In 2013, the Organ Procurement and Transplantation Network in the United States approved a new national deceased donor kidney allocation policy that introduces the kidney donor profile index (KDPI), which gives scores of 0%-100% based on 10 donor factors. Kidneys with lower KDPI scores are associated with better post-transplant survival. Important features of the new policy include first allocating kidneys from donors with a KDPI#20% to candidates in the top 20th percentile of estimated post-transplant survival, adding waiting time from dialysis initiation, conferring priority points for a calculated panelreactive antibody (CPRA).19%, broader sharing of kidneys for candidates with a CPRA$99%, broader sharing of kidneys from donors with a KDPI.85%, eliminating the payback system, and allocating blood type A2 and A2B kidneys to blood type B candidates. We simulated the distribution of kidneys under the new policy compared with the current allocation policy. The simulation showed increases in projected median allograft years of life with the new policy (9.07 years) compared with the current policy (8.82 years). With the new policy, candidates with a CPRA.20%, with blood type B, and aged 18-49 years were more likely to undergo transplant, but transplants declined in candidates aged 50-64 years (4.1% decline) and $65 years (2.7% decline). These simulations demonstrate that the new deceased donor kidney allocation policy may improve overall post-transplant survival and access for highly sensitized candidates, with minimal effects on access to transplant by race/ethnicity and declines in kidney allocation for candidates aged $50 years.

Background and objectives There is a shortage of kidneys for transplant, and many patients on the deceased donor kidney transplant waiting list would likely benefit from kidneys that are currently being discarded. In the United States, the most common reason given for discarding kidneys retrieved for transplant is procurement biopsy results. This study aimed to compare biopsy results from discarded kidneys with discard attributed to biopsy findings, with biopsy results from comparable kidneys that were successfully transplanted.Design, setting, participants, & measurements In this retrospective, observational, case-control study, biopsy reports were examined from 83 kidneys discarded in 2010 due to biopsy findings (cases), 83 contralateral transplanted kidneys from the same donor (contralateral controls), and 83 deceased donors randomly matched to cases by donor risk profile (randomly matched controls). A second procurement biopsy was obtained in 64 of 332 kidneys (19.3%).Results The quality of biopsy reports was low, with amounts of tubular atrophy, interstitial inflammation, arteriolar hyalinosis, and acute tubular necrosis often not indicated; 69% were wedge biopsies and 94% used frozen tissue. The correlation between first and second procurement biopsies was poor; only 25% of the variability (R 2 ) in glomerulosclerosis was explained by biopsies being from the same kidney. The percentages of glomerulosclerosis overlapped substantially between cases, contralateral controls, and randomly matched controls: 17.1%615.3%, 9.0%66.6%, and 5.0%65.9%, respectively. Of all biopsy findings, only glomerulosclerosis.20% was independently correlated with discard (cases versus contralateral controls; odds ratio, 15.09; 95% confidence interval, 2.47 to 92.41; P=0.003), suggesting that only this biopsy result was used in acceptance decisions. One-year graft survival was 79.5% and 90.7% in contralateral and randomly matched controls, respectively, versus 91.6% among all deceased donor transplants in the Scientific Registry of Transplant Recipients.Conclusions Routine use of biopsies could lead to unnecessary kidney discards.

Public reports of organ transplant program outcomes by the US Scientific Registry of Transplant Recipients have been both groundbreaking and controversial. The reports are used by regulatory agencies, private insurance providers, transplant centers and patients. Failure to adequately adjust outcomes for risk may cause programs to avoid performing transplants involving suitable but high-risk candidates and donors. At a consensus conference of stakeholders held February 13-15, 2012, the participants recommended that program-specific reports be better designed to address the needs of all users. Additional comorbidity variables should be collected, but innovation should also be protected by excluding patients who are in approved protocols from statistical models that identify underperforming centers. The potential benefits of hierarchical and mixed-effects statistical methods should be studied. Transplant centers should be provided with tools to facilitate quality assessment and performance improvement. Additional statistical methods to assess outcomes at small-volume transplant programs should be developed. More data on waiting list risk and outcomes should be provided. Monitoring and reporting of short-term living donor outcomes should be enhanced. Overall, there was broad consensus that substantial improvement in reporting outcomes of transplant programs in the United States could and should be made in a cost-effective manner.

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, 2.343.324.71; PELD/MELD scores 33‐36, 1.702.513.71). 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, 2.773.955.63; top 5 offers, 3.904.394.95; top 10 offers, 4.855.305.80). Candidates with exceptions had lower offer rates than candidates without exceptions for offers in the top 5 (ORR: hepatocellular carcinoma [HCC], 0.680.770.88; non‐HCC, 0.730.810.89) and top 10 (ORR: HCC, 0.590.650.71; non‐HCC, 0.690.750.81). 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.

Few equations have been developed to predict endstage renal disease (ESRD) after deceased donor liver transplant. This retrospective observational cohort study analyzed all adult deceased donor liver transplant recipients in the Scientific Registry of Transplant Recipients (SRTR) database, 1995-2010. The prediction equation for ESRD was developed using candidate predictor variables available in SRTR after implementation of the allocation policy based on the model for end-stage liver disease. ESRD was defined as initiation of maintenance dialysis therapy, kidney transplant or registration on the kidney transplant waiting list. We used Cox proportional hazard models to develop separate equations for assessing risk of ESRD by 6 months posttransplant and between 6 months and 5 years posttransplant. Variables in the 6-month equation included recipient age, history of diabetes, history of dialysis before liver transplant, history of malignancy, body mass index, serum creatinine and liver donor risk index. Variables in the 6-month to 5-year equation included recipient race, history of diabetes, hepatitis C status, serum albumin, serum bilirubin and serum creatinine. The prediction equations have good calibration and discrimination (C statistics 0.74-0.78). We have produced risk prediction equations that can be used to aid in understanding the risk of ESRD after liver transplant.