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Background: Reducing nonutilization of kidneys recovered from deceased donors is a current policy concern for kidney allocation in the United States. The likelihood of nonutilization is greater with a higher kidney donor risk index (KDRI) offer. We examine how opening offers for organs with KDRI >1.75 to the broader waitlist at varying points of time affects usage rates., Methods: We simulate kidney allocation using data for January 2018 to June 2019 from Organ Procurement and Transplantation Network. For the simulation experiment, allocation policy is modified so that KDRI >1.75 organs are offered to all local candidates (same donation service area) after a set amount of cold time simultaneously. Open offers to candidates nationally are similarly examined., Results: Simulation results ( n =50 replications) estimate that opening offers locally for KDRI >1.75 after 10 hours yields a nonutilization rate of 38% (range: 35%-42%), less than the prevailing rate of 55% of KDRI >1.75 kidneys. Opening offers after 5 hours yields 30% (range: 26%-34%), reducing the prevailing nonutilization rate by 45%. Opening offers nationally after 10 and 5 hours yields nonutilization rates of 11% (range: 8%-15%) and 6% (range: 4%-9%) for KDRI >1.75 kidneys, respectively., Conclusions: Simulation findings indicate that opening offers and adjusting their timing can significantly reduce nonutilization of high-KDRI kidneys., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Nephrology.)

Background: In the United States, more than 50% of kidneys in the lowest 15% quality range (those with Kidney Donor Profile Index >85) are discarded. Studies suggest that using more of these kidneys could benefit patients waiting for a transplant. This study assesses the trade-offs physicians make when selecting recipients for lower-quality kidneys., Methods: A discrete choice experiment (DCE) was administered to surgeons and nephrologists in the United States who are involved in kidney acceptance decisions. The DCE presented kidneys that varied in terms of Kidney Donor Profile Index, expected cold ischemia time, donor age, pump parameters, serum creatinine levels, glomerulosclerosis, donor diabetes status, and whether donation was made after circulatory death. Candidate characteristics included recipients' age, diabetes history, time on dialysis, ejection fraction, HLA mismatch, calculated panel reactive antibody, and Karnofsky performance score. Regression analysis was used to estimate acceptability weights associated with kidney and recipient characteristics., Results: A total of 108 physicians completed the DCE. The likelihood of acceptance was significantly lower with deterioration of kidney quality, expected cold ischemia time at transplantation, and missing biopsy and pump information. Acceptance was prioritized for patients who were higher on the waiting list, younger recipients, those who have spent less time on dialysis, and those without a history of diabetes. Performance status (Karnofsky score) and calculated panel reactive antibody also had a statistically significant but smaller association. Finally, ejection fraction had a marginally significant association, and HLA match had no significant association with the acceptance of marginal kidneys. A group of respondents were found to be primarily concerned about cold ischemia time., Conclusions: In this DCE, physicians considered the recipient characteristics that inform expected post-transplant survival score when they decided whether to accept a marginal kidney for a given recipient., (Copyright © 2023 by the American Society of Nephrology.)

Purpose of Review: The donation and kidney transplant system in the United States is challenged with reducing the number of kidneys that are procured for transplant but ultimately discarded. That number can reach 20% of donated kidneys each year., Recent Findings: The reasons for these discards, in the face of overwhelming demand, are multiple., Summary: The authors review the data supporting a number of potential causes for high discard rates as well as provide potential solutions to the problem., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background and Objectives: Reducing discard is important for the US transplantation system because nearly 20% of the deceased donor kidneys are discarded. One cause for the discards is the avoidance of protracted cold ischemia times. Extended cold ischemia times at transplant are associated with additional risk of graft failure and patient mortality. A preference for local (within the same donor service area) or low-Kidney Donor Risk Index organs, the endogeneity of cold ischemia time during organ allocation, and the use of provisional offers all complicate the analysis of cold ischemia times' influence on kidney acceptance decision making., Design, Setting, Participants, & Measurements: Using January 2018 to June 2019 Organ Procurement and Transplantation Network data, we modeled the probability of accepting an offer for a kidney after provisional acceptance. We use logistic regression that includes cold ischemia time, Kidney Donor Risk Index, and other covariates selected from literature. Endogeneity of cold ischemia time was treated by a two-stage instrumental variables approach., Results: Logistic regression results for 3.33 million provisional acceptances from 12,369 donors and 108,313 candidates quantify trade-offs between cold ischemia time at the time of offer acceptance and donor-recipient characteristics. Overall, each additional 2 hours of cold ischemia time affected acceptance for nonlocal and local recipients (odds ratio, 0.75; 95% confidence interval, 0.73 to 0.77, odds ratio, 0.88; 95% confidence interval, 0.86 to 0.91; P <0.001). For Kidney Donor Risk Index >1.75 (Kidney Donor Profile Index >85) kidneys, an additional 2 hours of cold ischemia time for nonlocal and local recipients was associated with acceptance with odds ratio, 0.58; 95% confidence interval, 0.54 to 0.63 (nonlocal) and odds ratio, 0.65; 95% confidence interval, 0.6 to 0.7 (local); P <0.001. The effect of an additional 2 hours of cold ischemia time on acceptance of kidneys with Kidney Donor Risk Index ≤1.75 (Kidney Donor Profile Index ≤85) was less pronounced for nonlocal offers (odds ratio, 0.82; 95% confidence interval, 0.80 to 0.85; P <0.001) and not significant for local offers., Conclusions: The acceptability of marginal organs was higher when placements were nearer to the donor and when cold ischemia time was shorter., (Copyright © 2022 by the American Society of Nephrology.)

Background: Despite the kidney supply shortage, 18%-20% of deceased donor kidneys are discarded annually in the United States. In 2018, 3569 kidneys were discarded., Methods: We compared machine learning (ML) techniques to identify kidneys at risk of discard at the time of match run and after biopsy and machine perfusion results become available. The cohort consisted of adult deceased donor kidneys donated between December 4, 2014, and July 1, 2019. The studied ML models included Random Forests (RF), Adaptive Boosting (AdaBoost), Neural Networks (NNet), Support Vector Machines (SVM), and K-nearest Neighbors (KNN). In addition, a Logistic Regression (LR) model was fitted and used for comparison with the ML models' performance., Results: RF outperformed other ML models. Of 8036 discarded kidneys in the test dataset, LR correctly classified 3422 kidneys, whereas RF correctly classified 4762 kidneys (area under the receiver operative curve [AUC]: 0.85 versus 0.888, and balanced accuracy: 0.681 versus 0.759). For the kidneys with kidney donor profile index of >85% (6079 total), RF significantly outperformed LR in classifying discard and transplant prediction (AUC: 0.814 versus 0.717, and balanced accuracy: 0.732 versus 0.657). More than 388 kidneys were correctly classified using RF. Including biopsy and machine perfusion variables improved the performance of LR and RF (LR's AUC: 0.888 and balanced accuracy: 0.74 versus RF's AUC: 0.904 and balanced accuracy: 0.775)., Conclusions: Kidneys that are at risk of discard can be more accurately identified using ML techniques such as RF., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Despite the shortage of kidneys for transplantation in the United States, approximately 18%-20% of deceased donor kidneys are discarded each year. These discarded kidneys can offer a survival benefit to suitable patients. Revisions to the current kidney allocation policy may be needed to reduce deceased donor kidney discard. We surveyed transplant physicians and patients to assess their perceived acceptability of policy proposals to reduce the discard of deceased donor kidneys. Members of professional societies (AST, ASTS) and a patient organization (AAKP) were invited to complete the survey. Responses were obtained from 97 physicians and 107 patients. The majority of physicians (73.4%) and patients (73.8%) "somewhat" or "completely" accepted a policy for fast-tracking kidneys at risk of discard. Physicians and patients also supported returning a proportion of waiting time to patients who accept KDPI >85 kidneys and experience graft failure within the first 12 months, with 36% of physicians and 50% of patients electing to return 100% of the waiting time. The majority of physicians (75%) "somewhat or completely" accepted a policy to skip less aggressive centers for KDPI 90 + offers. Physicians and patients provided insights into factors researchers, and policymakers should consider in the design and implementation of these policies., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Yearly, over half of deceased-donor kidneys with kidney donor profile index (KDPI) > 85 were discarded, yet they could improve survival outcomes for dialysis patients. The potential risk of high-KDPI kidney transplant (KT) depends on the patient's overall health summarized by functional status, which should be examined. The analyzed cohort consisted of adult deceased-donor KT candidates on dialysis listed in 2005-2014. A multivariate Cox proportional hazards model was fitted with functional status, measured using Karnofsky Performance Score (KPS), and transplant status as time-varying covariates. Derived from the Cox model, survival curves were analyzed to compare the survival outcomes between dialysis and transplant with different kidney qualities across three different KPS strata: 10-40, 50-70, and 80-100. With KDPI 0-99 KT, KPS 10-40 patients will survive ≥4.38 years median compared with 3.21 years median if they remained on dialysis. For KPS 50+ patients, the median survival years increase from 5.82 to 6.60 years on dialysis to ≥7.83 years after KDPI < 100 KT. The risk-adjusted analyses suggested that patients are expected to benefit more from KDPI 81-99 KT than from remaining on dialysis., (© 2019 Steunstichting ESOT.)

Background: Recorded at the time of transplant and reported to the Organ Procurement and Transplantation Network, patient's functional status is measured using the Karnofsky performance score (KPS), ranging 0 to 100. Functional status analysis may provide insights on candidate listing and posttransplant survival outcomes for deceased-donor kidney transplants., Methods: The cohort consisted of adult deceased-donor kidney transplant recipients transplanted beginning January 2007. One-year and 3-year Cox models for posttransplant survival were fitted with current Scientific Registry of Transplant Recipients (SRTR) variables and KPS. Comparative analyses were performed between the SRTR model without KPS and augmented model with it. Using the augmented model, we examined the impact of Kidney Donor Profile Index on posttransplant survivals for 5 different KPS strata: 10 to 30, 40 to 50, 60 to 70, 80 to 90, and 100., Results: Comparative analyses showed that KPS was a statistically significant predictor for posttransplant survival: it improved model calibration, discrimination, and predictive accuracy. From the augmented model, the survival curves illustrated that recipients with KPS 40 to 50 and kidneys with Kidney Donor Profile Index as high as 99 have expected survival probabilities of above 90% in 1 year and above 80% in 3 years. The expected survival probabilities improve as KPS increases. Recipients with KPS 10 to 30 have the worst survival probability, even if they received high-quality kidneys., Conclusions: Insights from the survival analyses recommend possible inclusion of functional status into SRTR's risk-adjusted models. Moreover, they invite further examination of its use to improve current listing and transplantation strategies at transplant centers and potentially reduce deceased-donor kidney discard rate.

Background: Underutilization of marginal-quality kidneys for transplantation produced ideas of expediting kidney placement for populations with decreased opportunities of receiving transplants. Such policies can be less efficacious for specific individuals and should be scrutinized until the decision-making for accepting marginal-quality organs, which has relied on experiential judgment, is better understood at the individual level. There exist rigorous tools promoting personalized decisions with useful and objective information., Methods: This article introduces a decision-tree methodology that analyzes a patient's dilemma: to accept a kidney offer now or reject it. The methodology calculates the survival benefit of accepting a kidney given a certain quality now and the survival benefit of rejecting it. Survival benefit calculation accounts for patients' and donors' characteristics and transplant centers' and organ procurement organizations' performances and incorporates patients' perceived transplant and dialysis utilities. Valuations of rejecting an offer are contingent on future opportunities and subject to uncertainty in the timing of successive kidney offers and their quality and donor characteristics., Results: The decision tree was applied to a realistic patient profile as a demonstration. The tool was tested on 1000 deceased-donor kidney offers in 2016. Evaluating up to 1 year of future offers, the tool attains 61% accuracy, with transplant utility of 1.0 and dialysis utility of 0.5. The accuracy reveals potential bias in kidney offer acceptance/rejection at transplant centers., Conclusions: The decision-tree tool presented could aid personalized transplant decision-making in the future by providing patients with calculated, individualized survival benefits between accepting and rejecting a kidney offer.

The national demand for kidney transplantation far outweighs the supply of kidney organs. Currently, a patient's ability to receive a kidney transplant varies depending on where he or she seeks transplantation. This reality is in direct conflict with a federal mandate from the Department of Health and Human Services. We analyze current kidney allocation and develop an alternative kidney sharing strategy using a multiperiod linear optimization model, KSHARE. KSHARE aims to improve geographic equity in kidney transplantation while also respecting transplant system constraints and priorities. KSHARE is tested against actual 2000-2009 kidney allocation using Organ Procurement and Transplant Network data. Geographic equity is represented by minimizing the range in kidney transplant rates around local areas of the country. In 2009, less than 25% of standard criteria donor kidneys were allocated beyond the local area of procurement, and Donor Service Area kidney transplantation rates varied from 3.0% to 30.0%, for an overall range of 27.0%. Given optimal sharing of kidneys within 600 miles of procurement for 2000-2009, kidney transplant rates vary from 5.0% to 12.5% around the country for an overall kidney transplant range of 7.5%. Nationally sharing kidneys optimally between local areas only further decreases the transplant rate range by 1.7%. Enhancing the practice of sharing kidneys by the KSHARE model may increase geographic equity in kidney transplantation., (© The Author(s) 2014.)

Background: The national organ allocation system for deceased-donor kidney transplant will endure increased burden as the waitlist expands and organ shortage persists. The Department of Health and Human Services issued the "Final Rule" in 1998 that states "Organs and tissues ought to be distributed on the basis of objective priority criteria and not on the basis of accidents of geography." However, it has not been addressed whether the rule was effective in encouraging regions to share the additional burden equitably., Objective: To assess the significance of changes of geographic disparities for four metrics since the rule's adoption: waiting times, transplant rates, pretransplant mortality, and organ quality., Methods: Using Organ Procurement and Transplant Network data from 1988 through 2009, annual ranges of the metrics were calculated for all donor service areas and United Network for Organ Sharing regions. Time series analyses were used to compare the metrics before and after the enactment of the Final Rule., Results: A total of 412,127 kidney transplant candidates and 178,163 deceased-donor recipients were analyzed. Demographics varied significantly by region. The ranges of the four metrics have worsened by approximately 30% or more after the Final Rule at both the regional and donor service area levels., Conclusion: Increasing geographic disparity in allocation procedures may yield diverging outcomes and experiences in different locations for otherwise similar candidates. Consensus for measuring allocation discrepancies and policy interventions are required to mitigate the inequities.

Background and Objectives: The Statewide Sharing variance to the national kidney allocation policy allocates kidneys not used within the procuring donor service area (DSA), first within the state, before the kidneys are offered regionally and nationally. Tennessee and Florida implemented this variance. Known geographic differences exist between the 58 DSAs, in direct violation of the Final Rule stipulated by the US Department of Health and Human Services. This study examined the effect of Statewide Sharing on geographic allocation disparity over time between DSAs within Tennessee and Florida and compared them with geographic disparity between the DSAs within a state for all states with more than one DSA (California, New York, North Carolina, Ohio, Pennsylvania, Texas, and Wisconsin)., Design, Setting, Participants, & Measurements: A retrospective analysis from 1987 to 2009 was conducted using Organ Procurement and Transplant Network data. Five previously used indicators for geographic allocation disparity were applied: deceased-donor kidney transplant rates, waiting time to transplantation, cumulative dialysis time at transplantation, 5-year graft survival, and cold ischemic time., Results: Transplant rates, waiting time, dialysis time, and graft survival varied greatly between deceased-donor kidney recipients in DSAs in all states in 1987. After implementation of Statewide Sharing in 1992, disparity indicators decreased by 41%, 36%, 31%, and 9%, respectively, in Tennessee and by 28%, 62%, 34%, and 19%, respectively in Florida, such that the geographic allocation disparity in Tennessee and Florida almost completely disappeared. Statewide kidney allocations incurred 7.5 and 5 fewer hours of cold ischemic time in Tennessee and Florida, respectively. Geographic disparity between DSAs in all the other states worsened or improved to a lesser degree., Conclusions: As sweeping changes to the kidney allocation system are being discussed to alleviate geographic disparity--changes that are untested run the risk of unintended consequences--more limited changes, such as Statewide Sharing, should be further studied and considered., (Copyright © 2014 by the American Society of Nephrology.)

Background: Waiting time to deceased donor kidney transplant varies greatly across the United States. This variation violates the final rule, a federal mandate, which demands geographic equity in organ allocation for transplantation., Methods: Retrospective analysis of the United States Renal Data System and United Network for Organ Sharing database from 2000 to 2009. Median waiting time was calculated for each of the 58 donor service areas (DSA) in the United States. Multivariate regression was performed to identify DSA predictors for long waiting times to kidney transplantation., Results: The median waiting time varied between the 58 DSAs from 0.61 to 4.57 years, ranging from 0.59 to 5.17 years for standard criteria donor kidneys and 0.41 to 4.69 years for expanded criteria donor kidneys. The disparity in waiting time between the DSAs grew from 3.26 years (range, 0.41-3.67) in 2000 to 4.72 years (range, 0.50-5.22) in 2009. In DSAs with longer waiting times, there were significantly more patients suffering from end-stage renal disease and more patients listed for kidney transplant, lower kidney procurement rates, and higher transplant center competition. Patients were more likely black, sensitized, with lower educational attainment and less likely to waitlist outside of their DSA of residence. Donor organs used in DSAs with long waiting times were more likely hepatitis C positive and had a higher kidney donor profile index. Graft and patient survival at 5 years was worse for deceased donor kidney transplant, but rates for living donor kidney transplant were higher., Conclusion: Our analysis demonstrates significant and worsening geographic disparity in waiting time for kidney transplant across the DSAs. Increase in living donor kidney transplant and use of marginal organs has not mitigated the disparity. Changes to the kidney allocation system might be required to resolve this extensive geographic disparity in kidney allocation.