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. 2023 Oct 2;183(11):1238–1246. doi: 10.1001/jamainternmed.2023.5013

Disparities in Kidney Transplant Waitlisting Among Young Patients Without Medical Comorbidities

S Ali Husain 1,2,✉, Miko E Yu 1,2, Kristen L King 1,2, Joel T Adler 3, Jesse D Schold 4,5, Sumit Mohan 1,2,6
PMCID: PMC10546295  PMID: 37782509

Key Points

Question

Are there disparities in kidney transplant waitlisting even among patients unlikely to have a medical contraindication to transplantation?

Findings

In this retrospective cohort study of 52 902 patients initiating dialysis in the US who were 40 years or younger and had no major medical comorbidities, only 30% were waitlisted for a kidney transplant within 1 year of dialysis initiation, with lower rates of waitlisting among patients who were Black, Hispanic, or unemployed and those with no predialysis nephrology care.

Meaning

These findings suggest that disparities in kidney transplant waitlisting are not attributable to population differences in comorbidity burden, so transplant policy changes are needed to increase transparency about structural barriers to waitlist access and address them.

This cohort study examines disparities in kidney transplant waitlisting among younger patients without medical comorbidities in the US.

Abstract

Importance

Disparities in kidney transplant referral and waitlisting contribute to disparities in kidney disease outcomes. Whether these differences are rooted in population differences in comorbidity burden is unclear.

Objective

To examine whether disparities in kidney transplant waitlisting were present among a young, relatively healthy cohort of patients unlikely to have medical contraindications to kidney transplant.

Design, Setting, and Participants

This retrospective cohort study used the US Renal Data System Registry to identify patients with end-stage kidney disease who initiated dialysis between January 1, 2005, and December 31, 2019. Patients who were older than 40 years, received a preemptive transplant, were preemptively waitlisted, or had documented medical comorbidities other than hypertension or smoking were excluded, yielding an analytic cohort of 52 902 patients. Data were analyzed between March 1, 2022, and February 1, 2023.

Main Outcome(s) and Measure(s)

Kidney transplant waitlisting after dialysis initiation.

Results

Of 52 902 patients (mean [SD] age, 31 [5] years; 31 132 [59%] male; 3547 [7%] Asian/Pacific Islander, 20 782 [39%] Black/African American, and 28 006 [53%] White) included in the analysis, 15 840 (30%) were waitlisted for a kidney transplant within 1 year of dialysis initiation, 11 122 (21%) were waitlisted between 1 and 5 years after dialysis initiation, and 25 940 (49%) were not waitlisted by 5 years. Patients waitlisted within 1 year of dialysis initiation were more likely to be male, to be White, to be employed full time, and to have had predialysis nephrology care. There were large state-level differences in the proportion of patients waitlisted within 1 year (median, 33%; range, 15%-58%). In competing risk regression, female sex (adjusted subhazard ratio [SHR], 0.92; 95% CI, 0.90-0.94), Hispanic ethnicity (SHR, 0.77; 95% CI, 0.75-0.80), and Black race (SHR, 0.66; 95% CI, 0.64-0.68) were all associated with lower waitlisting after dialysis initiation. Unemployment (SHR, 0.47; 95% CI, 0.45-0.48) and part-time employment (SHR, 0.74; 95% CI, 0.70-0.77) were associated with lower waitlisting compared with full-time employment, and more than 1 year of predialysis nephrology care, compared with none, was associated with greater waitlisting (SHR, 1.51; 95% CI, 1.46-1.56).

Conclusions and Relevance

This retrospective cohort study found that fewer than one-third of patients without major medical comorbidities were waitlisted for a kidney transplant within 1 year of dialysis initiation, with sociodemographic disparities in waitlisting even in this cohort of young, relatively healthy patients unlikely to have a medical contraindication to transplantation. Transplant policy changes are needed to increase transparency and address structural barriers to waitlist access.

Introduction

Despite survival, quality-of-life, and cost benefits associated with kidney transplant compared with dialysis for patients with end-stage kidney disease (ESKD), most patients who initiate dialysis in the US are never even waitlisted for a transplant.1,2,3,4,5,6,7,8 Furthermore, among the few of these patients who are ultimately waitlisted, most spend multiple years undergoing dialysis before transplant even though earlier transplant—ideally before dialysis initiation—is associated with superior quality of life and posttransplant survival.9,10,11 In response to disparities in timely referral and waitlisting for transplantation, a new kidney allocation system (KAS) was implemented in December 2014. Whereas waiting time accumulation previously began on the date of waitlisting, KAS aimed to reduce adverse consequences of late referral by initiating waiting time credit at the date of dialysis initiation rather than at the date the patient was later waitlisted. However, both before and after this change, patients belonging to disadvantaged demographic and economic groups, including patients with minority race, low educational attainment, and low socioeconomic status, have lower rates of transplant referral, waitlisting, transplants overall, transplants before dialysis initiation, and living donor transplants.12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28

Understanding the magnitude of underwaitlisting and waitlisting disparities is challenging due to difficulty determining the denominator of potentially waitlist-eligible patients. Given that a combination of advanced age and significant medical comorbidities may preclude transplantation or minimize its benefit, the cohort of all patients receiving dialysis includes some for whom transplant is not appropriate.29,30,31 Additionally, differences in comorbidity prevalence among groups, such as higher rates of diabetes, cardiovascular disease, and cancer among Black individuals, could have been hypothesized to influence transplant eligibility and confound observed differences in waitlisting rates. We therefore sought to ascertain waitlisting rates and disparities among a cohort of young incident dialysis patients without documented medical comorbidities who should therefore be highly likely to be medically eligible for transplant.

Methods

We performed a retrospective cohort study using registry data from the US Renal Data System (eMethods in Supplement 1).32 This study was approved by the institutional review board at Columbia University Medical Center. Informed consent was not required for this retrospective analysis of deidentified data. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

We identified adults (age ≥18 years) initiating dialysis from January 1, 2005, to December 31, 2019 (n = 1 011 508) (Figure 1; eFigure 1 in Supplement 1). We excluded patients older than 40 years or who were preemptively waitlisted for a transplant (before dialysis initiation) and then excluded patients with any documented comorbidities or limitations other than hypertension or smoking (n = 56 625) (excluded comorbidities included congestive heart failure, atherosclerotic heart disease, other cardiac disease, cerebrovascular disease, peripheral vascular disease, amputation, diabetes, chronic obstructive pulmonary disease, cancer, non-kidney congenital abnormality, alcohol dependence, drug dependence, inability to ambulate or transfer, or institutionalization). Further exclusion of 49 patients receiving maintenance dialysis in an inpatient setting or nursing home and 16 patients with a primary dialysis modality of “other” or with unknown sex yielded a final analytic cohort of 52 902 patients 40 years or younger with no major medical comorbidities who were initiating dialysis and were not already waitlisted at dialysis initiation.

Figure 1. Flowchart of US Renal Data System (USRDS) Records That Were Screened, Included, and Excluded in the Analysis.

Figure 1.

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A total of 52 902 patients who initiated dialysis between 2005 and 2019 and were 40 years or younger without documented medical comorbidities or kidney transplant waitlisting before dialysis initiation were included in the analysis.

We then categorized patients in the cohort into 3 groups based on outcome: (1) waitlisted after dialysis initiation but less than 1 year after dialysis initiation, (2) waitlisted 1 to 5 years after dialysis initiation, or (3) not waitlisted within 5 years of dialysis initiation. Demographic data were analyzed as included in the database (eMethods in Supplement 1). Race was included in this study to identify potential racial disparities in waitlisting, and race was classified according to the US Renal Data System database as American Indian or Alaska Native, Asian or Pacific Islander, Black, Middle Eastern, White, other or multiracial, or unknown. Characteristics of patients by outcome group were compared using χ2 and one-way analysis of variance tests for categorical and continuous variables, respectively. We calculated the proportion of patients waitlisted within 1, 3, and 5 years by state of residence.

Our primary outcome of interest was waitlisting for a kidney transplant after dialysis initiation. To assess the likelihood of the primary outcome in the presence of a competing risk of death, we used a subdistribution modeling approach. We used competing risk regression33 to calculate the cumulative incidence function for the probability of waitlisting, treating death as a competing event. Model variables (age, sex, ethnicity, race, employment status, insurance type, predialysis nephrology care, and allocation policy era) were selected a priori based on prior studies34,35,36,37 of factors associated with disparities in kidney transplants. After performing unadjusted competing risk regression to determine the subhazard of waitlisting for each characteristic, we performed an adjusted analysis that included all variables in the same model.

We performed a sensitivity analysis using unadjusted and adjusted logistic regression to determine the association between patient demographic characteristics and odds of waitlisting within 1 year of dialysis initiation using the same covariates as above. Statistical significance was defined by a 2-sided α < .05. Analyses were performed using Stata/MP software, version 17.0 (StataCorp).

Results

A total 52 902 patients (mean [SD] age, 31 [5] years; 31 132 [59%] male and 21 770 [41%] female; 3547 [7%] Asian/Pacific Islander, 20 782 [39%] Black/African American, and 28 006 [53%] White) who initiated dialysis between 2005 and 2019, were 40 years or younger, and had no documented medical comorbidities or preemptive waitlisting were included in the analysis (eTable 1 in Supplement 1). Of these, 15 840 (30%) were added to the kidney transplant waitlist within 1 year of dialysis initiation, and 11 122 (21%) were waitlisted between 1 and 5 years after dialysis initiation, whereas 25 940 (49%) were not waitlisted by 5 years (Table 1). Significant differences were found in demographic characteristics between groups, including sex, race, and full-time employment (Table 1). Similar disparities were observed in the cumulative incidence of waitlisting by group, with lower cumulative incidence of waitlisting among patients initiating dialysis who were female, were of Black race, or had unemployed or retired employment status (Figure 2; eFigure 1 and eTable 2 in Supplement 1). The absolute differences in cumulative waitlisting at 1 and 5 years after dialysis initiation, respectively, were −2% and −3% for female compared with male patients, −9% and −14% for Black patients compared with White patients, and −20% and −27% for unemployed patients compared with those who were employed full time. There were also large interstate differences in the proportion of patients listed within 1 year (median, 33%; range, 15%-58%) or within 5 years (median, 50%; range, 28%-73%) after dialysis initiation (eFigure 2 in Supplement 1). The proportion of patients waitlisted within 1 year of dialysis initiation ranged from 27% to 33% by year of dialysis start: 27% for patients starting dialysis each year after KAS implementation but 29% to 33% in the years preceding KAS (eFigure 3 in Supplement 1).

Table 1. Characteristics of Study Cohort by Waitlisting Outcomea.

Characteristic Waitlisted <1 y (n = 15 840) Waitlisted 1-5 y (n = 11 122) Never waitlisted (n = 25 940)
Age, mean (SD), y 30 (6) 30 (6) 31 (6)
Sex
Female 6183 (39) 4697 (42) 10 890 (42)
Male 9657 (61) 6425 (58) 15 050 (58)
Ethnicity
Hispanic 3576 (23) 2934 (26) 6763 (26)
Non-Hispanic 12 264 (77) 8188 (74) 19 177 (74)
Race
Asian or Pacific Islander 1493 (9) 825 (7) 1229 (5)
Black or African American 4563 (29) 4605 (41) 11 614 (45)
White 9656 (61) 5564 (50) 12 786 (49)
Other, multiracial, or unknownb 128 (1) 128 (1) 311 (1)
Employment
Unemployed 5437 (34) 5240 (47) 15 294 (59)
Employed full time 5413 (34) 2757 (25) 4101 (16)
Employed part time 1184 (7) 695 (6) 1400 (5)
Retired 760 (5) 698 (6) 2341 (9)
Student 1097 (7) 513 (5) 658 (3)
Other or missingc 1949 (12) 1219 (11) 2146 (8)
Applying for end-stage kidney disease Medicare coveraged 12 676 (80) 9049 (81) 20 048 (77)
Hypertension 12 900 (81) 9217 (83) 20 764 (80)
Current smoker 560 (4) 475 (4) 2032 (8)
Access used on first outpatient dialysis
Arteriovenous fistula 1228 (8) 930 (8) 2198 (8)
Arteriovenous graft 171 (1) 133 (1) 369 (1)
Catheter 11 019 (70) 8320 (75) 20 868 (80)
Other or unknown 3422 (22) 1739 (16) 2505 (10)
Primary dialysis setting
Dialysis center 12 543 (79) 9493 (85) 23 660 (91)
Home 3297 (21) 1629 (15) 2280 (8)
Primary type of dialysis
Hemodialysis 12 597 (80) 9505 (85) 23 716 (91)
Peritoneal dialysis 3243 (20) 1617 (15) 2224 (9)
Predialysis exogenous erythropoietin
No or ≤1 y 15 360 (97) 10 838 (97) 25 520 (98)
>1 y 480 (3) 284 (3) 420 (2)
Predialysis nephrologist care
No 7376 (47) 5838 (52) 15 801 (61)
<6 mo 2070 (13) 1379 (12) 2904 (11)
6-12 mo 2780 (18) 1829 (16) 3499 (13)
>1 y 3614 (23) 2076 (19) 3736 (14)
Predialysis kidney dietitian care
No or ≤1 y 15 456 (98) 10 909 (98) 25 540 (98)
>1 y 384 (2) 213 (2) 400 (2)
Informed about transplant 14 796 (94) 9959 (90) 22 414 (87)
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a

Data are given as number (percentage) of patients unless otherwise indicated. Because of rounding, percentages might not add up to 100 exactly.

b

Responses included in the other, multiracial, or unknown category include American Indian or Alaska Native, other or multiracial, Middle Eastern, or unknown.

c

Responses included in other employment include homemaker, medical leave of absence, or other.

d

See eMethods in Supplement 1 for additional information.

Figure 2. Cumulative Incidence of Kidney Transplant Waitlisting After Dialysis Initiation by Demographic Characteristic Group.

Figure 2.

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Female patients initiating dialysis had a lower cumulative incidence of waitlisting than male patients (A), and patients with Black race had the lowest cumulative incidence of waitlisting among all racial groups (B). Patients with full-time employment status had higher cumulative incidence of waitlisting compared with any other employment status, with unemployed and retired patients having the lowest cumulative incidence of waitlisting (C). Patients with a longer duration of predialysis nephrology care had a higher cumulative incidence of waitlisting (D). The other, multiracial, or unknown race group includes American Indian or Alaska Native, other or multiracial, Middle Eastern, or unknown.

Patients waitlisted within 1 year of dialysis initiation were most likely to have had any predialysis nephrology care, including more than 1 year of predialysis care. Dialysis type and setting also differed between groups: those waitlisted within 1 year of dialysis initiation were least likely to initiate dialysis via catheter or use in-center hemodialysis. Although most patients in each group were reported to have been informed about kidney transplantation, this proportion was highest among those waitlisted within 1 year of dialysis initiation (Table 1).

In unadjusted competing risk regression, older age, female sex, Hispanic ethnicity, Black race, employment statuses other than full-time employment or student, and dialysis initiation after KAS implementation were significantly associated with decreased waitlisting after dialysis initiation, whereas having predialysis nephrology care was associated with increased waitlisting. We next computed an adjusted model, including age at dialysis initiation, sex, ethnicity, race, employment status, ESKD Medicare coverage application, duration of prior nephrology care, and policy era (Table 2). In this adjusted model, higher age (subhazard ratio [SHR], 0.98 per year; 95% CI, 0.97-0.98; P < .001), female sex (SHR, 0.92; 95% CI, 0.90-0.94; P < .001), Hispanic ethnicity (SHR, 0.77; 95% CI, 0.75-0.80; P < .001), Black race (SHR, 0.66; 95% CI, 0.64-0.68; P < .001), and dialysis initiation after KAS (SHR, 0.75; 95% CI, 0.73-0.78; P < .001) were all associated with decreased waitlisting after dialysis initiation (Table 2). Unemployment (SHR, 0.47; 95% CI, 0.45-0.48) and part-time employment (SHR, 0.74; 95% CI, 0.70-0.77) were associated with decreased waitlisting compared with full-time employment, and more than 1 year of predialysis nephrology care was associated with greater waitlisting compared with none (SHR, 1.51; 95% CI, 1.46-1.56) (Table 2). A sensitivity analysis computing logistic regression models with waitlisting within 1 year of dialysis initiation as a binary outcome showed similar results (eTable 3 in Supplement 1).

Table 2. Competing Risk Regression of Association Between Patient Characteristics and Odds of Kidney Transplant Waitlisting Within 1 Year of Dialysis Initiation.

Characteristic Adjusted SHR (95% CI) P value
Age at dialysis 0.98 (0.97-0.98) <.001
Sex
Male 1 [Reference] <.001
Female 0.92 (0.90-0.94)
Ethnicity
Non-Hispanic 1 [Reference] <.001
Hispanic 0.77 (0.75-0.80)
Race
White 1 [Reference]
Black 0.66 (0.64-0.68) <.001
Asian or Pacific Islander 1.20 (1.14-1.25) <.001
Other, multiracial, or unknowna 0.70 (0.62-0.79) <.001
Employment status
Full time 1 [Reference]
Part time 0.74 (0.70-0.77) <.001
Unemployed 0.47 (0.45-0.48) <.001
Retired 0.41 (0.39-0.44) <.001
Student 0.88 (0.83-0.93) <.001
Other or missingb 0.80 (0.77-0.84) <.001
Applying for ESKD Medicare coverage
No 1 [Reference] <.001
Yes 1.17 (1.13-1.20)
Prior nephrology care
No care 1 [Reference]
≤1 y 1.35 (1.31-1.39) <.001
>1 y 1.51 (1.46-1.56) <.001
Policy era
Before KAS 1 [Reference] <.001
After KAS 0.75 (0.73-0.78)
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Abbreviations: ESKD, end-stage kidney disease; KAS, kidney allocation system; SHR, subhazard ratio.

a

Responses included in the other, multiracial, or unknown category include American Indian or Alaska Native, other or multiracial, Middle Eastern, or unknown.

b

Responses included in other employment include homemaker, medical leave of absence, or other.

Discussion

In this retrospective cohort study analyzing US ESKD registry data, we found that even among young patients initiating dialysis who had no major reported comorbidities, only 30% were waitlisted for a kidney transplant within 1 year of dialysis initiation, and only 51% were waitlisted within 5 years. We found disparities in waitlisting, with female sex, Black race, Hispanic ethnicity, and unemployment associated with significantly lower rates of waitlisting after dialysis initiation. Furthermore, there was a significant association between a long duration of predialysis nephrology care and a higher rate of waitlisting. Given that most patients in this cohort would be expected to be medically suitable transplant candidates because of their young age and health status, these findings indicate that the opportunity to receive a kidney transplant is overtly or implicitly denied to many eligible transplant candidates, especially those belonging to disadvantaged groups, likely reflective of structural racism in access to transplants.

Despite more than $51 billion in ESKD-related expenditures by Medicare in 2019, patients receiving dialysis have survival rates inferior to patients with most cancers.38,39 However, transplants are associated with markedly better survival and quality of life compared with maintenance dialysis.1,2,3,4,5,6,7 For example, in a 30-year-old man without hypertension, diabetes, or cardiovascular disease who has recently initiated dialysis, transplant reduces the estimated 3-year mortality risk from 20% to 2%.40 These patient benefits align with payer incentives to increase transplant rates, which is a cost-effective treatment.8 Despite these benefits, half of our cohort of young patients receiving incident dialysis—likely the healthiest individuals receiving dialysis with the largest expected benefit from transplant—were not waitlisted for a transplant within 5 years of dialysis initiation.

Understanding why transplant is underused even in this highly selected cohort is critical to improving ESKD care outcomes and cost. Consistent with earlier analyses,41,42 we found that patients without prior nephrology care were less likely to be waitlisted. This finding is troubling given prior data showing that fewer than one-third of patients receive at least 1 year of predialysis nephrology care, a proportion that is lower among Black, Hispanic, and Asian patients.43 The absence of prior nephrology care precludes predialysis counseling about transplant and preemptive waitlisting and may have an adverse impact on education efforts at dialysis initiation. Structural racism manifesting as disparate access to predialysis care is compounded by disparities in quality of transplant counseling because patients with chronic kidney disease who are female, are Black, or have lower levels of income and education have more thorough discussions about dialysis than about transplants.44,45

The complex process of getting onto the waitlist has many steps, and single-center analyses have identified disparities in attrition and rate of progression between each of these steps.21,34,46,47 However, our ability to assess which stages of this process act as the largest barriers to waitlisting or are responsible for waitlist disparities is limited by the absence of this information at the national level.47 There is no mandate for transplant centers to report which patients have been referred to them for transplant evaluation, which candidates do not complete a transplant workup, or which patients are deemed unsuitable for waitlisting and the reasons for these denials. Including this information in national registries is the requisite first step to identifying and addressing structural barriers to transplant access as well as identifying transplant centers that underperform at adding patients to the waitlist.48 Public reporting of this center-level data on the steps to the waitlist will allow patients to identify and seek transplant evaluations at centers that will afford them the highest likelihood of being waitlisted— especially considering new waitlist mortality-related regulatory measures, which may unintentionally incentivize greater waitlisting selectivity. Additionally, requiring centers to report why patients referred for transplant evaluation were denied waitlisting is necessary to understand the degree to which nonmedical contraindications to transplant—including subjective assessments of risk of posttransplant nonadherence or inadequate social support—are applied unevenly to patients with lower socioeconomic status and/or minority race.49 For example, prior investigations50,51,52 have shown that factors such as a history of substance use are more likely to cause Black kidney transplant candidates to be denied waitlisting compared with White candidates. The disparate application of these subjective criteria to the detriment of the candidacy of racially minoritized patients is an example of structural racism and is consistent with data from a broad range of health care scenarios demonstrating that implicit practitioner bias has detrimental impacts on the management and outcomes of minoritized patients.53,54,55,56,57,58,59,60

Similarly, although dialysis centers report whether patients have been informed about transplantation, the intensity of this counseling is not standardized. Racial and socioeconomic disparities in transplant counseling have been well described and are associated with decreased access to transplant for Black and Hispanic patients receiving dialysis despite their lower rates of medical ineligibility for transplant.27,61,62,63,64,65 Recent proposals to add referral66 or waitlisting48 metrics for dialysis centers have been met with resistance because transplant waitlisting is outside the locus of control of dialysis centers. However, because dialysis centers are responsible for transplant referral, such accountability can incentivize them to refer patients for transplant evaluation and use their positions as referral streams to apply market pressure to transplant centers to expand and expedite waitlist access. The latter mechanism is especially powerful given increasing consolidation in the US dialysis market,67,68 because avoiding loss of transplant evaluation referrals from dialysis organizations in a consolidated market would be a strong incentive for transplant centers to optimize evaluation and waitlisting processes.

These findings also support the need to consider overcoming structural barriers with novel methods of expediting equitable transplant access for patients receiving dialysis, including universal referral and/or waitlisting with opt-out delisting.69 Updated payment models may also play a role in achieving expanded and equitable transplant access.70 These efforts can augment the effects of KAS policies in reducing the deleterious impact of late transplant referral,13 because we also found that patients initiating dialysis after the implementation of KAS had a lower rate of waitlisting compared with those initiating dialysis before KAS.

Limitations

Limitations of our study include the possibility of residual confounding, such as the presence of uncaptured characteristics that differ between groups and influence waitlisting rates. Additionally, it is possible that our data set does not capture some patient comorbidities if they were not accurately recorded during the completion of the ESKD Medical Evidence Report. However, given the young age of our cohort, we anticipate that few included patients would have comorbidities at the time of dialysis initiation that were severe enough to prevent transplant waitlisting yet were not recognized when completing the ESKD Medical Evidence Report. Given that no national registry captures patients with advanced chronic kidney disease who are eligible for preemptive waitlisting before dialysis initiation, our analysis likely also underestimates the degree of disparities in waitlist access. Waitlisted individuals with estimated glomerular filtration rates of 20 mL/min/1.73 m2 or less can accumulate predialysis waiting time, but these preemptive listings disproportionately include patients of White race, male sex, and higher socioeconomic status. Finally, our study cannot analyze the impact of very recent payment reforms aimed at improving kidney transplant referral rates.

Conclusions

In this retrospective cohort study using US ESKD registry data, we found that approximately half of young patients initiating dialysis who had no major medical comorbidities were not waitlisted for a kidney transplant within 5 years of dialysis initiation and that there were disparities in waitlisting rates to the detriment of female, Black, and unemployed patients. These findings in a population in which most patients should be medically suitable for transplant suggest that disparities in transplant waitlisting are not attributable to population differences in comorbidity burden but instead are likely reflective of structural racism in access to transplantation and that dialysis centers and transplant centers must be scrutinized on referral and waitlisting rates to ensure timely and equitable access to kidney transplantation.

Supplement 1.

eMethods. Supplemental Methods

eFigure 1. Cumulative Incidence of Waitlisting After Dialysis Initiation for All Patients in the Analytic Cohort

eFigure 2. Observed Proportions of Patients, by State of Residence, Added to the Kidney Transplant Waiting List Within 1, 3 and 5 Years Following Dialysis Initiation and Map of Proportions of Patients, by State of Residence, Added to the Kidney Transplant Waiting List Within 5 Years Following Dialysis Initiation

eFigure 3. Number of Included Patients and Observed Proportion of Waitlisting Within 1 Year of Dialysis Initiation by Year of Study Cohort

eTable 1. Characteristics of All Incident Dialysis Patients During the Study Period by Waitlisting Outcome

eTable 2. Unadjusted Cumulative Incidence of Kidney Transplant Waitlisting After Dialysis Initiation Based on Demographic Characteristics

eTable 3. Logistic Regression of Association Between Patient Characteristics and Odds of Kidney Transplant Waitlisting Within 1 Year of Dialysis Initiation

eReferences

Click here for additional data file. (461.9KB, pdf)
Supplement 2.

Data Sharing Statement

Click here for additional data file. (14.3KB, pdf)

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eMethods. Supplemental Methods

eFigure 1. Cumulative Incidence of Waitlisting After Dialysis Initiation for All Patients in the Analytic Cohort

eFigure 2. Observed Proportions of Patients, by State of Residence, Added to the Kidney Transplant Waiting List Within 1, 3 and 5 Years Following Dialysis Initiation and Map of Proportions of Patients, by State of Residence, Added to the Kidney Transplant Waiting List Within 5 Years Following Dialysis Initiation

eFigure 3. Number of Included Patients and Observed Proportion of Waitlisting Within 1 Year of Dialysis Initiation by Year of Study Cohort

eTable 1. Characteristics of All Incident Dialysis Patients During the Study Period by Waitlisting Outcome

eTable 2. Unadjusted Cumulative Incidence of Kidney Transplant Waitlisting After Dialysis Initiation Based on Demographic Characteristics

eTable 3. Logistic Regression of Association Between Patient Characteristics and Odds of Kidney Transplant Waitlisting Within 1 Year of Dialysis Initiation

eReferences

Click here for additional data file. (461.9KB, pdf)
Supplement 2.

Data Sharing Statement

Click here for additional data file. (14.3KB, pdf)

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