlisting were more likely to be Black, reside in a zip code with lower median household income, and have a higher social deprivation index compared with the overall waitlisted population.25,26 While the implementation of KAS was associated with an increase in DDKT and improvement in patient survival, nearly three-quarters of this disadvantaged population were never waitlisted despite the policy change suggesting the potential for improvement in referral and waitlisting practice. Additional policy changes are necessary to further increase equity in kidney transplantation across racial/ethnic, and socioeconomic groups. Allocation policy changes in isolation have limited impact. Multimodal dedicated strategies need to be developed to motivate practice changes and broader collaboration between dialysis providers, transplant programs, and the government.
Supplementary Material
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by Health Resources and Services Administration contract 234-2005-370011C. The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. SM was supported by NIH grants DK114893, DK116066, DK126739, DK130058 and MD014161 and a Nelson Family Faculty Development Award. SAH was supported by NIDDK grant K23DK133729 and a Nelson Family Faculty Development Award. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Footnotes
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Supplemental Material
Supplemental material for this article is available online.
References
- 1.Husain SA, Yu ME, King KL, Adler JT, Schold JD, Mohan S. Disparities in kidney transplant waitlisting among young patients without medical comorbidities. JAMA Intern Med. 2023;183(11): 1238–1246. doi: 10.1001/jamainternmed.2023.5013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Ernst Z, Wilson A, Peña A, Love M, Moore T, Vassar M. Factors associated with health inequities in access to kidney transplantation in the USA: A scoping review. Transplant Rev (Orlando). 2023;37(2):100751. doi: 10.1016/j.trre.2023.100751 [DOI] [PubMed] [Google Scholar]
- 3.Smothers L, Patzer RE, Pastan SO, DuBay D, Harding JL. Gender disparities in kidney transplantation referral vary by age and race: A multiregional cohort study in the Southeast United States. Kidney Int Rep. 2022;7(6):1248–1257. doi: 10.1016/j.ekir.2022.03.027 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.King KL, Husain SA, Schold JD, et al. Major variation across local transplant centers in probability of kidney transplant for wait-listed patients. J Am Soc Nephrol. 2020;31(12):2900–2911. doi: 10.1681/ASN.2020030335 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Patzer RE, Di M, Zhang R, et al. Referral and evaluation for kidney transplantation following implementation of the 2014 National Kidney Allocation System. Am J Kidney Dis. 2022; 80(6):707–717. doi: 10.1053/j.ajkd.2022.01.423 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Watters TK, Glass BD, Mallett AJ. Identifying the barriers to kidney transplantation for patients in rural and remote areas: a scoping review. J Nephrol. 2023. doi: 10.1007/s40620-023-01755-0. Online ahead of print. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Glorioso JM. Kidney allocation policy: Past, present, and future. Adv Chronic Kidney Dis. 2021;28(6):511–516. doi: 10.1053/j.ackd.2022.01.006 [DOI] [PubMed] [Google Scholar]
- 8.Lefaucher C, Louis K, Morris AB, et al. Clinical recommendations for posttransplant assessment of anti-HLA (Human Leukocyte Antigen) donor-specific antibodies: A sensitization in transplantation: Assessment of risk consensus document. Am J Transplant. 2023;23(1):115–132. doi: 10.1016/j.ajt.2022.11.013 [DOI] [PubMed] [Google Scholar]
- 9.Senev A, Lerut E, Van Sandt V, et al. Specificity, strength, and evolution of pretransplant donor-specific HLA antibodies determine outcome after kidney transplantation. Am J Transplant. 2019;19(11):3100–3113. doi: 10.1111/ajt.15414 [DOI] [PubMed] [Google Scholar]
- 10.United States Renal Data System 2010 Annual Data Report, Volume Two, Chapter 7, Page 314.
- 11.Bekbolsynov D, Mierzejewska B, Khuder S, et al. Improving access to HLA-matched kidney transplants for African American patients. Front Immunol. 2022;13:832488. doi: 10.3389/fimmu.2022.832488 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Jackson KR, Covarrubias K, Holscher CM, et al. The national landscape of deceased donor kidney transplantation for the highly sensitized: Transplant rates, waitlist mortality, and posttransplant survival under KAS. Am J Transplant. 2019;19(4): 1129–1138. doi: 10.1111/ajt.15149 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Massie AB, Luo X, Lonze BE, et al. Early changes in kidney distribution under the new allocation system. J Am Soc Nephrol. 2016;27(8):2495–2501. doi: 10.1681/ASN.2015080934 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Parsons RF, Locke JE, Redfield RR 3rd, Roll GR, Levine MH. Kidney transplantation of highly sensitized recipients under the new kidney allocation system: A reflection from five different transplant centers across the United States. Hum Immunol. 2017;78(1):30–36. doi: 10.1016/j.humimm.2016.10.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Goto S, Fujii H, Mieno M, et al. Survival benefit of living donor kidney transplantation in patients on hemodialysis. Clin Exp Nephrol. 2024;28(2):165–174. doi: 10.1007/s10157-023-02417-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Strohmaier S, Wallisch C, Kammer M, et al. Survival benefit of first single-organ deceased donor kidney transplantion compared with long-term dialysis across ages in transplant-eligible patients with kidney failure. JAMA Netw Open. 2022;5(10):e2234971. doi: 10.1001/jamanetworkopen.2022.34971 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hariharan S, Israni AK, Danovitch G. Long-term survival after kidney transplantation. N Engl J Med. 2021;385(8):729–743. doi: 10.1056/NEJMra2014530 [DOI] [PubMed] [Google Scholar]
- 18.Israni AK, Salkowski N, Gustafson S, et al. New national allocation policy for deceased donor kidneys in the United States and possible effect on patient outcomes. J Am Soc Nephrol. 2014;25(8):1842–1848. doi: 10.1681/ASN.2013070784 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Melanson TA, Hockenberry JM, Plantinga L, et al. New Kidney Allocation System associated with increased rates of transplants among Black and Hispanic patients. Health Aff (Millwood). 2017;36(6):1078–1085. doi: 10.1377/hlthaff.2016.1625 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Zhang R Donor-specific antibodies in kidney transplant recipients. Clin J Am Soc Nephrol. 2018;13(1):182–192. doi: 10.2215/CJN.00700117 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Loupy A, Lefaucheur C. Antibody-mediated rejection of solidorgan allografts. N Engl J Med. 2018;379(12):1150–1160. doi: 10.1056/NEJMra1802677 [DOI] [PubMed] [Google Scholar]
- 22.Madill-Thomsen KS, Böhmig GA, Bromberg J, et al. Donor-specific antibody is associated with increased expression of rejection transcripts in renal transplant biopsies classified as no rejection. J Am Soc Nephrol. 2021;32(11):2743–2758. doi: 10.1681/ASN.2021040433 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Senev A, Lerut E, Coemans M, et al. Association of HLA mismatches and histology suggestive of antibody-mediated injury in the absence of donor-specific anti-HLA antibodies. Clin J Am Soc Nephrol. 2022;17(8):1204–1215. doi: 10.2215/CJN.00570122 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Kulkarni S, Ladin K, Haakinson D, Greene E, Li L, Deng Y. Association of racial disparities with access to kidney transplant after the implementation of the new Kidney Allocation System. JAMA Surg. 2019;154(7):618–625. doi: 10.1001/jamasurg.2019.0512 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Kadatz M, Lan JH, Brar S, et al. Transplantation of patients with long dialysis vintage in the current deceased donor Kidney Allocation System (KAS). Am J Kidney Dis. 2022;80(3):319–329.e1. doi: 10.1053/j.ajkd.2022.01.429 [DOI] [PubMed] [Google Scholar]
- 26.Whelan AM, Dinh A, Ku E. Kidney transplantation in the setting of prolonged dialysis vintage: It’s about time. Am J Kidney Dis. 2022;80(3):307–308. doi: 10.1053/j.ajkd.2022.05.001 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.