Faculty Bibliography

BACKGROUND:A number of deceased donor kidney scoring systems have been developed to predict post-transplant graft failure. However, studies comparing the predictive ability of these scoring systems to each other are lacking. METHODS:We used single-center histopathologic and UNOS data from 140 marginal deceased donor kidneys and transplant recipients to compare the predictive accuracy of the Maryland Aggregate Pathology Index (MAPI), Kidney Donor Risk Index (KDRI), Remuzzi, and Nyberg scoring systems for 2-year graft survival using time-dependent receiver operating curves and Kaplan-Meier analysis. RESULTS:MAPI had the highest predictive accuracy (area under curve [AUC] = 0.81) compared to KDRI (AUC = 0.45), Remuzzi (AUC = 0.59), and Nyberg (AUC = 0.63) for 2-year graft survival. Furthermore, when analyzing each score according to its pre-defined risk strata, MAPI was the only scoring system for which 2-year graft survival was significantly different across strata (84.3% for low risk, 56.5% for intermediate risk, and 50% for high risk, P < .001). Additionally, MAPI was the only risk score significantly associated with 2-year graft survival (hazard ratio per point: 1.12, 95% confidence interval [CI]: 1.01-1.23, P = .03). CONCLUSIONS:In a single-center cohort of biopsied marginal kidneys used for transplantation, MAPI had the best predictive ability of these four scoring systems. When biopsy data are available for kidneys considered for transplantation, the MAPI score may provide additional information that could be used to better identify kidneys likely to have longer graft survival.

BACKGROUND:Optimizing amino acid (eplet) histocompatibility at first transplant decreases the risk of de novo donor-specific antibody (dnDSA) development and may improve long-term graft survival in pediatric kidney transplant recipients (KTR). We performed a retrospective analysis of pediatric KTR and their respective donors to identify eplets most commonly associated with dnDSA formation. METHODS:Eplet mismatch analysis was performed in a cohort of 125 pediatric KTR-donor pairs (2006-2018). We determined the prevalence of each eplet mismatch and quantified the percentage of exposed patients who developed dnDSA for each mismatched eplet. RESULTS:Recipient median age was 14 (IQR 8-17) years with a racial distribution of 42% Black, 48% Caucasian, and 5.6% Middle-Eastern. Median eplet load varied significantly by recipient race, Black 82 (IQR 58-98), White 60 (IQR 44-81) and Other 66 (IQR 61-76), p = 0.002. Forty-four percent of patients developed dnDSA after median 37.1 months. Compared to dnDSA- patients, dnDSA+ patients had higher median eplet load, 64 (IQR 46-83) vs. 77 (IQR 56-98), p = 0.012. The most common target of dnDSA were eplets expressed in HLA-A*11 and A2 in Class I, and HLA-DQ6 and DQA5 in Class II. The most commonly mismatched eplets were not the most likely to result in dnDSA formation. CONCLUSIONS:In a racially diverse population, only a subset of eplets was linked to antibody formation. Eplet load alone is not a sufficient surrogate for eplet immunogenicity. These findings illustrate the need to optimize precision in donor selection and allocation to improve long-term graft outcomes. Graphical Abstract A higher resolution version of the Graphical abstract is available as Supplementary information.

BACKGROUND:Live kidney donors (LKDs) account for nearly a third of kidney transplants in the United States. While donor nephrectomy poses minimal post-surgical risk, LKDs face an elevated adjusted risk of developing chronic diseases such as hypertension, diabetes, and end-stage renal disease. Routine screening presents an opportunity for the early detection and management of chronic conditions. Transplant hospital reporting requirements mandate the submission of laboratory and clinical data at 6-months, 1-year, and 2-years after kidney donation, but less than 50% of hospitals are able to comply. Strategies to increase patient engagement in follow-up efforts while minimizing administrative burden are needed. We seek to evaluate the effectiveness of using small financial incentives to promote patient compliance with LKD follow-up. METHODS/DESIGN:We are conducting a two-arm randomized controlled trial (RCT) of patients who undergo live donor nephrectomy at The Johns Hopkins Hospital Comprehensive Transplant Center (MDJH) and the University of Maryland Medical Center Transplant Center (MDUM). Eligible donors will be recruited in-person at their first post-surgical clinic visit or over the phone. We will use block randomization to assign LKDs to the intervention ($25 gift card at each follow-up visit) or control arm (current standard of care). Follow-up compliance will be tracked over time. The primary outcome will be complete (all components addressed) and timely (60 days before or after expected visit date), submission of LKD follow-up data at required 6-month, 1-year, and 2-year time points. The secondary outcome will be transplant hospital-level compliance with federal reporting requirements at each visit. Rates will be compared between the two arms following the intention-to-treat principle. DISCUSSION:Small financial incentivization might increase patient compliance in the context of LKD follow-up, without placing undue administrative burden on transplant providers. The findings of this RCT will inform potential center- and national-level initiatives to provide all LKDs with small financial incentives to promote engagement with post-donation monitoring efforts. TRIAL REGISTRATION:ClinicalTrials.gov number: NCT03090646 Date of registration: March 2, 2017 Sponsors: Johns Hopkins University, University of Maryland Medical Center Funding: The Living Legacy Foundation of Maryland.

An increasing number of studies claim machine learning (ML) predicts transplant outcomes more accurately. However, these claims were possibly confounded by other factors, namely, supplying new variables to ML models. To better understand the prospects of ML in transplantation, we compared ML to conventional regression in a "common" analytic task: predicting kidney transplant outcomes using national registry data. We studied 133 431 adult deceased-donor kidney transplant recipients between 2005 and 2017. Transplant centers were randomly divided into 70% training set (190 centers/97 787 recipients) and 30% validation set (82 centers/35 644 recipients). Using the training set, we performed regression and ML procedures [gradient boosting (GB) and random forests (RF)] to predict delayed graft function, one-year acute rejection, death-censored graft failure C, all-cause graft failure, and death. Their performances were compared on the validation set using -statistics. In predicting rejection, regression (C = _0.601 0.611_0.621 ) actually outperformed GB (C = _0.581 0.591_0.601 ) and RF (C = _0.569 0.579_0.589 ). For all other outcomes, the C-statistics were nearly identical across methods (delayed graft function, 0.717-0.723; death-censored graft failure, 0.637-0.642; all-cause graft failure, 0.633-0.635; and death, 0.705-0.708). Given its shortcomings in model interpretability and hypothesis testing, ML is advantageous only when it clearly outperforms conventional regression; in the case of transplant outcomes prediction, ML seems more hype than helpful.

In March 2020, COVID-19 infections began to rise exponentially in the United States, placing substantial burden on the healthcare system. As a result, there was a rapid change in transplant practices and policies, with cessation of most procedures. Our goal was to understand changes to pediatric kidney transplantation (KT) at the national level during the COVID-19 epidemic. Using SRTR data, we examined changes in pediatric waitlist registration, waitlist removal or inactivation, and deceased donor and living donor (DDKT/LDKT) events during the start of the disease transmission in the United States compared to the same time the previous year. We saw an initial decrease in DDKT and LDKT by 47% and 82% compared to expected events and then a continual increase, with numbers reaching expected pre-pandemic levels by May 2020. In the early phase of the pandemic, waitlist inactivation and removals due to death or deteriorating condition rose above expected values by 152% and 189%, respectively. There was a statistically significant decrease in new waitlist additions (IRR _0.49 0.65 _0.85 ) and LDKT (IRR _0.17 0.38 _0.84 ) _{in states with high vs low COVID activity. Transplant recipients during the pandemic were more likely to have received a DDKT, but had similar cPRA, waitlist time and cause of ESRD as before the pandemic. The COVID-19 pandemic initially reduced access to kidney transplantation among pediatric patients in the United States, but has not had a sustained effect.}