Beyond Graft Survivl: A National Cohort Study Quantifying the Impact of Increasing Kidney Donor Profile Index on Recipient Outcomes 1 Year Post-transplantation.

Background: The reporting of a locally validated kidney donor profile index (KDPI) began in Australia in 2016. Across diverse populations, KDPI has demonstrated utility in predicting allograft survival and function. A metric that incorporates both elements may provide a more comprehensive picture of suboptimal recipient outcomes. Methods: A retrospective cohort study of adult kidney transplant recipients in Australia (January 2009 to December 2014) was conducted. Conventional recipient outcomes and a composite measure of suboptimal outcome (1-y allograft failure or estimated glomerular filtration rate [eGFR] <30 mL/min) were evaluated across KDPI intervals (KDPI quintiles and 5-point increments in the KDPI 81-100 cohort). The impact of increasing KDPI on allograft function (1-y eGFR) and a suboptimal outcome was explored using multivariable regression models, adjusting for potential confounding factors. Results: In 2923 donor kidneys eligible for analysis, median KDPI was 54 (interquartile range [IQR], 31-77), and Kidney Donor Risk Index was 1.39 (IQR, 1.03-1.67). The median 1-y eGFR was 52.74 mL/min (IQR, 40.79-66.41 mL/min). Compared with the first quintile reference group, progressive reductions in eGFR were observed with increasing KDPI and were maximal in the fifth quintile (adjusted ß-coefficient: -27.43 mL/min; 95% confidence interval, -29.44 to -25.42; P < 0.001). A suboptimal outcome was observed in 359 recipients (12.3%). The adjusted odds for this outcome increased across quintiles from a baseline of odds ratio of 1.00 (first quintile) to odds ratio of 11.68 (95% confidence interval, 6.33-21.54, P < 0.001) in the fifth quintile cohort. Conclusions: Increases in donor KDPI were associated with higher probabilities of a suboptimal outcome and poorer baseline allograft function, particularly in the KDPI > 80 cohort. These findings may inform pretransplant discussions with potential recipients of high-KDPI allografts.

Healthcare professional and community preferences in deceased donor kidney allocation: A best-worst scaling survey.

Deceased donor kidneys are a scarce community resource; therefore, the principles underpinning organ allocation should reflect societal values. This study aimed to elicit community and healthcare professional preferences for principles guiding the allocation of kidneys from deceased donors and compare how these differed across the populations. A best-worst scaling survey including 29 principles in a balanced incomplete block design was conducted among a representative sample of the general community (n = 1237) and healthcare professionals working in transplantation (n = 206). Sequential best-worst multinomial logistic regression was used to derive scaled preference scores (PS) (range 0-100). Thematic analysis of free text responses was performed. Five of the six most valued principles among members of the community related to equity, including priority for the longest waiting (PS 100), difficult to transplant (PS 94.5) and sickest (PS 93.9), and equitable access for men and women (PS 94.0), whereas the top four principles for healthcare professional focused on maximizing utility (PS 89.9-100). Latent class analysis identified unmeasured class membership among community members. There are discordant views between community members and healthcare professionals. These should be considered in the design, evaluation, and implementation of deceased donor kidney allocation protocols.

Development and validation of a risk index to predict kidney graft survival: the kidney transplant risk index.

BACKGROUND: Kidney graft failure risk prediction models assist evidence-based medical decision-making in clinical practice. Our objective was to develop and validate statistical and machine learning predictive models to predict death-censored graft failure following deceased donor kidney transplant, using time-to-event (survival) data in a large national dataset from Australia. METHODS: Data included donor and recipient characteristics (n = 98) of 7,365 deceased donor transplants from January 1st, 2007 to December 31st, 2017 conducted in Australia. Seven variable selection methods were used to identify the most important independent variables included in the model. Predictive models were developed using: survival tree, random survival forest, survival support vector machine and Cox proportional regression. The models were trained using 70% of the data and validated using the rest of the data (30%). The model with best discriminatory power, assessed using concordance index (C-index) was chosen as the best model. RESULTS: Two models, developed using cox regression and random survival forest, had the highest C-index (0.67) in discriminating death-censored graft failure. The best fitting Cox model used seven independent variables and showed moderate level of prediction accuracy (calibration). CONCLUSION: This index displays sufficient robustness to be used in pre-transplant decision making and may perform better than currently available tools.

Paediatric deceased donor kidney transplant in Australia: A 30-year review-What have paediatric bonuses achieved and where to from here?

BACKGROUND: In this 30-year national review, we describe trends in DD transplantation for paediatric recipients, assess the impact of paediatric allocation bonuses and identify outstanding areas of need for this population. METHODS: A retrospective review of all DD kidney only transplants to paediatric recipients (<18 years old) in Australia between 1989 and 2018 was conducted using deidentified extracts from the ANZDATA. RESULTS: Of the 1011 kidney only transplants performed in paediatric recipients during the study period, 426 (42%) were from deceased donors. Paediatric candidates on the DD waiting list had consistently higher rates of transplantation and shorter time from dialysis initiation to transplantation compared with adult candidates (median 372 vs 832 days in 2018, for example). Donor characteristics remained more favourable for paediatric recipients, despite a decline in the overall quality of the donor pool. The mean number of HLA antigen mismatches for paediatric recipients of DD transplants increased each decade (2.86 [1989-1998], 3.85 [1999-2008], 4.01 [2009-2018]). Both patient and graft survival have improved for paediatric DD transplant recipients in the most recent era (5-year graft and patient survival 85% vs 65% and 99% vs 94%, respectively, for 2009-2018 vs 1999-2008). CONCLUSIONS: The current DD kidney allocation system in Australia provides rapid access to high-quality organs for paediatric recipients, and early graft loss has decreased significantly in recent years; however, additional targeted interventions to address HLA matching may improve long-term outcomes in this population.

The Introduction of cPRA and Its Impact on Access to Deceased Donor Kidney Transplantation for Highly Sensitized Patients in Australia.

BACKGROUND: In March 2016, Australia's deceased donor kidney allocation program introduced calculated panel reactive antibody (cPRA) based on antibody exclusions using multiplex assays to define sensitization for waitlisted candidates. We aimed to assess the impact of this change and review access to transplantation for highly sensitized patients under the current allocation rules. METHODS: Registry data were used to reconstruct changes in panel reactive antibody (PRA)/cPRA for all patients active on the waiting list between 2013 and 2018. A multilevel, mixed-effects negative binomial regression model was used to determine the association between sensitization and transplantation rate in the cPRA era. RESULTS: Following the introduction of cPRA, there was an increase in the percentage of the waiting list classified as highly sensitized (PRA/cPRA ≥80%) from 7.2% to 27.8% and very highly sensitized (PRA/cPRA ≥99%) from 2.7% to 15.3%. Any degree of sensitization was associated with a decreased rate of transplantation with a marked reduction for those with cPRA 95%-98% (adjusted incidence rate ratio, 0.36 [95% confidence interval, 0.28-0.47], P < 0.001) and cPRA ≥99% (adjusted incidence rate ratio, 0.09 [95% confidence interval, 0.07-0.12], P < 0.001). CONCLUSIONS: The proportion of the waiting list classified as highly sensitized increased substantially following the introduction of cPRA, and despite current prioritization, very highly sensitized patients have markedly reduced access to deceased donor transplantation.

Incidence and predictors of vascular events following end-stage kidney disease in childhood.

AIM: Cardiovascular death is a leading cause of mortality in paediatric end-stage kidney disease (ESKD). There is however little known about the clinically relevant vascular disease in this population. We aimed to describe the incidence of new onset vascular disease and vascular death in Australian children receiving renal replacement therapy (RRT). We also aimed to identify demographic or childhood risk factors for these endpoints, and whether vascular disease predicts mortality. METHODS: Data on Australian patients who commenced RRT at <18 years of age from 1991 to 2017 were extracted from the Australian and New Zealand Dialysis and Transplant Registry (ANZDATA). Multivariable competing risks regression was used to identify factors associated with vascular events. RESULTS: A cohort of 1268 patients were followed up for a median of 10.31 years. Vascular disease was reported in 5.4%, and vascular death in 4.1%. The cumulative incidence of any vascular event, that is, disease or death, at 10 and 20 years was 5.5% and 12.8%, respectively. Childhood vascular events were associated with non-Caucasian, non-Indigenous ethnicity, and for the 804 patients followed up after 18 years of age, vascular events were associated with lack of childhood transplantation, longer childhood dialysis duration and Indigenous ethnicity. Vascular disease was only reported for 25.49% of patients who had a vascular death, and although a significant risk factor for mortality, it had limited ability to predict mortality. CONCLUSION: Cumulative incidence of vascular events is significant after commencing RRT during childhood and is associated with ethnicity, longer childhood dialysis duration and lack of childhood transplantation.

Multicenter registry analysis comparing survival on home hemodialysis and kidney transplant recipients in Australia and New Zealand.

BACKGROUND: In the era of organ shortage, home hemodialysis (HHD) has been identified as the possible preferential bridge to kidney transplantation. Data are conflicting regarding the comparability of HHD and transplantation outcomes. This study aimed to compare patient and treatment survival between HHD patients and kidney transplant recipients. METHODS: The Australia and New Zealand Dialysis and Transplant Registry was used to include incident HHD patients on Day 90 after initiation of kidney replacement therapy and first kidney-only transplant recipients in Australia and New Zealand from 1997 to 2017. Survival times were analyzed using the Kaplan-Meier product-limit method comparing HHD patients with subtypes of kidney transplant recipients using the log-rank test. Adjusted analyses were performed with multivariable Cox proportional hazards regression models for time to all-cause mortality. Time-to-treatment failure or death was assessed as a composite secondary outcome. RESULTS: The study compared 1411 HHD patients with 4960 living donor (LD) recipients, 6019 standard criteria donor (SCD) recipients and 2427 expanded criteria donor (ECD) recipients. While LD and SCD recipients had reduced risks of mortality compared with HHD patients [LD adjusted hazard ratio (HR) = 0.57, 95% confidence interval (CI) 0.46-0.71; SCD HR = 0.65 95% CI 0.52-0.79], the risk of mortality was comparable between ECD recipients and HHD patients (HR = 0.90, 95% CI 0.73-1.12). LD, SCD and ECD kidney recipients each experienced superior time-to-treatment failure or death compared with HHD patients. CONCLUSIONS: This large registry study showed that kidney transplant offers a survival benefit compared with HHD but that this advantage is not significant for ECD recipients.

Donor Kidney Quality and Transplant Outcome: An Economic Evaluation of Contemporary Practice.

OBJECTIVES: The study had two main aims. First, we assessed the cost-effectiveness of transplanting deceased donor kidneys of differing quality levels based on the Kidney Donor Profile Index (KDPI). Second, we assessed the cost-effectiveness of remaining on the waiting list until a high-quality kidney becomes available compared to transplanting a lower-quality kidney. METHODS: A decision analytic model to estimate cost-effectiveness was developed using a Markov process. Separate models were developed for 4 separate KDPI bands, with higher values indicating lower quality. Models were simulated in 1-year cycles for a 20-year time horizon, with transitions through distinct health states relevant to the kidney recipient from the healthcare payer's perspective. Weibull regression was used to calculate the time-dependent transition probabilities in the base analysis. The impact uncertainty arising in model parameters was included by probabilistic sensitivity analysis using the Monte Carlo simulation method. Willingness to pay was considered as Australian $28 000. RESULTS: Transplanting a kidney of any quality is cost-effective compared to remaining on a waitlist. Transplanting a lower KDPI kidney is cost-effective compared to a higher KDPI kidney. Transplanting lower KDPI kidneys to younger patients and higher KDPI kidneys to older patients is also cost-effective. Depending on dialysis in hopes of receiving a lower KDPI kidney is not a cost-effective strategy for any age group. CONCLUSION: Efforts should be made by the health systems to reduce the discard rates of low-quality kidneys with the view of increasing the transplant rates.

Deceased donor kidney allocation: an economic evaluation of contemporary longevity matching practices.

BACKGROUND: Matching survival of a donor kidney with that of the recipient (longevity matching), is used in some kidney allocation systems to maximize graft-life years. It is not part of the allocation algorithm for Australia. Given the growing evidence of survival benefit due to longevity matching based allocation algorithms, development of a similar kidney allocation system for Australia is currently underway. The aim of this research is to estimate the impact that changes to costs and health outcomes arising from 'longevity matching' on the Australian healthcare system. METHODS: A decision analytic model to estimate cost-effectiveness was developed using a Markov process. Four plausible competing allocation options were compared to the current kidney allocation practice. Models were simulated in one-year cycles for a 20-year time horizon, with transitions through distinct health states relevant to the kidney recipient. Willingness to pay was considered as AUD 28000. RESULTS: Base case analysis indicated that allocating the worst 20% of Kidney Donor Risk Index (KDRI) donor kidneys to the worst 20% of estimated post-transplant survival (EPTS) recipients (option 2) and allocating the oldest 25% of donor kidneys to the oldest 25% of recipients are both cost saving and more effective compared to the current Australian allocation practice. Option 2, returned the lowest costs, greatest health benefits and largest gain to net monetary benefits (NMB). Allocating the best 20% of KDRI donor kidneys to the best 20% of EPTS recipients had the lowest expected incremental NMB. CONCLUSION: Of the four longevity-based kidney allocation practices considered, transplanting the lowest quality kidneys to the worst kidney recipients (option 2), was estimated to return the best value for money for the Australian health system.

Human leukocyte antigen eplet mismatches and long-term clinical outcomes in pediatric renal transplantation: A pragmatic, registry-based study.

BACKGROUND: HLA epitope-based matching offers the potential to improve immunological risk prediction and management in children receiving renal allografts; however, studies demonstrating the association between systems for defining epitope mismatches and clinical end-points are lacking in this population. METHODS: We conducted a pragmatic, retrospective, registry-based study of pediatric recipients of primary renal allografts in Victoria, Australia between 1990 and 2014 to determine the association between HLA EpMM and clinical outcomes including graft failure, re-transplantation and dnDSA formation. RESULTS: A total of 196 patients were included in the analysis with a median age of 11 years. Median follow-up period was 15 years during which time 108 (55%) primary grafts failed and 72 patients were re-transplanted. HLA class I but not class II EpMM was a significant predictor of graft failure on univariate analysis but not in adjusted models. EpMM was associated with reduced likelihood of re-transplantation in univariate but not adjusted analysis. Within the limitations of the study, class-specific EpMM was a strong predictor of dnDSA formation. Associations were stronger when considering only the subset of antibody-verified EpMM. CONCLUSION: Associations between HLA EpMM and clinical outcomes in pediatric renal allograft recipients seen on univariate analysis were attenuated following adjustment for confounders. These findings are inconclusive but suggest that HLA EpMM may provide one tool for assessing long-term risk in this population while highlighting the need for further clinical studies.

Effect of patient- and center-level characteristics on uptake of home dialysis in Australia and New Zealand: a multicenter registry analysis.

BACKGROUND: Home-based dialysis therapies, home hemodialysis (HHD) and peritoneal dialysis (PD) are underutilized in many countries and significant variation in the uptake of home dialysis exists across dialysis centers. This study aimed to evaluate the patient- and center-level characteristics associated with uptake of home dialysis. METHODS: The Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry was used to include incident dialysis patients in Australia and New Zealand from 1997 to 2017. Uptake of home dialysis was defined as any HHD or PD treatment reported to ANZDATA within 6 months of dialysis initiation. Characteristics associated with home dialysis uptake were evaluated using mixed effects logistic regression models with patient- and center-level covariates, era as a fixed effect and dialysis center as a random effect. RESULTS: Overall, 54 773 patients were included. Uptake of home-based dialysis was reported in 24 399 (45%) patients but varied between 0 and 87% across the 76 centers. Patient-level factors associated with lower uptake included male sex, ethnicity (particularly indigenous peoples), older age, presence of comorbidities, late referral to a nephrology service, remote residence and obesity. Center-level predictors of lower uptake included small center size, smaller proportion of patients with permanent access at dialysis initiation and lower weekly facility hemodialysis hours. The variation in odds of home dialysis uptake across centers increased by 3% after adjusting for the era and patient-level characteristics but decreased by 24% after adjusting for center-level characteristics. CONCLUSION: Center-specific factors are associated with the variation in uptake of home dialysis across centers in Australia and New Zealand.

Insights into the labeling effect of Kidney Donor Performance Index reporting: The Australian experience.

In 2016, Australia began reporting the Kidney Donor Performance Index (KDPI) with all deceased donor kidney transplant offers despite this not being used in organ allocation rules, offering a unique opportunity to explore the "labeling effect" of KDPI reporting. We reviewed all kidneys retrieved for transplant in Australia from 2015 to 2018 and analyzed the association of KDPI reporting with organ nonutilization, number of offer declines, and donor/recipient age and longevity matching. Analyses were stratified by organ failure risk: higher risk (KDPI > 80%), standard risk (KDPI 20% to 79%), and lower risk (KDPI 0% to 20%). There was no significant difference in organ nonutilization post KDPI reporting either overall or for higher-risk kidneys. KDPI reporting was associated with an increase in offer declines for both higher-risk (incidence risk ratio 1.45, P = .007) and standard-risk (incidence risk ratio 1.22, P = .021) kidneys but not for lower-risk organs. There was a significant increase in recipient age and expected posttransplant survival score for higher-risk kidneys but no differences among other groups. We conclude that although KDPI reporting in Australia has been associated with an increased number of offer declines for higher-risk kidneys, this has not resulted in increased nonutilization and may have contributed to more appropriate use of these organs.

Examining the Increased Rates of Deceased Donor Kidney Nonutilization in Australia: What Has Changed?

BACKGROUND: From 2013, Australia has experienced a sustained increase in the proportion of deceased donor kidneys that are retrieved but not utilized for transplantation. We aimed to determine whether this could be explained by changes in donor characteristics over time. METHODS: Registry data were used to examine predictors of kidney nonutilization over the period 2005-2017. Multilevel mixed effect logistic regression modeling and propensity score analysis were used to determine whether era of donation (2013-2017 versus 2005-2012) was an independent predictor of organ nonutilization after controlling for donor characteristics. RESULTS: A total of 7810 kidneys were retrieved for the purpose of transplantation with 334 (4.3%) not utilized. The nonutilization rate was 5.8% in 2013-2017 compared to 2.7% in 2005-2012. Despite adjustment for donor characteristics, donation in the more recent era remained a significant predictor of kidney nonutilization (adjusted odds ratio, 1.98; 95% confidence interval, 1.54-2.54; P < 0.001). This finding was confirmed in the propensity score analysis. CONCLUSIONS: Kidneys retrieved in Australia since 2013 were more likely not to be utilized for transplantation even after adjusting for changes in donor characteristics. The abrupt increase may be explained by increased clinical risk aversion, changes in unmeasured donor factors or logistical issues. Although nonutilization rates in Australia remain low by international standards, further clinical auditing of the reasons for offer decline may help to optimize resource utilization and maximize transplant opportunities.

Infection-Related Mortality in Recipients of a Kidney Transplant in Australia and New Zealand.

BACKGROUND AND OBJECTIVES: The burden of infectious disease is high among kidney transplant recipients because of concomitant immunosuppression. In this study the incidence of infectious-related mortality and associated factors were evaluated. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In this registry-based retrospective, longitudinal cohort study, recipients of a first kidney transplant in Australia and New Zealand between 1997 and 2015 were included. Cumulative incidence of infectious-related mortality was estimated using competing risk regression (using noninfectious mortality as a competing risk event), and compared with age-matched, populated-based data using standardized incidence ratios. RESULTS: Among 12,519 patients, (median age 46 years, 63% men, 15% diabetic, 6% Indigenous ethnicity), 2197 (18%) died, of whom 416 (19%) died from infection. The incidence of infection-related mortality during the study period (1997-2015) was 45.8 (95% confidence interval [95% CI], 41.6 to 50.4) per 10,000 patient-years. The incidence of infection-related mortality reduced from 53.1 (95% CI, 45.0 to 62.5) per 10,000 person-years in 1997-2000 to 43.9 (95% CI, 32.5 to 59.1) per 10,000 person-years in 2011-2015 (P<0.001) Compared with the age-matched general population, kidney transplant recipients had a markedly higher risk of infectious-related death (standardized incidence ratio, 7.8; 95% CI, 7.1 to 8.6). Infectious mortality was associated with older age (≥60 years adjusted subdistribution hazard ratio [SHR], 4.16; 95% CI, 2.15 to 8.05; reference 20-30 years), female sex (SHR, 1.62; 95% CI, 1.19 to 2.29), Indigenous ethnicity (SHR, 2.87; 95% CI, 1.84 to 4.46; reference white), earlier transplant era (2011-2015: SHR, 0.39; 95% CI, 0.20 to 0.76; reference 1997-2000), and use of T cell-depleting therapy (SHR, 2.43; 95% CI, 1.36 to 4.33). Live donor transplantation was associated with lower risk of infection-related mortality (SHR, 0.53; 95% CI, 0.37 to 0.76). CONCLUSIONS: Infection-related mortality in kidney transplant recipients is significantly higher than the general population, but has reduced over time. Risk factors include older age, female sex, Indigenous ethnicity, T cell-depleting therapy, and deceased donor transplantation. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2019_08_27_CJN03200319.mp3.

External validation of the US and UK kidney donor risk indices for deceased donor kidney transplant survival in the Australian and New Zealand population.

BACKGROUND: The US Kidney Donor Risk Index (KDRI) and the UK KDRI were developed to estimate the risk of graft failure following kidney transplantation. Neither score has been validated in the Australian and New Zealand (ANZ) population. METHODS: Using data from the Australia and New Zealand Organ Donor (ANZOD) and Dialysis and Transplant (ANZDATA) Registries, we included all adult deceased donor kidney-only transplants performed in ANZ from 2005 to 2016 (n = 6405). The KDRI was calculated using both the US donor-only and UK formulae. Three Cox models were constructed (Model 1: KDRI only; Model 2: Model 1 + transplant characteristics; Model 3: Model 2 + recipient characteristics) and compared using Harrell's C-statistics for the outcomes of death-censored graft survival and overall graft survival. RESULTS: Both scores were strongly associated with death-censored and overall graft survival (P < 0.0001 in all models). In the KDRI-only models, discrimination of death-censored graft survival was moderately good with C-statistics of 0.63 and 0.59 for the US and UK scores, respectively. Adjusting for transplant characteristics resulted in marginal improvements of the US KDRI to 0.65 and the UK KDRI to 0.63. The addition of recipient characteristics again resulted in marginal improvements of the US KDRI to 0.70 and the UK KDRI to 0.68. Similar trends were seen for the discrimination of overall graft survival. CONCLUSIONS: The US and UK KDRI scores were moderately good at discriminating death-censored and overall graft survival in the ANZ population, with the US score performing slightly better in all models.

Comparison of cause of death between Australian and New Zealand Dialysis and Transplant Registry and the Australian National Death Index.

AIM: The aim of the present study was to understand the differences in how cause of death for patients receiving renal replacement therapy in Australia is recorded in The Australian and New Zealand Dialysis and Transplant Registry (ANZDATA) compared to the National Death Index (NDI). METHODS: Data linkage was performed between ANZDATA and NDI for all deaths in the period 1980-2013. Cause of death was classified according to ICD-10 chapter. Overall and chapter specific agreement were assessed using the Kappa statistic. Descriptive analysis was used to explore differences where there was disagreement on primary cause of death. RESULTS: The analysis cohort included 28 675 patients. Ninety five percent of ANZDATA reported deaths fell within +/- 3 days of the date recorded by NDI. Circulatory death was the most common cause of death in both databases (ANZDATA 48%, NDI 32%). Overall agreement at ICD chapter level of primary cause was poor (36%, kappa 0.22). Agreement was best for malignancy (kappa 0.71). When there was disagreement on primary cause of death these were most commonly coded as genitourinary (35%) and endocrine (25.0%) in NDI, and circulatory (39%) and withdrawal (24%) in ANZDATA. Sixty-nine percent of patients had a renal related cause documented as either primary or a contributing cause of death in the NDI. CONCLUSION: There is poor agreement in primary cause of death between ANZDATA and NDI which is in part explained by the absence of diabetes and renal failure as causes of death in ANZDATA and the absence of 'withdrawal' in NDI. These differences should be appreciated when interpreting epidemiological data on cause of death in the Australian end stage kidney disease population.

Access to waitlisting for deceased donor kidney transplantation in Australia.

AIM: A detailed analysis of waitlisting for deceased donor kidney transplantation in Australia has not previously been reported. We aimed to determine if patient characteristics associated with waitlisting identify areas of potential inequality in access to transplantation in Australia. METHODS: A competing risk time-to-event model was used to determine predictors of waitlisting for all adult incident renal replacement therapy patients in Australia between 2006 and 2015. Secondary analysis was performed to determine predictors of overall access to transplantation (using a combined outcome of waitlisting and living donor transplantation). RESULTS: The cohort consisted of 21 231 patients with a median age of 63 years. Overall, 4361 (20.5%) were waitlisted and 1239 (5.8%) received a living donor transplant without being previously waitlisted. Primary analysis revealed that medical comorbidities, older age, smoking status and body mass index were all significant predictors of waitlisting and that and there was variation in waitlisting practice across states Despite adjustment for the above factors, demographic characteristics, including Indigenous ethnicity (subdistribution hazard ratios (SHR) 0.46 (95% confidence interval (CI) 0.38-0.55)), female gender (SHR 0.85 (95% CI 0.80, 0.91)) and residence in a regional area (SHR 0.88 (95% CI 0.81-0.95)) were also associated with a lower likelihood of waitlisting. Secondary analysis showed younger age and higher socio-economic advantage were additional predictors of overall access to transplantation, driven by higher rates of living donor transplantation. CONCLUSION: Demographic as well as clinical characteristics are associated with reduced likelihood of waitlisting for kidney transplantation in Australia. Further analysis and auditing should be considered to determine if this reflects other unmeasured factors or highlights a need to address inequality.

HLA epitope matching in pediatric renal transplantation.

Chronic graft loss due to antibody-mediated rejection (AMR) and the difficulty of re-transplanting highly sensitized patients are two of the major long-term challenges in pediatric renal transplantation. Treatments for AMR are often ineffective and desensitization protocols can be a high risk, making prevention a highly appealing strategy. Insights into the structural determinants of humoral alloantigenicity present an exciting opportunity to reassess our current paradigm of tissue matching and potentially preventing these complications. We review the theory behind human leukocyte antigen (HLA) B cell epitopes and the various systems that have been proposed to define them, including eplets. There is a growing body of clinical evidence suggesting that epitope-based tissue matching may be superior to traditional HLA antigen matching at predicting a range of clinical outcomes. However, additional studies are required to better understand the biological relevance of these systems of defining epitopes and their role in pediatric transplantation.