Comparison of cause of death between ANZDATA 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

Enhanced Interleukin (IL)-13 Responses in Mice Lacking IL-13 Receptor α 2

Interleukin (IL)-13 has recently been shown to play important and unique roles in asthma, parasite immunity, and tumor recurrence. At least two distinct receptor components, IL-4 receptor (R)α and IL-13Rα1, mediate the diverse actions of IL-13. We have recently described an additional high affinity receptor for IL-13, IL-13Rα2, whose function in IL-13 signaling is unknown. To better appreciate the functional importance of IL-13Rα2, mice deficient in IL-13Rα2 were generated by gene targeting. Serum immunoglobulin E levels were increased in IL-13Rα2−/− mice despite the fact that serum IL-13 was absent and immune interferon γ production increased compared with wild-type mice. IL-13Rα2–deficient mice display increased bone marrow macrophage progenitor frequency and decreased tissue macrophage nitric oxide and IL-12 production in response to lipopolysaccharide. These results are consistent with a phenotype of enhanced IL-13 responsiveness and demonstrate a role for endogenous IL-13 and IL-13Rα2 in regulating immune responses in wild-type mice

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.</p

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

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.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.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.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

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

Infection-Related Mortality in Recipients of a Kidney Transplant in Australia and New Zealand : Infection-related mortality in kidney transplant recipients

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.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.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

INFECTION-RELATED MORTALITY FOLLOWING KIDNEY TRANSPLANTATION 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.Samuel Chan, Elaine M. Pascoe, Philip A. Clayton, Stephen P. McDonald, Wai H. Lim, Matthew P. Sypek, Suetonia C. Palmer, Nicole M. Isbel, Ross S. Francis, Scott B. Campbell, Carmel M. Hawley and David W. Johnso