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The Scientific Registry of Transplant Recipients (SRTR) held a consensus conference in 2012 that examined methods used by SRTR for constructing performance metrics and made recommendations on how to improve program-specific reports. That consensus conference provided 25 recommendations categorized as follows: statistical methods, risk adjustment, and outcomes and data. During the subsequent decade, SRTR has implemented most of these recommendations; these are described in this article along with plans for another consensus conference in 2022. With the present article, SRTR aims to create transparency in the field of transplant metrics and guide discussion in the planning of the next consensus conference in 2022. The new conference will revisit the previous topics and have a broader focus to improve the metrics and information that SRTR provides. Readers can provide feedback on topics to be discussed at the next consensus conference as early as possible, by emailing srtr@srtr.org with the subject line "Task 5 Public Comment."

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.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.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.We found no evidence of the predicted surge in listings for solid organ transplant with a plateau or control of the pandemic.

Major gaps remain in our understanding of antibody-mediated rejection (AMR) after kidney transplant. We examined the incidence, risk factors, response to treatment, and effects on outcomes of AMR at seven transplant programs in the long-term Deterioration of Kidney Allograft Function prospective study cohort. Among 3131 kidney recipients, there were 194 observed AMR cases (6.2%) during (mean ± SD) 4.85 ± 1.86 years of follow-up. Time to AMR was 0.97 ± 1.17 (median, 0.48) years. Risk factors for AMR included younger recipient age, human leukocyte antigen DR mismatches, panel-reactive antibody >0%, positive T- or B-cell cross-match, and delayed graft function. Compared with no AMR, the adjusted time-dependent hazard ratio for death-censored graft failure is 10.1 (95% confidence interval, 6.5-15.7) for all AMR patients, 4.0 (2.5, 9.1) for early AMR (

Background Sofosbuvir use in patients with decompensated cirrhosis may be associated with reduced liver transplant waitlist mortality and reduced need for transplant. Methods Data from the Scientific Registry of Transplant Recipients were linked with a national database of pharmacy claims. All adult patients on the liver transplant waitlist on January 1, 2014, or added to the list during 2014, with hepatitis C virus as reason for listing were identified (2009 patients). A subgroup of 1093 unique patients had consistent pharmacy claim capture and observations. We compared patients who were and were not treated with all sofosbuvir-based regimens. Results During the study period, 154 patients received sofosbuvir-based regimens. These patients had lower model for end-stage liver disease scores and significantly longer waiting times. We found a trend toward significance for more sofosbuvir-treated than untreated patients being removed from the waitlist due to improved condition (4.54% vs 3.19%, p=0.03). In a propensity score-adjusted analysis, sofosbuvir-treated patients were less likely to undergo transplant (hazard ratio 0.57, 95% confidence interval 0.37-0.89, p=0.01). Conclusion During the study period reflecting early sofosbuvir use, few liver transplant candidates received sofosbuvir. Use was associated with lower incidence of transplant and a trend toward more waitlist removals due to improved condition.

Background Candidates for repeat kidney transplant (KT) have increased. While graft and patient survival are inferior to primary KT, second and third KTs improve patient survival over dialysis. Little is known about the outcomes after fourth KTs. Methods We retrospectively compared characteristics of third and fourth KTs in the SRTR. Factors associated with graft survival in third vs fourth KT and patient survival of fourth KT vs patients waitlisted for a 4th KT were assessed by Cox regression and multivariable linear regression analysis. Results There were 3055 third- and fourth-time KTs performed in the United States. Fourth-time graft survival was not significantly different from third-time transplants (HR 1.06, P = .653). Patients who received a fourth KT have a significant survival advantage compared with patients who remained on the waitlist for a fourth KT (HR = 0.53, P = .006). Conclusions Graft and patient survival of fourth KTs are comparable to third KTs, but inferior to first and second KTs in terms of graft and patient survival. Recipients of fourth KT have had an increased life expectancy compared with patients waitlisted for a fourth KT.

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

Two renal-risk variants in the apolipoprotein L1 gene (APOL1) in African American (AA) deceased donors (DD) are associated with shorter renal allograft survival after transplantation. To identify additional genes contributing to allograft survival, a genome-wide association study was performed in 532 AA DDs. Phenotypic data were obtained from the Scientific Registry of Transplant Recipients. Association and single-nucleotide polymorphism (SNP)-by-APOL1 interaction tests were conducted using death-censored renal allograft survival accounting for relevant covariates. Replication and inverse-variance-weighted meta-analysis were performed using data from 250 AA DD in the Genomics of Transplantation study. Accounting for APOL1, multiple SNPs near the Nudix Hydrolase 7 gene (NUDT7) showed strong independent effects (P = 1.6 × 10(−8)−2.2 × 10(−8)). Several SNPs in the Translocation protein SEC63 homolog (SEC63; P = 2 × 10(−9)-3.7 × 10(−8)) and plasmacytoma variant translocation 1 (PVT1) genes (P = 4.0 × 10(−8)-7 × 10(−8)) modified the effect of APOL1 on allograft survival. SEC63 is expressed in human renal tubule cells and glomeruli, and PVT1 is associated with diabetic kidney disease. Overall, associations were detected for 41 SNPs (P = 2 × 10(−9)-5 × 10(−8)) contributing independently or interacting with APOL1 to impact renal allograft survival after transplantation from AA DD. Given the small sample size of the discovery and replication sets, independent validations and functional genomic efforts are needed to validate these results.

Cytochrome P450 3A5 (CYP3A5) and cytochrome P450 3A4 (CYP3A4) are the predominate enzymes responsible for tacrolimus metabolism. The presence of CYP3A4 and CYP3A5 genetic variants significantly affects tacrolimus clearance and dose requirements. CYP3A5*3 is a loss-of-function variant resulting in no CYP3A5 enzyme production. CYP3A4*22 is a variant that reduces production of functional CYP3A4 protein. Caucasians commonly carry these variant alleles but are very rarely homozygous for both CYP3A5*3 and CYP3A4*22. This report describes four kidney transplant recipients who carry a rare genotype combination (CYP3A5*3/*3 and CYP3A4*22/*22). These patients were identified from a larger cohort of Caucasian kidney transplant recipients (n=1366). To understand the significance of this genotype combination on tacrolimus troughs and doses, we compared these patients to recipients without this combination. Patients homozygous for both variants are at risk for profound reductions in metabolism of CYP3A substrates. A 342% and a 90.6% increase in the median dose-normalized trough was observed, when the CYP3A5*3/*3 and CYP3A4*22/*22 genotype combination was compared to the CYP3A5*1/*1 and CYP3A4*1/*1 genotype combination and the CYP3A5*3/*3 and CYP3A4*1/*1 genotype combination, respectively. These four individuals only required on average 2.5 mg/day of tacrolimus. Knowledge of these genotypes would be useful in selecting appropriate tacrolimus doses to avoid overexposure.

Objective To better inform health care consumers by better identifying differences in transplant program performance. Data Source Adult kidney transplants performed in the United States, January 1, 2012–June 30, 2014. Study Design In December 2016, the Scientific Registry of Transplant Recipients instituted a five-tier system for reporting transplant program performance. We compare the differentiation of program performance and the simulated misclassification rate of the five-tier system with the previous three-tier system based on the 95 percent credible interval. Data Collection Scientific Registry of Transplant Recipients database. Principal Findings The five-tier system improved differentiation and maintained a low misclassification rate of less than 22 percent for programs differing by two tiers. Conclusion The five-tier system will better inform health care consumers of transplant program performance.

Transplant eligibility for tobacco and/or marijuana using candidates varies among transplant centers. This study compared the impact of marijuana use and tobacco use on kidney transplant recipient outcomes. Kidney transplant recipients at a single center from 2001 to 2015 were reviewed for outcomes of all-cause graft loss, infection, biopsy-proven acute rejection, and estimated glomerular filtration rate between four groups: marijuana-only users, marijuana and tobacco users, tobacco-only users, and nonusers. The cohort (N = 919) included 48 (5.2%) marijuana users, 45 (4.8%) marijuana and tobacco users, 136 (14.7%) tobacco users, and 75% nonusers. Smoking status was not significantly associated with acute rejection, estimated glomerular filtration rate or pneumonia within one-year post-transplant in an adjusted model. Compared to nonuse, marijuana and tobacco use and tobacco-only use was significantly associated with increased risk of graft loss (aHR 1.68, P = .034 and 1.52, P = .006, respectively). Patients with isolated marijuana use had similar overall graft survival compared to nonusers (aHR 1.00, P = .994). Marijuana use should not be an absolute contraindication to kidney transplant.

The Organ Procurement and Transplantation Network is charged with overseeing the quality of transplant programs in the United States. However, there has been controversy over whether too many programs are being identified as underperforming. It has also been suggested that dramatic improvements in outcomes throughout the United States have made the thresholds for determining which deceased donor transplant programs are underperforming no longer clinically relevant. The Scientific Registry of Transplant Recipients compared actual and expected 1-y graft survival for transplant programs identified as underperforming in the most recent cohort (transplants from July 1, 2012 to December 31, 2014). For most organs, actual 1-y graft survival was substantially lower for programs identified as underperforming than for programs identified as performing as expected. Differences were smallest for kidney programs: median 1-y graft survival 89.2% vs 95.4% in large-volume programs identified and not identified for Membership and Professional Standards Committee review, respectively. Median expected graft survival was only slightly lower (94.8% vs 95.1%, respectively), suggesting that identified and not identified programs tend to have similar risk tolerances. An excess of 143 grafts were lost from kidney programs identified as underperforming. Transplant programs identified as underperforming generally have reduced 1-y graft survival that stakeholders may consider clinically relevant.

Little is known about how patients make the critical decision of choosing a transplant center. In the United States, acceptance criteria, waiting times, and mortality vary significantly by geography and center. We sought to understand patients' experiences and perspectives when selecting transplant centers. We included 82 kidney transplant patients in 20 semi-structured interviews, nine focus groups with local candidates, and three focus groups with national recipients. Sites included two local transplant centers in Minneapolis, Minnesota, and national recipients from across the United States. Transcripts were analyzed by two researchers using a thematic analysis. Several themes emerged related to priorities and barriers when choosing a center. Patients were often unfamiliar with options, even with multiple local centers. Patients described being referred to a specific center by a trusted provider. Patients prioritized perceived reputation, comfort, and convenience. Insurance coverage was both a source of information and a barrier to options. Patients underestimated differences across centers and the effects on being waitlisted and receiving a transplant. Barriers in decision making included an overwhelming scope of information and difficulty locating information relevant to patients with unique medical needs. Informed decisions could be improved by the dissemination of understandable information better tailored to individual patient needs.

BACKGROUND We performed a study to identify differences in the urinary microbiome associated with chronic allograft dysfunction (CAD) and compared the urinary microbiome of male and female transplant recipients with CAD. METHODS This case-control study enrolled 67 patients within the Deterioration of Kidney Allograft Function (DeKAF) Genomics cohort at two transplant centers. CAD was defined as a greater than 25% rise in serum creatinine relative to a 3 month post-transplant baseline. Urine samples from patients with and without CAD were analyzed using 16S V4 bacterial ribosomal DNA sequences. RESULTS Corynebacterium was more prevalent in female and male patients with CAD compared to non-CAD female patients (P = 0.0005). A total 21 distinct Operational Taxonomic Unit (OTUs) were identified as significantly different when comparing CAD and non-CAD patients using Kruskal-Wallis (P

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Patients with low tacrolimus troughs are at a higher risk of rejection while those with high troughs are at an increased risk for toxicity. Therefore, achieving the therapeutic range is important. • CYP3A5 genotype and days post transplant have been previously shown individually to be associated with tacrolimus troughs. WHAT THIS STUDY ADDS • This paper presents the first dosing model for tacrolimus using a combination of genetic and clinical factors in adult kidney transplant recipients. It was developed from one of the largest tacrolimus pharmacogenetic studies conducted to date (681 subjects and 11 823 trough concentrations). • We found that CL/F was significantly influenced by days post transplant, CYP3A5 genotype, transplantation at a steroid sparing centre, recipient age and the use of a calcium channel blocker. • Our large sample size enabled us to define the distinct differences in tacrolimus CL/F between three CYP3A5 genotype groups (*1/*1, *1/*3 and *3/*3). • This study is an important step towards using pharmacogenetic information in the clinical setting. AIM To develop a dosing equation for tacrolimus, using genetic and clinical factors from a large cohort of kidney transplant recipients. Clinical factors and six genetic variants were screened for importance towards tacrolimus clearance (CL/F). METHODS Clinical data, tacrolimus troughs and corresponding doses were collected from 681 kidney transplant recipients in a multicentre observational study in the USA and Canada for the first 6 months post transplant. The patients were genotyped for 2 724 single nucleotide polymorphisms using a customized Affymetrix SNP chip. Clinical factors and the most important SNPs (rs776746, rs12114000, rs3734354, rs4926, rs3135506 and rs2608555) were analysed for their influence on tacrolimus CL/F. RESULTS The CYP3A5*1 genotype, days post transplant, age, transplant at a steroid sparing centre and calcium channel blocker (CCB) use significantly influenced tacrolimus CL/F. The final model describing CL/F (l h−1) was: 38.4 ×[(0.86, if days 6–10) or (0.71, if days 11–180)]×[(1.69, if CYP3A5*1/*3 genotype) or (2.00, if CYP3A5*1/*1 genotype)]× (0.70, if receiving a transplant at a steroid sparing centre) × ([age in years/50]−0.4) × (0.94, if CCB is present). The dose to achieve the desired trough is then prospectively determined using the individuals CL/F estimate. CONCLUSIONS The CYP3A5*1 genotype and four clinical factors were important for tacrolimus CL/F. An individualized dose is easily determined from the predicted CL/F. This study is important towards individualization of dosing in the clinical setting and may increase the number of patients achieving the target concentration. This equation requires validation in an independent cohort of kidney transplant recipients.

The Scientific Registry of Transplant Recipients (SRTR) provides federally mandated program-specific transplant data to the public. Currently, there is little understanding of how different program measures are prioritized by patients in selecting a program for transplantation. This study recruited 479 transplant advocacy group members from mailing lists and social media of the National Kidney Foundation (NKF), transplant families (TF), and Transplant Recipient International Organization (TRIO). Survey participants identified how many different programs would be reasonable to consider and viewed four measures that have recently been displayed on SRTR public search result websites and six measures not recently displayed and indicated importance on a 5-point scale. Four hundred two completed the survey (TF = 26; TRIO = 34; NKF = 342). Seventy-eight percent indicated that considering more than one program would be reasonable. Linear mixed models adjusted for organization, education, and gender. Likert scores for pretransplant (transplant rate) and transplant volume measures were similar and were very or extremely important to over 80% of participants. Posttransplant (survival after transplant) was rated as 0.52 points higher, confidence interval (0.41, 0.64). Results indicate that many patient advocacy group members find a choice between two or more programs reasonable and value multiple measures when assessing programs where they may want to undergo transplantation.

BACKGROUND Suboptimal immunosuppression after kidney transplantation contributes to toxicity and loss of efficacy. Little is known regarding the impact of intra-patient variability of tacrolimus (TAC) doses and troughs in the early post-transplant period or the influence of genetic variants on variability. METHODS Coefficients of variation (CV) of TAC troughs and doses of 1226 European American (EA) and 246 African American (AA) adult recipients enrolled in DeKAF Genomics were compared for association with acute rejection and graft failure. Additionally, the influence of recipients' number of CYP3A5 loss-of-function alleles was assessed. RESULTS Acute rejection was associated with greater CV of dose in AA (P

The Organ Procurement Transplant Network (OPTN) listing criteria for simultaneous liver-kidney transplant (SLK) are not well defined. Concerns remain about rising numbers of SLKs, which divert quality kidneys from candidates awaiting kidney transplants (KT). We performed a retrospective review of liver transplants (LTs) at our center from 2004 to 2014; 127 recipients (liver transplant alone; 102 LTA, 25 SLK) were identified with short-term preoperative kidney dysfunction (creatinine >4 mg/dL or preoperative hemodialysis [HD] for

Transplant patients often seek specific data and statistics to inform medical decision making; however, for many relevant measures, patient-friendly information is not available. Development of patient-centered resources should be informed by patient needs. This study used qualitative document research methods to review 678 detailed Scientific Registry of Transplant Recipients (SRTR) entries and summary counts of 55,362 United Network for Organ Sharing (UNOS) entries to provide a better understanding of what was asked and what requests were most common. Incoming call and email logs maintained by SRTR and UNOS were reviewed for 2010–2015. Patients sought a wide range of information about outcomes, waiting times, program volumes, and willingness to perform transplants in candidates with specific diseases or demographics. Patients and members of their support networks requested explanation of complex information, such as actual versus expected outcomes, and of general transplant processes, such as registering on the waiting list or becoming a living donor. They sought transplant program data from SRTR and UNOS, but encountered gaps in the information they wanted and occasionally struggled to interpret some data. These findings were used to identify potential gaps in providing program-specific data and to enhance the SRTR website (www.srtr.org) with more patient-friendly information.