Impact of donor kidney biopsy on kidney yield and posttransplant outcomes.

Procurement biopsy is performed to determine kidney quality, but evidence supporting such association is poor. We investigated the impact of glomerulosclerosis percentage (GS%) on kidney yield and patient outcomes. Information on deceased kidney donors from July 1, 2017, to June 30, 2019, was collected. Association between GS% and kidney yield (number of kidneys procured per donor) and posttransplant graft and patient outcomes were studied. Maximal GS% and minimal GS% were calculated to determine the relationship between GS% and kidney yield; minimal GS% only for correlation with posttransplant outcomes. Multinomial logistic regression and Cox models with least absolute shrinkage and selection operator were used to analyze the association of GS% with kidney yield and posttransplant outcomes, respectively. The kidney yield was 1.63 when maximal GS% and minimal GS% were <5%, but was 0.88 when both GS% were >20%. The hazard ratio for graft failure 1 year after transplant was 1.05 when minimal GS% was 16% to 20%, but was 1.3 for GS% of >20%. The hazard ratio for mortality increased from 1 to 1.2 when minimal GS% reached >20%. In summary, higher GS% was associated with lower kidney yield and inferior posttransplant outcomes. Incorporation of GS% into Scientific Registry of Transplant Recipients models may reassure organ procurement organizations and transplant centers pursuing kidneys with relatively high GS% levels, thereby reducing kidney discard rates.

Expected effect of the lung Composite Allocation Score system on US lung transplantation.

Efforts are underway to transition the current lung allocation system to a continuous distribution framework whereby multiple factors are simultaneously combined into a Composite Allocation Score (CAS) to prioritize candidates for lung transplant. The purpose of this study was to compare discrete CAS scenarios with the current concentric circle-based allocation system to assess their potential effects on the US lung transplantation system using the Scientific Registry of Transplant Recipients' thoracic simulated allocation model. Six alternative CAS scenarios were compared over 10 simulation runs using data from individuals on the lung transplant waiting list from January 1, 2018, through December 31, 2019. Outcome measures were transplant rate, count, waitlist deaths, posttransplant deaths within 2 years, donor-to-recipient distance, and percentage of organs predicted to have flown. Across scenarios, waitlist deaths decreased by 36% to 47%, with larger decreases in deaths at lower placement efficiency weight and higher weighting of the waitlist outcomes. When waitlist outcomes were equally weighted to posttransplant outcomes, more transplants occurred in individuals with the highest expected posttransplant survival. All CAS scenarios led to improved overall measures of equity compared with the current Lung Allocation Score system, including reduced waitlist deaths, and resulted in similar posttransplant survival.

The Effect of Acuity Circles on Deceased Donor Transplant and Offer Rates Across Model for End-Stage Liver Disease Scores and Exception Statuses.

Acuity circles (AC), the new liver allocation system, was implemented on February 4, 2020. Difference-in-differences analyses estimated the effect of AC on adjusted deceased donor transplant and offer rates across Pediatric End-Stage Liver Disease (PELD) and Model for End-Stage Liver Disease (MELD) categories and types of exception statuses. The offer rates were the number of first offers, top 5 offers, and top 10 offers on the match run per person-year. Each analysis adjusted for candidate characteristics and only used active candidate time on the waiting list. The before-AC period was February 4, 2019, to February 3, 2020, and the after-AC period was February 4, 2020, to February 3, 2021. Candidates with PELD/MELD scores 29 to 32 and PELD/MELD scores 33 to 36 had higher transplant rates than candidates with PELD/MELD scores 15 to 28 after AC compared with before AC (transplant rate ratios: PELD/MELD scores 29-32, 2.34 3.324.71 ; PELD/MELD scores 33-36, 1.70 2.513.71 ). Candidates with PELD/MELD scores 29 or higher had higher offer rates than candidates with PELD/MELD scores 15 to 28, and candidates with PELD/MELD scores 29 to 32 had the largest difference (offer rate ratios [ORR]: first offers, 2.77 3.955.63 ; top 5 offers, 3.90 4.394.95 ; top 10 offers, 4.85 5.305.80 ). Candidates with exceptions had lower offer rates than candidates without exceptions for offers in the top 5 (ORR: hepatocellular carcinoma [HCC], 0.68 0.770.88 ; non-HCC, 0.73 0.810.89 ) and top 10 (ORR: HCC, 0.59 0.650.71 ; non-HCC, 0.69 0.750.81 ). Recipients with PELD/MELD scores 15 to 28 and an HCC exception received a larger proportion of donation after circulatory death (DCD) donors after AC than before AC, although the differences in the liver donor risk index were comparatively small. Thus, candidates with PELD/MELD scores 29 to 34 and no exceptions had better access to transplant after AC, and donor quality did not notably change beyond the proportion of DCD donors.

Impact of COVID-19 pandemic on the size of US transplant waiting lists.

BACKGROUND: More patients are waitlisted for solid organs than transplants are performed each year. The COVID-19 pandemic immediately increased waitlist mortality and decreased transplants and listings. METHODS: To calculate the number of candidate listings after the pandemic began and short-term changes that may affect waiting time, we conducted a Scientific Registry of Transplant Recipients surveillance study from January 1, 2012 to February 28, 2021. RESULTS: The number of candidates on the liver waitlist continued a steady decline that began before the pandemic. Numbers of candidates on the kidney, heart, and lung waitlists decreased dramatically. More than 3000 fewer candidates were awaiting a kidney transplant on March 7, 2021, than on March 8, 2020. Listings and removals decreased for each solid organ beginning in March 2020. The number of heart and lung listings returned to equal or above that of removals. Listings for kidney transplant, which is often less urgent than heart and lung transplant, remain below numbers of removals. Removals due to transplant decreased for all organs, while removals due to death increased for only kidneys. CONCLUSIONS: We found no evidence of the predicted surge in listings for solid organ transplant with a plateau or control of the pandemic.

Improving the predictive ability of the pediatric end-stage liver disease score for young children awaiting liver transplant.

The current pediatric end-stage liver disease (PELD) score underestimates pediatric waitlist mortality. Children frequently require PELD exception points to achieve appropriate priority ranking. We developed a new PELD score using serum sodium, creatinine, and updated original PELD components to more accurately rank children and equalize children's mortality risk with the age-standardized mortality rate of adults. We included children aged younger than 12 years with chronic liver disease, listed for deceased donor livers January 1, 2005-December 31, 2017. Pediatric candidates (n = 5111) were followed from listing to the earliest of waitlist mortality (death or removal from the list due to being too sick to undergo transplant, n = 339) or 180 days. We incorporated linear splines for the current components of PELD and added sodium and creatinine to the equation. The updated PELD-Na-Cr had a cross-validated AUC ROC of 0.854, vs 0.799 for the original PELD. PELD-Na-Cr required 9.44 additional points to equalize children's mortality risk with the age-standardized mortality rate of adults. PELD-Na-Cr better ordered the sickest children and should better prioritize children relative to adults. As a result, PELD-Na-Cr could increase pediatric transplant rates and reduce pediatric liver transplant waitlist mortality.

Mortality among solid organ waitlist candidates during COVID-19 in the United States.

We examined the effects of COVID-19 on solid organ waiting list mortality in the United States and compared effects across patient demographics (e.g., race, age, and sex) and donation service areas. Three separate piecewise exponential survival models estimated for each solid organ the overall, demographic-specific, and donation service area-specific differences in the hazard of waitlist mortality before and after the national emergency declaration on March 13, 2020. Kidney waiting list mortality was higher after than before the national emergency (adjusted hazard ratio [aHR], 1.37; 95% CI, 1.23-1.52). The hazard of waitlist mortality was not significantly different before and after COVID-19 for liver (aHR, 0.94), pancreas (aHR, 1.01), lung (aHR, 1.00), and heart (aHR, 0.94). Kidney candidates had notable variability in differences across donation service areas (aHRs, New York City, 2.52; New Jersey, 1.84; and Michigan, 1.56). The only demographic group with increased waiting list mortality were Blacks versus Whites (aHR, 1.41; 95% CI, 1.07-1.86) for kidney candidates. The first 10 weeks after the declaration of a national emergency had a heterogeneous effect on waitlist mortality rate, varying by geography and ethnicity. This heterogeneity will complicate comparisons of transplant program performance during COVID-19.

The Centers for Medicare and Medicaid Services' proposed metrics for recertification of organ procurement organizations: Evaluation by the Scientific Registry of Transplant Recipients.

On December 23, 2019, the US Centers for Medicare and Medicaid Services proposed 2 new standards that organ procurement organizations (OPOs) must meet for recertification. An OPO's organ donation rate (deceased donors/potential donors) and organ transplant rate (organs transplanted/potential donors) must not fall significantly below the 75th percentile for rates among all OPOs. We examined how OPOs would have fared under the proposed performance standards in 2016-2017. Data on donors and transplants were from the Organ Procurement and Transplantation Network; donor potential was estimated from Detailed Multiple Cause of Death data collected by the Centers for Disease Control and Prevention. In 2017, 31 (53%) OPOs failed to meet the proposed donation rate standard, 36 (62%) failed to meet the proposed organ transplant rate standard, and 37 (64%) failed at least 1 standard. We found that adjusting for age, race, and Hispanic ethnicity altered the evaluation: 8 OPOs changed their pass/fail status for the donation rate and 5 for the proposed organ transplant rate standard. We conclude that the proposed new standards may result in over half of OPOs facing decertification, and risk adjustment suggests that underlying characteristics of deaths vary regionally such that decertification decisions may be affected.

Posttransplant outcome assessments at listing: Long-term outcomes are more important than short-term outcomes.

Posttransplant outcome assessments are publicly reported for patient and regulatory use. However, the currently reported 1-year posttransplant graft survival assessments are commonly criticized for not identifying clinically meaningful differences between programs, and not providing information about longer-term posttransplant outcomes. We investigated the association of different posttransplant outcome assessments available to patients at the time of listing with subsequent posttransplant graft survival. The posttransplant assessments were from period prevalent, rather than incident, cohorts with more timely 1-, 3-, and 5-year follow-up and 6-, 12-, 18-, 24-, and 30-month cohort windows. The association of these assessments at listing with subsequent posttransplant graft survival included candidates listed between July 12, 2011, and December 15, 2015, who subsequently underwent transplant before December 31, 2018. The assessments with 1-year follow-up had uniformly weaker associations than the assessments with 3- and 5-year follow-up. The assessments with 5-year follow-up had the strongest association in kidney and liver transplantation. For kidney, liver, and lung transplantation, assessment windows of at least 18 months typically had the strongest associations with subsequent graft survival. Posttransplant assessments with 5-year follow-up and 18-30-month cohort windows are better than the current posttransplant assessment with 1-year follow-up, particularly at the time of listing.

The Collaborative Innovation and Improvement Network (COIIN): Effect on donor yield, waitlist mortality, transplant rates, and offer acceptance.

The Organ Procurement and Transplantation Network implemented the Collaborative Improvement and Innovation Network (COIIN) to improve the use of donors with kidney donor profile index >50%. COIIN recruited 2 separate cohorts of kidney transplant programs. Cohort A included 19 programs of 44 applicants (January 1, 2017, to September 30, 2017), and cohort B included 39 programs of 47 applicants (October 1, 2017, to June 30, 2018). We investigated the effect of COIIN on kidney yield (number of kidneys transplanted from donors from whom any organ was recovered), offer acceptance, deceased donor transplant rates, and waitlist mortality rates for January 1, 2016, to March 31, 2019. COIIN did not notably affect kidney yield or waitlist mortality rates. Cohort A, but not cohort B, had significantly higher deceased donor transplant and offer acceptance rates during its intervention period than programs not in COIIN (adjusted transplant rate ratio: cohort A, 1.08 1.171.27 , cohort B, 0.94 1.011.08 ; adjusted offer acceptance ratio: cohort A, 1.08 1.181.29 , cohort B, 0.93 1.001.08 ). Thus, COIIN improved the use of kidneys at programs in cohort A but not at those in cohort B. Further research is necessary to understand the different effects for cohorts A and B, and further monitoring of posttransplant outcomes is required.

Association between changes in Membership and Professional Standards Committee review criteria and use of higher-risk kidneys for transplant.

The Organ Procurement and Transplantation Network's Membership and Professional Standards Committee implemented an operational rule on March 1, 2017, intended to increase the number of kidneys transplanted from donors with kidney donor profile index (KDPI) ≥ 85% into recipients with poor estimated posttransplant survival (≥ 80%). Using data from the Scientific Registry of Transplant Recipients, ordinal and logistic regressions estimated, respectively, differences in kidney yield (number of transplanted kidneys per recovered donor) and offer acceptance practices before and after implementation. We included donors recovered January 1, 2016-February 28, 2018. The odds of higher kidney yield for donors with KDPI ≥ 85% were 27% higher after implementation (odds ratio, 1.06 1.271.53 ), but odds were also 20% higher for donors with KDPI < 85% (1.04 1.201.38 ). Thus, kidney yield was higher for all donors, with a slightly larger difference for donors with KDPI ≥ 85%. Additionally, the difference in offer acceptance before and after implementation was similar regardless of KDPI (KDPI < 85%, 0.97 1.021.07 ; KDPI ≥ 85%, 0.95 1.041.14 ). In the first year after implementation, kidney yield increased for donors with KDPI < and ≥ 85%. Thus, kidney yield from higher KDPI donors may have increased without the operational rule.

Seeking new answers to old questions about public reporting of transplant program performance in the United States.

The Scientific Registry of Transplant Recipients (SRTR) is mandated by the National Organ Transplant Act, the Final Rule, and the SRTR contract with the Health Resources and Services Administration to report program-specific information on the performance of transplant programs. Following a consensus conference in 2012, SRTR developed a new version of the public website to improve public reporting of often complex metrics, including changing from a 3-tier to a 5-tier summary metric for first-year posttransplant survival. After its release in December 2016, the new presentation was moved to a "beta" website to allow collection of additional feedback. SRTR made further improvements and released a new beta website in May 2018. In response to feedback, SRTR added 5-tier summaries for standardized waitlist mortality and deceased donor transplant rate ratios, along with an indicator of which metric most affects survival after listing. Presentation of results was made more understandable with input from patients and families from surveys and focus groups. Room for improvement remains, including continuing to make the data more useful to patients, deciding what additional data elements should be collected to improve risk adjustment, and developing new metrics that better reflect outcomes most relevant to patients.

Association of pretransplant and posttransplant program ratings with candidate mortality after listing.

The Scientific Registry of Transplant Recipients (SRTR) is responsible for understandable reporting of program metrics, including transplant rate, waitlist mortality, and posttransplant outcomes. SRTR developed five-tier systems for each metric to improve accessibility for the public. We investigated the associations of the five-tier assignments at listing with all-cause candidate mortality after listing, for candidates listed July 12, 2011-June 16, 2014. Transplant rate evaluations with one additional tier were associated with lower mortality after listing in kidney (hazard ratio [HR], 0.93 0.950.97 ), liver (HR, 0.87 0.900.92 ), and heart (HR, 0.92 0.961.00 ) transplantation. For lung transplant patients, mortality after listing was highest at programs with above- and below-average transplant rates and lowest at programs with average transplant rates, suggesting that aggressive acceptance behavior may not always provide a survival benefit. Waitlist mortality evaluations with one additional tier were associated with lower mortality after listing in kidney (HR, 0.94 0.960.99 ) transplantation, and posttransplant graft survival evaluations with one additional tier were associated with lower mortality after listing in lung (HR, 0.90 0.940.98 ) transplantation. Transplant rate typically had the strongest association with mortality after listing, but the strength of associations differed by organ.

The relationship between the C-statistic and the accuracy of program-specific evaluations.

The C-statistic of the risk-adjustment model is often used to judge the accuracy of program evaluations. However, the C-statistic depends on the variability in risk for individual transplants and may be inappropriate for determining the accuracy of program evaluations. A simulation study investigated the association of the C-statistic with several metrics of program evaluation accuracy, including categorizing programs into the 5-tier system and identifying programs for regulatory review. The simulation study used data from deceased donor kidney-alone transplants for adult recipients in the program-specific reports released January 2018. A range of C-statistics was generated by changing the variability in risk for individual transplants. The C-statistic had no association with any metric of program evaluation accuracy. Instead, the number of expected events at a program was the most important factor. For example, Spearman's rho, which is the correlation of ranks, was -0.27 and -0.72 between the true program-specific hazard ratios and assigned tiers for programs with, respectively, <3 and >10 expected events. Presence of unadjusted risk factors did not modify the associations, although the accuracy of program evaluations was systematically lower. Therefore, the C-statistic provides no information on the accuracy of program evaluations.

Comparing Scientific Registry of Transplant Recipients posttransplant program-specific outcome ratings at listing with subsequent recipient outcomes after transplant.

To improve accessibility of program-specific reports to patients, the Scientific Registry of Transplant Recipients released a 5-tier system for categorizing 1-year posttransplant program evaluations. Whether this system predicts subsequent posttransplant outcomes at the time patients are waitlisted has been questioned. We investigated the association of tier at listing and the corresponding continuous score used for tier assignment, which ranges from 0 (poor outcomes) to 1 (good outcomes), with eventual 1-year posttransplant graft survival for candidates listed between July 12, 2011, and June 16, 2014, who underwent transplant before December 31, 2016. One additional tier at listing was associated with better 1-year posttransplant outcomes in liver (hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.89-0.97) and lung transplant (HR, 0.90; 95% CI, 0.84-0.97) but not kidney (HR, 0.96; 95% CI, 0.92-1.01) or heart transplant (HR, 1.02; 95% CI, 0.93-1.10). In liver and lung transplant, longer time between listing and transplant was associated with stronger protective effects for high-tier programs. In kidney, liver, and lung transplant, posttransplant evaluations at listing had nonlinear associations with eventual posttransplant outcomes: relatively flat for 5-tier scores <0.5 and decreasing for scores >0.5. After adjustment for measured recipient and donor risk factors, posttransplant evaluations at listing predicted differences in eventual outcomes in liver and lung transplant, providing useful information to patients.

The association between loss of Medicare, immunosuppressive medication use, and kidney transplant outcomes.

Kidney transplant recipients aged <65 years qualify for Medicare coverage, but coverage ends 3 years posttransplant. We determined the association between timing of Medicare loss and immunosuppressive medication fills and kidney allograft loss. Using data from the Scientific Registry of Transplant Recipients (SRTR), US Renal Data System, and Symphony pharmacy fill database, we analyzed 78 861 Medicare-covered, kidney-alone recipients aged <65 years, and assessed the timing of Medicare loss posttransplant: early (<3 years), on-time (at 3 years), or late (>3 years). Immunosuppressant use was measured as medication possession ratio (MPR). Allograft loss was assessed using SRTR data. MPR was lower for recipients with early or late Medicare loss compared with no coverage loss for all immunosuppressive medication types. For calcineurin inhibitors, early Medicare loss was associated with a 53% to 86% lower MPR. On-time Medicare loss was not associated with a lower MPR. When recipients were matched by age, posttransplant timing of Medicare loss, and donor risk, the hazard of allograft loss was 990% to 1630% higher after early Medicare loss, and 140% to 740% higher after late Medicare loss, with no difference in the hazard for on-time Medicare loss. Ensuring ongoing Medicare access before and after 3 years posttransplant could affect graft survival.

Scientific Registry of Transplant Recipients program-specific reports: where we have been and where we are going.

PURPOSE OF REVIEW: Reporting provider data on quality to patients and the general public is increasingly common in healthcare. Reporting outcomes in solid organ transplantation has always been controversial and deserves careful consideration to ensure optimal results. RECENT FINDINGS: As mandated by Federal law, the Scientific Registry of Transplant Recipients publishes program-specific reports on transplant candidates, recipients, donors, and transplant outcomes every 6 months. Recent changes designed to make the results more easily understood by patients and the general public have been well received by patients and controversial among providers. In particular, outcomes are now reported using a five-tier system that distinguishes program results better than the old three-tier system, in which almost all programs were reported "as expected." Metrics that reflect access to transplant are also reported, including transplant rate and survival on the waiting list. Possible measures of longer term outcomes and program rates of accepting organs for transplant are being explored. SUMMARY: Providing detailed information regarding transplant program practices and outcomes in ways that patients and the general public can understand remains a major focus of the Scientific Registry of Transplant Recipients. Efforts to improve data collection and metrics reported are ongoing.

Organ distribution without geographic boundaries: A possible framework for organ allocation.

The Final Rule mandates that organ allocation not be based on the transplant candidate's place of residence or listing, except as required by sound medical judgment and best use of donated organs, to avoid wasting organs and futile transplants, and to promote access and efficiency. Current Organ Procurement and Transplantation Network (OPTN) policies use donation service areas and OPTN regions to distribute and allocate organs for transplant. These policies have recently been called into question as not meeting the requirements of the Final Rule. Therefore, we propose using borderless allocation scores that combine medical priority scores with geographic feasibility scores. Medical priority scores are currently used in OPTN allocation policy, for example, the model for end-stage liver disease and the lung allocation score. Geographic feasibility scores can be developed to account for the effects of ischemia due to travel times, donor characteristics that modify the feasibility of traveling due to organ outcomes, and the costs of shipping organs over long distances. A borderless distribution and allocation system could address the goals of equity and utility, while fulfilling the mandates of the Final Rule and providing optimal use of a scare resource.

Heart and lung organ offer acceptance practices of transplant programs are associated with waitlist mortality and organ yield.

Variation in heart and lung offer acceptance practices may affect numbers of transplanted organs and create variability in waitlist mortality. To investigate these issues, offer acceptance ratios, or adjusted odds ratios, for heart and lung transplant programs individually and for all programs within donation service areas (DSAs) were estimated using offers from donors recovered July 1, 2016, and June 30, 2017. Logistic regressions estimated the association of DSA-level offer acceptance ratios with donor yield and local placement of organs recovered in the DSA. Competing risk methodology estimated the association of program-level offer acceptance ratios with incidence and rate of waitlist removals due to death or becoming too sick to undergo transplant. Higher DSA-level offer acceptance was associated with higher yield (odds ratios [ORs]: lung, 1.04 1.111.19 ; heart, 1.09 1.211.35 ) and more local placement of transplanted organs (ORs: lung, 1.01 1.121.24 ; heart, 1.47 1.691.93 ). Higher program-level offer acceptance was associated with lower incidence of waitlist removal due to death or becoming too sick to undergo transplant (hazard ratios [HRs]: heart, 0.80 0.860.93 ; lung, 0.67 0.750.83 ), but not with rate of waitlist removal (HRs: heart, 0.91 0.981.06 ; lung, 0.89 0.991.10 ). Heart and lung offer acceptance practices affected numbers of transplanted organs and contributed to program-level variability in the probability of waitlist mortality.

A kidney offer acceptance decision tool to inform the decision to accept an offer or wait for a better kidney.

We developed a kidney offer acceptance decision tool to predict the probability of graft survival and patient survival for first-time kidney-alone candidates after an offer is accepted or declined, and we characterized the effect of restricting the donor pool with a maximum acceptable kidney donor profile index (KDPI). For accepted offers, Cox proportional hazards models estimated these probabilities using transplanted kidneys. For declined offers, these probabilities were estimated by considering the experience of similar candidates who declined offers and the probability that declining would lead to these outcomes. We randomly selected 5000 declined offers and estimated these probabilities 3 years post-offer had the offers been accepted or declined. Predicted outcomes for declined offers were well calibrated (<3% error) with good predictive accuracy (area under the curve: graft survival, 0.69; patient survival, 0.69). Had the offers been accepted, the probabilities of graft survival and patient survival were typically higher. However, these advantages attenuated or disappeared with higher KDPI, candidate priority, and local donor supply. Donor pool restrictions were associated with worse 3-year outcomes, especially for candidates with high allocation priority. The kidney offer acceptance decision tool could inform offer acceptance by characterizing the potential risk-benefit trade-off associated with accepting or declining an offer.