Integrative multi-omics profiling in human decedents receiving pig heart xenografts

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

Long-Term Outcomes after Conversion to a Belatacept-Based Immunosuppression in Kidney Transplant Recipients

BACKGROUND

Conversion to a belatacept-based immunosuppression is currently used as a calcineurin inhibitor (CNI) avoidance strategy when the CNI-based standard-of-care immunosuppression is not tolerated after kidney transplantation. However, there is a lack of evidence on the long-term benefit and safety after conversion to belatacept.

METHODS

We prospectively enrolled 311 kidney transplant recipients from 2007 to 2020 from two referral centers, converted from CNI to belatacept after transplant according to a prespecified protocol. Patients were matched at the time of conversion to patients maintained with CNIs, using optimal matching. The primary end point was death-censored allograft survival at 7 years. The secondary end points were patient survival, eGFR, and safety outcomes, including serious viral infections, immune-related complications, antibody-mediated rejection, T-cell-mediated rejection, de novo anti-HLA donor-specific antibody, de novo diabetes, cardiovascular events, and oncologic complications.

RESULTS

A total of 243 patients converted to belatacept (belatacept group) were matched to 243 patients maintained on CNIs (CNI control group). All recipient, transplant, functional, histologic, and immunologic parameters were well balanced between the two groups with a standardized mean difference below 0.05. At 7 years post-conversion to belatacept, allograft survival was 78% compared with 63% in the CNI control group ( P < 0.001 for log-rank test). The safety outcomes showed a similar rate of patient death (28% in the belatacept group versus 36% in the CNI control group), active antibody-mediated rejection (6% versus 7%), T-cell-mediated rejection (4% versus 4%), major adverse cardiovascular events, and cancer occurrence (9% versus 11%). A significantly higher rate of de novo proteinuria was observed in the belatacept group as compared with the CNI control group (37% versus 21%, P < 0.001).

CONCLUSIONS

This real-world evidence study shows that conversion to belatacept post-transplant was associated with lower risk of graft failure and acceptable safety outcomes compared with patients maintained on CNIs.

CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER

Long-term Outcomes after Conversion to Belatacept, NCT04733131 .

High-dimensional mass cytometry identified circulating natural killer T-cell subsets associated with protection from cytomegalovirus infection in kidney transplant recipients

Cytomegalovirus (CMV) infection is associated with poor kidney transplant outcomes. While innate and adaptive immune cells have been implicated in its prevention, an in-depth characterization of the in vivo kinetics of multiple cell subsets and their role in protecting against CMV infection has not been achieved. Here, we performed high-dimensional immune phenotyping by mass cytometry, and functional assays, on 112 serially collected samples from CMV seropositive kidney transplant recipients. Advanced unsupervised deep learning analysis was used to assess immune cell populations that significantly correlated with prevention against CMV infection and anti-viral immune function. Prior to infection, kidney transplant recipients who developed CMV infection showed significantly lower CMV-specific cell-mediated immune (CMI) frequencies than those that did not. A broad diversity of circulating cell subsets within innate and adaptive immune compartments were associated with CMV infection or protective CMV-specific CMI. While percentages of CMV (tetramer-stained)-specific T cells associated with high CMI responses and clinical protection, circulating CD3+CD8midCD56+ NK-T cells overall strongly associated with low CMI and subsequent infection. However, three NK-T cell subsets sharing the CD11b surface marker associated with CMV protection and correlated with strong anti-viral CMI frequencies in vitro. These data were validated in two external independent cohorts of kidney transplant recipients. Thus, we newly describe the kinetics of a novel NK-T cell subset that may have a protective role in post-transplantation CMV infection. Our findings pave the way to more mechanistic studies aimed at understanding the function of these cells in protection against CMV infection.

Comparing the prognostic performance of iBOX and biopsy-proven acute rejection for long-term kidney graft survival

Biopsy-proven acute rejection (BPAR) occurs in approximately 10% of kidney transplant recipients in the first year, making superiority trials unfeasible. iBOX, a quantitative composite of estimated glomerular filtration rate, proteinuria, antihuman leukocyte antigen donor-specific antibody, and + full/- abbreviated kidney histopathology, is a new proposed surrogate endpoint. BPAR's prognostic ability was compared with iBOX in a pooled cohort of 1534 kidney transplant recipients from 4 data sets, including 2 prospective randomized controlled trials. Discrimination analyses showed mean c-statistic differences between both iBOX compared with BPAR of 0.25 (95% confidence interval: 0.17-0.32) for full iBOX and 0.24 (95% confidence interval: 0.16-0.32) for abbreviated iBOX, indicating statistically significantly higher c-statistic values for the iBOX prognosis of death-censored graft survival. Mean (± standard error) c-statistics were 0.81 ± 0.03 for full iBOX, 0.80 ± 0.03 for abbreviated iBOX, and 0.57 ± 0.03 for BPAR. In calibration analyses, predicted graft loss events from both iBOX models were not significantly different from those observed. However, for BPAR, the predicted events were significantly (P < .01) different (observed: 64; predicted: 70; full iBOX: 76; abbreviated iBOX: 173 BPAR). IBOX at 1-year posttransplant is superior to BPAR in the first year posttransplant in graft loss prognostic performance, providing valuable additional information and facilitating the demonstration of superiority of novel immunosuppressive regimens.

Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection

There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.

Report of the 2022 Banff Heart Concurrent: Focus on non-human leukocyte antigen antibodies in rejection and the pathology of "mixed" rejection

The Banff Heart Concurrent Session, held as part of the 16th Banff Foundation for Allograft Pathology Conference at Banff, Alberta, Canada, on September 21, 2022, focused on 2 major topics: non-human leukocyte antigen (HLA) antibodies and mixed rejection. Each topic was addressed in a multidisciplinary fashion with clinical, immunological, and pathology perspectives and future developments and prospectives. Following the Banff organization model and principles, the collective aim of the speakers on each topic was to • Determine current knowledge gaps in heart transplant pathology • Identify limitations of current pathology classification systems • Discuss next steps in addressing gaps and refining classification system.

Long-term Kidney Transplant Survival Across the Globe

BACKGROUND

The outcomes after kidney transplantation (KT), including access, wait time, and other issues around the globe, have been studied. However, issues do vary from one country to another.

METHODS

We obtained data from several countries from North America, South America, Europe, Asia, and Australia, including the number of patients awaiting KT from 2015, transplant rate per million population (pmp), proportion of living donor and deceased donor (LD/DD) KT, and posttransplant survival. We also sought opinions on key difficulties faced by each of these countries with respect to KT and long-term survival.

RESULTS

Variation in access to KT across the globe was noted. Countries with the highest rates of KT pmp included the United States (79%) and Spain (71%). A higher proportion of LD transplants was noted in Japan (93%), India (85%), Singapore (63%), and South Korea (63%). A higher proportion of DD KTs was noted in Spain (90%), Brazil (90%), France (85%), Italy (85%), Finland (85%), Australia-New Zealand (80%), and the United States (77%). The 5-y graft survival for LD was highest in South Korea (95%), Singapore (94%), Italy (93%), Finland (93%), and Japan (93%), whereas for DD, it was South Korea (93%), Italy (88%), Japan (86%), and Singapore (86%). The common issues surrounding KTs are access and a limited number of LDs and DDs. Key issues identified for long-term survival were increasing age of donors and recipients, higher recipient comorbidity, and posttransplant events, such as alloimmune injury to the kidney, infection, cancer, and suboptimal adherence to therapy.

CONCLUSIONS

A unified approach is necessary to improve issues surrounding KT as the demand continues to increase.

The Banff 2022 Kidney Meeting Report: Reappraisal of microvascular inflammation and the role of biopsy-based transcript diagnostics

The XVI-th Banff Meeting for Allograft Pathology was held at Banff, Alberta, Canada, from 19th to 23rd September 2022, as a joint meeting with the Canadian Society of Transplantation. To mark the 30th anniversary of the first Banff Classification, premeeting discussions were held on the past, present, and future of the Banff Classification. This report is a summary of the meeting highlights that were most important in terms of their effect on the Classification, including discussions around microvascular inflammation and biopsy-based transcript analysis for diagnosis. In a postmeeting survey, agreement was reached on the delineation of the following phenotypes: (1) "Probable antibody-mediated rejection (AMR)," which represents donor-specific antibodies (DSA)-positive cases with some histologic features of AMR but below current thresholds for a definitive AMR diagnosis; and (2) "Microvascular inflammation, DSA-negative and C4d-negative," a phenotype of unclear cause requiring further study, which represents cases with microvascular inflammation not explained by DSA. Although biopsy-based transcript diagnostics are considered promising and remain an integral part of the Banff Classification (limited to diagnosis of AMR), further work needs to be done to agree on the exact classifiers, thresholds, and clinical context of use.

The Banff 2022 Kidney Meeting Work Plan: Data-driven refinement of the Banff Classification for renal allografts

The XVIth Banff Meeting for Allograft Pathology was held in Banff, Alberta, Canada, from September 19 to 23, 2022, as a joint meeting with the Canadian Society of Transplantation. In addition to a key focus on the impact of microvascular inflammation and biopsy-based transcript analysis on the Banff Classification, further sessions were devoted to other aspects of kidney transplant pathology, in particular T cell-mediated rejection, activity and chronicity indices, digital pathology, xenotransplantation, clinical trials, and surrogate endpoints. Although the output of these sessions has not led to any changes in the classification, the key role of Banff Working Groups in phrasing unanswered questions, and coordinating and disseminating results of investigations addressing these unanswered questions was emphasized. This paper summarizes the key Banff Meeting 2022 sessions not covered in the Banff Kidney Meeting 2022 Report paper and also provides an update on other Banff Working Group activities relevant to kidney allografts.

Prognostic Biomarkers in Kidney Transplantation: A Systematic Review and Critical Appraisal

SIGNIFICANCE STATEMENT

Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice.

BACKGROUND

Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon.

METHODS

We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators.

RESULTS

A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8-35.5) between 2005 and 2012 and 57.5 (IQR, 53.3-59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96-629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0-6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies.

CONCLUSIONS

Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients

In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.

Identification of liver transplant biopsy phenotypes associated with distinct liver biological markers and allograft survival

The intricate association between histologic lesions and circulating antihuman leucocyte antigen donor-specific antibodies (DSA) in liver transplantation (LT) requires further clarification. We conducted a probabilistic, unsupervised approach in a comprehensively well-annotated LT cohort to identify clinically relevant archetypes. We evaluated 490 pairs of LT biopsies with DSA testing from 325 recipients transplanted between 2010 and 2020 across 3 French centers and an external cohort of 202 biopsies from 128 recipients. Unsupervised archetypal analysis integrated all clinico-immuno-histologic parameters of each biopsy to identify biopsy archetypes. The median time after LT was 1.17 (interquartile range, 0.38-2.38) years. We identified 7 archetypes distinguished by clinico-immuno-histologic parameters: archetype #1: severe T cell-mediated rejection (15.9%); #2: chronic rejection with ductopenia (1.8%); #3: architectural and microvascular damages (3.5%); #4: (sub)normal (55.9%); #5: mild T cell-mediated rejection (4.9%); #6: acute antibody-mediated rejection (6.5%); and #7: chronic rejection with DSA (11.4%). Cell infiltrates vary in the archetype. These archetypes were associated with distinct liver biological markers and allograft outcomes. These findings remained consistent when stratified using the patient's age or indications for LT, with good performance in the external cohort (mean highest probability assignment = 0.58, standard deviation ± 0.17). In conclusion, we have identified clinically meaningful archetypes, providing valuable insights into the intricate DSA-histology association, which may help standardize liver allograft pathology classification.

Challenges in the management of the kidney allograft: from decline to failure: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

In March 2022, Kidney Disease: Improving Global Outcomes (KDIGO) held a virtual Controversies Conference to address the important but rarely examined phase during which the kidney transplant is failing or has failed. In addition to discussing the definition of a failing allograft, 4 broad areas were considered in the context of a declining functioning graft: prognosis and kidney failure trajectory; immunosuppression strategies; management of medical and psychological complications, and patient factors; and choice of kidney replacement therapy or supportive care following graft loss. Identifying and paying special attention to individuals with failing allografts was felt to be important in order to prepare patients psychologically, manage immunosuppression, address complications, prepare for dialysis and/or retransplantation, and transition to supportive care. Accurate prognostication tools, although not yet widely available, were embraced as necessary to define allograft survival trajectories and the likelihood of allograft failure. The decision of whether to withdraw or continue immunosuppression after allograft failure was deemed to be based most appropriately on risk-benefit analysis and likelihood of retransplantation within a few months. Psychological preparation and support was identified as a critical factor in patient adjustment to graft failure, as was early communication. Several models of care were noted that enabled a medically supportive transition back to dialysis or retransplantation. Emphasis was placed on the importance of dialysis-access readiness before initiation of dialysis, in order to avoid use of central venous catheters. The centrality of the patient to all management decisions and discussions was deemed to be paramount. Patient "activation," which can be defined as engaged agency, was seen as the most effective way to achieve success. Unresolved controversies, gaps in knowledge, and areas for research were also stressed in the conference deliberations.

Validation of the clinical utility of microRNA as noninvasive biomarkers of cardiac allograft rejection: A prospective longitudinal multicenter study

While studies have shown an association between microRNAs and cardiac rejection, the clinical relevance of a preidentified miRNA signature as a noninvasive biomarker has never been assessed in prospective multicentric unselected cohorts. To address this unmet need, we designed a prospective study (NCT02672683) including recipients from 11 centers between August 2016 to March 2018. The objective was to validate the association between 3 previously identified circulating microRNA (10a, 92a, 155) and the histopathological diagnosis of rejection. Both relative and absolute (sensitivity analysis) quantifications of microRNAs were performed. Overall, 461 patients were included (831 biopsies, 79 rejections). A per-protocol interim analysis (258 biopsies, 49 rejections) did not find any association between microRNA and rejection (microRNA 10a: odds ratio (OR) = 1.05, 95% confidence intervals (CI) = 0.87-1.27, p = 0.61; 92a: OR = 0.98, 95%CI = 0.87-1.10, p = 0.68; 155: OR = 0.91, 95%CI = 0.76-1.10, p = 0.33). These results were confirmed in the sensitivity analysis. The analysis of the remaining sera was stopped for futility. This study shows no clinical utility of circulating microRNAs 10a, 92a, and 155 monitoring in heart allograft recipients.

Banff Digital Pathology Working Group: Image Bank, Artificial Intelligence Algorithm, and Challenge Trial Developments

The Banff Digital Pathology Working Group (DPWG) was established with the goal to establish a digital pathology repository; develop, validate, and share models for image analysis; and foster collaborations using regular videoconferencing. During the calls, a variety of artificial intelligence (AI)-based support systems for transplantation pathology were presented. Potential collaborations in a competition/trial on AI applied to kidney transplant specimens, including the DIAGGRAFT challenge (staining of biopsies at multiple institutions, pathologists' visual assessment, and development and validation of new and pre-existing Banff scoring algorithms), were also discussed. To determine the next steps, a survey was conducted, primarily focusing on the feasibility of establishing a digital pathology repository and identifying potential hosts. Sixteen of the 35 respondents (46%) had access to a server hosting a digital pathology repository, with 2 respondents that could serve as a potential host at no cost to the DPWG. The 16 digital pathology repositories collected specimens from various organs, with the largest constituent being kidney (n = 12,870 specimens). A DPWG pilot digital pathology repository was established, and there are plans for a competition/trial with the DIAGGRAFT project. Utilizing existing resources and previously established models, the Banff DPWG is establishing new resources for the Banff community.

Complement-activating donor-specific anti-HLA antibodies in solid organ transplantation: systematic review, meta-analysis, and critical appraisal

Introduction

Several studies have investigated the impact of circulating complement-activating anti-human leukocyte antigen donor-specific antibodies (anti-HLA DSAs) on organ transplant outcomes. However, a critical appraisal of these studies and a demonstration of the prognostic value of complement-activating status over anti-HLA DSA mean fluorescence intensity (MFI) level are lacking.

Methods

We conducted a systematic review, meta-analysis and critical appraisal evaluating the role of complement-activating anti-HLA DSAs on allograft outcomes in different solid organ transplants. We included studies through Medline, Cochrane, Scopus, and Embase since inception of databases till May 05, 2023. We evaluated allograft loss as the primary outcome, and allograft rejection as the secondary outcome. We used the Newcastle-Ottawa Scale and funnel plots to assess risk of bias and used bias adjustment methods when appropriate. We performed multiple subgroup analyses to account for sources of heterogeneity and studied the added value of complement assays over anti-HLA DSA MFI level.

Results

In total, 52 studies were included in the final meta-analysis (11,035 patients). Complement-activating anti-HLA DSAs were associated with an increased risk of allograft loss (HR 2.77; 95% CI 2.33-3.29, p<0.001; I²=46.2%), and allograft rejection (HR 4.98; 95% CI 2.96-8.36, p<0.01; I²=70.9%). These results remained significant after adjustment for potential sources of bias and across multiple subgroup analyses. After adjusting on pan-IgG anti-HLA DSA defined by the MFI levels, complement-activating anti-HLA DSAs were significantly and independently associated with an increased risk of allograft loss.

Discussion

We demonstrated in this systematic review, meta-analysis and critical appraisal the significant deleterious impact and the independent prognostic value of circulating complement-activating anti-HLA DSAs on solid organ transplant risk of allograft loss and rejection.

Intermediate-term outcomes of complement inhibition for prevention of antibody-mediated rejection in immunologically high-risk heart allograft recipients

Allosensitization represents a major barrier to heart transplantation. We previously reported favorable 1-year outcomes of complement inhibition at transplant in highly sensitized recipients. We now report a longer follow-up. In this single-arm trial (NCT02013037), 20 patients with panel reactive antibodies ≥70% and preformed donor-specific antibodies received eculizumab during the first 2 months post-transplant. The primary end-point was antibody-mediated rejection ≥ pAMR2 and/or left ventricular dysfunction. The median follow-up was 4.8 years. Beyond the first year post-transplant, there were no episodes of pAMR2 or greater and no Left Ventricular (LV) dysfunction. There were 3 deaths, 1 episode of pAMR1, and 1 patient with minimal de novo cardiac allograft vasculopathy. Compared to a matched control group, we observed a nonstatistically significant benefit of eculizumab with a lower incidence of the primary end-point or death (primary end-point: hazard ratio = 0.50, 95% confidence interval = 0.15-1.67, and p = 0.26; mortality: hazard ratio = 0.51, 95% confidence interval = 0.13-2.07, and p = 0.35). Our results support the utility of complement inhibition for high-immunological-risk recipients. CLINICAL TRIAL REGISTRATION: ClinincalTrials.gov, NCT02013037. https://clinicaltrials.gov/ct2/show/NCT02013037?term=eculizumab&cond=heart+transplantation&draw=2&rank=1.

Validation of a prediction system for risk of kidney allograft failure in pediatric kidney transplant recipients: An international observational study

Predicting long-term kidney allograft failure is an unmet need for clinical care and clinical trial optimization in children. We aimed to validate a kidney allograft failure risk prediction system in a large international cohort of pediatric kidney transplant recipients. Patients from 20 centers in Europe and the United States, transplanted between 2004 and 2017, were included. Allograft assessment included estimated glomerular filtration rate, urine protein-to-creatinine ratio, circulating antihuman leukocyte antigen donor-specific antibody, and kidney allograft histology. Individual predictions of allograft failure were calculated using the integrative box (iBox) system. Prediction performances were assessed using discrimination and calibration. The allograft evaluations were performed in 706 kidney transplant recipients at a median time of 9.1 (interquartile range, 3.3-19.2) months posttransplant; mean estimated glomerular filtration rate was 68.7 ± 28.1 mL/min/1.73 m2, and median urine protein-to-creatinine ratio was 0.1 (0.0-0.4) g/g, and 134 (19.0%) patients had antihuman leukocyte antigen donor-specific antibodies. The iBox exhibited accurate calibration and discrimination for predicting the outcomes up to 10 years after evaluation, with a C-index of 0.81 (95% confidence interval, 0.75-0.87). This study confirms the generalizability of the iBox to predict long-term kidney allograft failure in children, with performances similar to those reported in adults. These results support the use of the iBox to improve patient monitoring and facilitate clinical trials in children.

Qualifying a novel clinical trial endpoint (iBOX) predictive of long-term kidney transplant outcomes

New immunosuppressive therapies that improve long-term graft survival are needed in kidney transplant. Critical Path Institute's Transplant Therapeutics Consortium received a qualification opinion for the iBOX Scoring System as a novel secondary efficacy endpoint for kidney transplant clinical trials through European Medicines Agency's qualification of novel methodologies for drug development. This is the first qualified endpoint for any transplant indication and is now available for use in kidney transplant clinical trials. Although the current efficacy failure endpoint has typically shown the noninferiority of therapeutic regimens, the iBOX Scoring System can be used to demonstrate the superiority of a new immunosuppressive therapy compared to the standard of care from 6 months to 24 months posttransplant in pivotal or exploratory drug therapeutic studies.

Immune response after pig-to-human kidney xenotransplantation: a multimodal phenotyping study

BACKGROUND

Cross-species immunological incompatibilities have hampered pig-to-human xenotransplantation, but porcine genome engineering recently enabled the first successful experiments. However, little is known about the immune response after the transplantation of pig kidneys to human recipients. We aimed to precisely characterise the early immune responses to the xenotransplantation using a multimodal deep phenotyping approach.

METHODS

We did a complete phenotyping of two pig kidney xenografts transplanted to decedent humans. We used a multimodal strategy combining morphological evaluation, immunophenotyping (IgM, IgG, C4d, CD68, CD15, NKp46, CD3, CD20, and von Willebrand factor), gene expression profiling, and whole-transcriptome digital spatial profiling and cell deconvolution. Xenografts before implantation, wild-type pig kidney autografts, as well as wild-type, non-transplanted pig kidneys with and without ischaemia-reperfusion were used as controls.

FINDINGS

The data collected from xenografts suggested early signs of antibody-mediated rejection, characterised by microvascular inflammation with immune deposits, endothelial cell activation, and positive xenoreactive crossmatches. Capillary inflammation was mainly composed of intravascular CD68+ and CD15+ innate immune cells, as well as NKp46+ cells. Both xenografts showed increased expression of genes biologically related to a humoral response, including monocyte and macrophage activation, natural killer cell burden, endothelial activation, complement activation, and T-cell development. Whole-transcriptome digital spatial profiling showed that antibody-mediated injury was mainly located in the glomeruli of the xenografts, with significant enrichment of transcripts associated with monocytes, macrophages, neutrophils, and natural killer cells. This phenotype was not observed in control pig kidney autografts or in ischaemia-reperfusion models.

INTERPRETATION

Despite favourable short-term outcomes and absence of hyperacute injuries, our findings suggest that antibody-mediated rejection in pig-to-human kidney xenografts might be occurring. Our results suggest specific therapeutic targets towards the humoral arm of rejection to improve xenotransplantation results.

FUNDING

OrganX and MSD Avenir.

Qualifying a Novel Clinical Trial Endpoint (iBOX) Predictive of Long-Term Kidney Transplant Outcomes

New immunosuppressive therapies that improve long-term graft survival are needed in kidney transplant. Critical Path Institute's Transplant Therapeutics Consortium received a qualification opinion for the iBOX Scoring System as a novel secondary efficacy endpoint for kidney transplant clinical trials through European Medicines Agency's qualification of novel methodologies for drug development. This is the first qualified endpoint for any transplant indication and is now available for use in kidney transplant clinical trials. Although the current efficacy failure endpoint has typically shown the noninferiority of therapeutic regimens, the iBOX Scoring System can be used to demonstrate the superiority of a new immunosuppressive therapy compared to the standard of care from 6 months to 24 months posttransplant in pivotal or exploratory drug therapeutic studies.

Banff Human Organ Transplant Consensus Gene Panel for the Detection of Antibody Mediated Rejection in Heart Allograft Biopsies

The molecular refinement of the diagnosis of heart allograft rejection based on whole-transcriptome analyses faces several hurdles that greatly limit its widespread clinical application. The targeted Banff Human Organ Transplant gene panel (B-HOT, including 770 genes of interest) has been developed to facilitate reproducible and cost-effective gene expression analysis of solid organ allografts. We aimed to determine in silico the ability of this targeted panel to capture the antibody-mediated rejection (AMR) molecular profile using whole-transcriptome data from 137 heart allograft biopsies (71 biopsies reflecting the entire landscape of histologic AMR, 66 non-AMR control biopsies including cellular rejection and non-rejection cases). Differential gene expression, pathway and network analyses demonstrated that the B-HOT panel captured biologically and clinically relevant genes (IFNG-inducible, NK-cells, injury, monocytes-macrophage, B-cell-related genes), pathways (interleukin and interferon signaling, neutrophil degranulation, immunoregulatory interactions, endothelial activation) and networks reflecting the pathophysiological mechanisms underlying the AMR process previously identified in whole-transcriptome analysis. Our findings support the potential clinical use of the B-HOT-gene panel as a reliable proxy to whole-transcriptome analysis for the gene expression profiling of cardiac allograft rejection.

Excess mortality after kidney transplantation: does sex matter?

Understanding sex differences in graft outcomes within the course of kidney transplantation is needed to unravel factors leading to the observed disparities and further improve patient management. In this issue, Vinson et al. presented a relative survival analysis comparing the excess risk of mortality in female and male recipients after kidney transplantation. This commentary discusses the major findings but also the challenges of the use of registry data to conduct large-scale analyses.

Race-free estimated glomerular filtration rate equation in kidney transplant recipients: development and validation study

OBJECTIVE

To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients.

DESIGN

Development and validation study SETTING: 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials).

PARTICIPANTS

15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021.

MAIN OUTCOME MEASURE

The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation.

RESULTS

The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient's creatinine level, age, and sex (https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/).

CONCLUSION

A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05229939.

Sudden cardiac death after heart transplantation: a population-based study

AIMS

The epidemiology of sudden cardiac death (SCD) after heart transplantation (HTx) remains imprecisely described. We aimed to assess the incidence and determinants of SCD in a large cohort of HTx recipients, compared with the general population.

METHODS AND RESULTS

Consecutive HTx recipients (n = 1246, 2 centres) transplanted between 2004 and 2016 were included. We prospectively assessed clinical, biological, pathologic, and functional parameters. SCD was centrally adjudicated. We compared the SCD incidence beyond the first year post-transplant in this cohort with that observed in the general population of the same geographic area (registry carried out by the same group of investigators; n = 19 706 SCD). We performed a competing risk multivariate Cox model to identify variables associated with SCD. The annual incidence of SCD was 12.5 per 1,000 person-years [95% confidence interval (CI), 9.7-15.9] in the HTx recipients cohort compared with 0.54 per 1,000 person-years (95% CI, 0.53-0.55) in the general population (P < 0.001). The risk of SCD was markedly elevated among the youngest HTx recipients with standardized mortality ratios for SCD up to 837 for recipients ≤30 years. Beyond the first year, SCD was the leading cause of death. Five variables were independently associated with SCD: older donor age (P = 0.003), younger recipient age (P = 0.001) and ethnicity (P = 0.034), pre-existing donor-specific antibodies (P = 0.009), and last left ventricular ejection fraction (P = 0.048).

CONCLUSION

HTx recipients, particularly the youngest, were at very high risk of SCD compared with the general population. The consideration of specific risk factors may help identify high-risk subgroups.

Machine learning does not outperform traditional statistical modelling for kidney allograft failure prediction

Machine learning (ML) models have recently shown potential for predicting kidney allograft outcomes. However, their ability to outperform traditional approaches remains poorly investigated. Therefore, using large cohorts of kidney transplant recipients from 14 centers worldwide, we developed ML-based prediction models for kidney allograft survival and compared their prediction performances to those achieved by a validated Cox-Based Prognostication System (CBPS). In a French derivation cohort of 4000 patients, candidate determinants of allograft failure including donor, recipient and transplant-related parameters were used as predictors to develop tree-based models (RSF, RSF-ERT, CIF), Support Vector Machine models (LK-SVM, AK-SVM) and a gradient boosting model (XGBoost). Models were externally validated with cohorts of 2214 patients from Europe, 1537 from North America, and 671 from South America. Among these 8422 kidney transplant recipients, 1081 (12.84%) lost their grafts after a median post-transplant follow-up time of 6.25 years (Inter Quartile Range 4.33-8.73). At seven years post-risk evaluation, the ML models achieved a C-index of 0.788 (95% bootstrap percentile confidence interval 0.736-0.833), 0.779 (0.724-0.825), 0.786 (0.735-0.832), 0.527 (0.456-0.602), 0.704 (0.648-0.759) and 0.767 (0.711-0.815) for RSF, RSF-ERT, CIF, LK-SVM, AK-SVM and XGBoost respectively, compared with 0.808 (0.792-0.829) for the CBPS. In validation cohorts, ML models' discrimination performances were in a similar range of those of the CBPS. Calibrations of the ML models were similar or less accurate than those of the CBPS. Thus, when using a transparent methodological pipeline in validated international cohorts, ML models, despite overall good performances, do not outperform a traditional CBPS in predicting kidney allograft failure. Hence, our current study supports the continued use of traditional statistical approaches for kidney graft prognostication.

An automated histological classification system for precision diagnostics of kidney allografts

For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnoses.ClinicalTrials.gov registration: NCT05306795 .

Quantitative scoring of progression in transplant glomerulopathy using digital pathology may be superior to Banff cg scoring

Antibody-mediated rejection (ABMR) is a major cause of kidney allograft failure. Biopsy-based surrogate endpoints reflecting ABMR progression on sequential biopsies that predict long-term outcome offer the potential to make treatment trials for ABMR feasible. However, the Banff transplant glomerulopathy (TG) scoring system (chronic glomerular injury score [cg]) relies on relatively crude and arbitrary ordinal grades and has low inter-observer concordance that currently limits its usefulness as a surrogate endpoint for ABMR progression in clinical drug trials. Here, we describe and validate a novel quantitative method for quantifying progression of TG in ABMR. Using digital pathology in sequential biopsies from 75 patients at various stages of ABMR, we scored all capillaries in the most affected glomeruli for basement membrane duplication that were correlated with allograft function, outcome, Banff lesion scores, and gene expression. Our digital scoring reflected TG progression better than the categorical Banff cg score and correlated with Banff ABMR and chronicity lesions, but not transcript changes. In multivariate analysis, the delta change between biopsies with serum creatinine and mean percent duplicated glomerular basement membranes was significantly associated with graft loss. Neither the delta in any Banff lesion scores (including cg) nor in gene expression was associated with outcome. Receiver operating characteristic curve analysis showed that the digital pathology approach was superior to the conventional score for predicting graft failure. Thus, our digital pathology-based approach for scoring TG accurately assessed progression in TG. However, further validation as a potential surrogate endpoint in clinical trials for the treatment of ABMR is warranted.

Outcomes in kidney transplant recipients treated with immediate-release tacrolimus capsules versus extended-release tacrolimus capsules: A cohort study

INTRODUCTION

Prior randomized trials and observational studies have generally reported similar outcomes in kidney transplant recipients (KTRs) treated with immediate-release tacrolimus (IR-TAC) versus extended-release tacrolimus (ER-TAC). However, many of these previous studies focused on patients with low immunological risks, had small sample sizes and brief follow-up periods, and excluded outcomes associated with graft loss, such as chronic rejection.

METHODS

To address these limitations, we conducted a cohort study of 848 KTRs at a single transplantation center who had generally high immunological risks and were treated with either IR-TAC capsules (589 patients, 65.9%) or ER-TAC capsules (289 patients, 34.1%). All patients received their designated maintenance immunosuppressive regimen for at least 3 months post-transplantation. Afterwards, tacrolimus formulation was at the discretion of each patient's transplant nephrologist. For the two treatment groups, we compared the hazards of experiencing a composite outcome of acute or chronic antibody-mediated rejection (AMR), acute or chronic T-cell-mediated rejection, de novo DSA, and/or graft loss over a 3-year period starting at 3 months post-transplantation.

RESULTS

In a multivariable Cox proportional hazards regression model, KTRs treated with IR-TAC capsules had an increased hazard of experiencing the composite outcome when compared to patients treated with ER-TAC capsules; however, this result was not significant (adj HR 1.24, 95% CI .92-1.68, p = .163). Similar results were obtained with inverse probability of treatment weighting (IPTW) using a propensity score (adj HR 1.25, 95% CI .93-1.68, p = .146).

CONCLUSION

These findings suggest that when compared to IR-TAC capsules, ER-TAC capsules do not reduce the hazard of poor outcomes in KTRs with generally high immunological risks.

Immunosuppressant drugs and quality-of-life outcomes in kidney transplant recipients: An international cohort study (EU-TRAIN)

Introduction: Patient-Reported Outcomes (PRO) integrate a wide range of holistic dimensions that arenot captured within clinical outcomes. Particularly, from induction treatment to maintenance therapy, patient quality-of-life (QoL) of kidney transplant recipients have been sparsely investigated in international settings. Methods: In a prospective, multi-centric cohort study, including nine transplant centers in four countries, we explored the QoL during the year following transplantation using validated elicitation instruments (EQ-5D-3L index with VAS) in a population of kidney transplant patients receiving immunosuppressive therapies. Calcineurin inhibitors (tacrolimus and ciclosporin), IMPD inhibitor (mycophenolate mofetil), and mTOR inhibitors (everolimus and sirolimus) were the standard-of-care (SOC) medications, together with tapering glucocorticoid therapy. We used EQ-5D and VAS data as QoL measures alongside descriptive statistics at inclusion, per country and hospital center. We computed the proportions of patients with different immunosuppressive therapy patterns, and using bivariate and multivariate analyses, assessed the variations of EQ-5D and VAS between baseline (i.e., inclusion Month 0) and follow up visits (Month 12). Results: Among 542 kidney transplant patients included and followed from November 2018 to June 2021, 491 filled at least one QoL questionnaire at least at baseline (Month 0). The majority of patients in all countries received tacrolimus and mycophenolate mofetil, ranging from 90.0% in Switzerland and Spain to 95.8% in Germany. At M12, a significant proportion of patients switched immunosuppressive drugs, with proportion varying from 20% in Germany to 40% in Spain and Switzerland. At visit M12, patients who kept SOC therapy had higher EQ-5D (by 8 percentage points, p < 0.05) and VAS (by 4 percentage points, p < 0.1) scores than switchers. VAS scores were generally lower than EQ-5D (mean 0.68 [0.5-0.8] vs. 0.85 [0.8-1]). Discussion: Although overall a positive trend in QoL was observed, the formal analyses did not show any significant improvements in EQ-5D scores or VAS. Only when the effect of a therapy use was separated from the effect of switching, the VAS score was significantly worse for switchers during the follow up period, irrespective of the therapy type. If adjusted for patient characteristics and medical history (e.g., gender, BMI, eGRF, history of diabetes), VAS and EQ-5D delivered sound PRO measures for QoL assessments during the year following renal transplantation.

Data-Driven Chronic Allograft Phenotypes: A Novel and Validated Complement for Histologic Assessment of Kidney Transplant Biopsies

BACKGROUND

No validated system currently exists to realistically characterize the chronic pathology of kidney transplants that represents the dynamic disease process and spectrum of disease severity. We sought to develop and validate a tool to describe chronicity and severity of renal allograft disease and integrate it with the evaluation of disease activity.

METHODS

The training cohort included 3549 kidney transplant biopsies from an observational cohort of 937 recipients. We reweighted the chronic histologic lesions according to their time-dependent association with graft failure, and performed consensus k-means clustering analysis. Total chronicity was calculated as the sum of the weighted chronic lesion scores, scaled to the unit interval.

RESULTS

We identified four chronic clusters associated with graft outcome, based on the proportion of ambiguous clustering. The two clusters with the worst survival outcome were determined by interstitial fibrosis and tubular atrophy (IFTA) and by transplant glomerulopathy. The chronic clusters partially overlapped with the existing Banff IFTA classification (adjusted Rand index, 0.35) and were distributed independently of the acute lesions. Total chronicity strongly associated with graft failure (hazard ratio [HR], 8.33; 95% confidence interval [CI], 5.94 to 10.88; P<0.001), independent of the total activity scores (HR, 5.01; 95% CI, 2.83 to 7.00; P<0.001). These results were validated on an external cohort of 4031 biopsies from 2054 kidney transplant recipients.

CONCLUSIONS

The evaluation of total chronicity provides information on kidney transplant pathology that complements the estimation of disease activity from acute lesion scores. Use of the data-driven algorithm used in this study, called RejectClass, may provide a holistic and quantitative assessment of kidney transplant injury phenotypes and severity.

Clinical Prediction Model for Antibody-Mediated Rejection: A Strategy to Minimize Surveillance Endomyocardial Biopsies After Heart Transplantation

BACKGROUND

In heart transplantation, antibody-mediated rejection (AMR) is a major contributor to patient morbidity and mortality. Multiple routine endomyocardial biopsies (EMB) remain the gold standard to detect AMR, but this invasive procedure suffers from many limitations. We aimed to develop and validate an AMR risk model to improve individual risk stratification of AMR.

METHODS

Heart recipients from 2 referral transplant centers, Cedars-Sinai (US) and Pitié-Salpêtrière (France), were included from 2012 to 2019. Database included detailed clinical, immunologic, imaging, and histological parameters. The US cohort was randomly distributed in a derivation (2/3) and in a test set (1/3). The primary end point was biopsy-proven AMR. A mixed effect logistic regression model with a random intercept was applied to identify variables independently associated with AMR. Simulation analyzes were performed.

RESULTS

The US and French cohorts comprised a total of 1341 patients, representing 12 864 EMB. Overall, 490 AMR episodes were diagnosed (3.8% of EMB). Among the 26 potential determinants of AMR, 5 variables showed independent association: time post-transplant (P<0.001), pretransplant sensitizing event (P=0.001), circulating donor-specific anti-human leukocyte antigen antibody (P=0.001), graft dysfunction (P=0.004), and prior history of definite AMR (P<0.001). In the US test set, the calibration and the discrimination of the model were accurate (area under the curve, 0.79 [95% CI, 0.78-0.81]). Those results were confirmed in the external validation cohort (area under the curve, 0.78 [95% CI, 0.77-0.79]) and reinforced by various sensitivity analyses. The model also showed good performance to predict overall cause of rejection. Simulation models revealed that the AMR risk model could safely reduce the number of EMB.

CONCLUSIONS

Our results support the use of the AMR risk model as a clinical decision tool to minimize the number of routine EMB after heart transplantation.

Proposed Definitions of Antibody-Mediated Rejection for Use as a Clinical Trial Endpoint in Kidney Transplantation

Antibody-mediated rejection (AMR) is caused by antibodies that recognize donor human leukocyte antigen (HLA) or other targets. As knowledge of AMR pathophysiology has increased, a combination of factors is necessary to confirm the diagnosis and phenotype. However, frequent modifications to the AMR definition have made it difficult to compare data and evaluate associations between AMR and graft outcome. The present paper was developed following a Broad Scientific Advice request from the European Society for Organ Transplantation (ESOT) to the European Medicines Agency (EMA), which explored whether updating guidelines on clinical trial endpoints would encourage innovations in kidney transplantation research. ESOT considers that an AMR diagnosis must be based on a combination of histopathological factors and presence of donor-specific HLA antibodies in the recipient. Evidence for associations between individual features of AMR and impaired graft outcome is noted for microvascular inflammation scores ≥2 and glomerular basement membrane splitting of >10% of the entire tuft in the most severely affected glomerulus. Together, these should form the basis for AMR-related endpoints in clinical trials of kidney transplantation, although modifications and restrictions to the Banff diagnostic definition of AMR are proposed for this purpose. The EMA provided recommendations based on this Broad Scientific Advice request in December 2020; further discussion, and consensus on the restricted definition of the AMR endpoint, is required.

Allograft Function as Endpoint for Clinical Trials in Kidney Transplantation

Clinical study endpoints that assess the efficacy of interventions in patients with chronic renal insufficiency can be adopted for use in kidney transplantation trials, given the pathophysiological similarities between both conditions. Kidney dysfunction is reflected in the glomerular filtration rate (GFR), and although a predefined (e.g., 50%) reduction in GFR was recommended as an endpoint by the European Medicines Agency (EMA) in 2016, many other endpoints are also included in clinical trials. End-stage renal disease is strongly associated with a change in estimated (e)GFR, and eGFR trajectories or slopes are increasingly used as endpoints in clinical intervention trials in chronic kidney disease (CKD). Similar approaches could be considered for clinical trials in kidney transplantation, although several factors should be taken into account. The present Consensus Report was developed from documentation produced by the European Society for Organ Transplantation (ESOT) as part of a Broad Scientific Advice request that ESOT submitted to the EMA in 2020. This paper provides a contemporary discussion of primary endpoints used in clinical trials involving CKD, including proteinuria and albuminuria, and evaluates the validity of these concepts as endpoints for clinical trials in kidney transplantation.

Rationale for Surrogate Endpoints and Conditional Marketing Authorization of New Therapies for Kidney Transplantation

Conditional marketing authorization (CMA) facilitates timely access to new drugs for illnesses with unmet clinical needs, such as late graft failure after kidney transplantation. Late graft failure remains a serious, burdensome, and life-threatening condition for recipients. This article has been developed from content prepared by members of a working group within the European Society for Organ Transplantation (ESOT) for a Broad Scientific Advice request, submitted by ESOT to the European Medicines Agency (EMA), and reviewed by the EMA in 2020. The article presents the rationale for using surrogate endpoints in clinical trials aiming at improving late graft failure rates, to enable novel kidney transplantation therapies to be considered for CMA and improve access to medicines. The paper also provides background data to illustrate the relationship between primary and surrogate endpoints. Developing surrogate endpoints and a CMA strategy could be particularly beneficial for studies where the use of primary endpoints would yield insufficient statistical power or insufficient indication of long-term benefit following transplantation.

Surrogate Endpoints for Late Kidney Transplantation Failure

In kidney transplant recipients, late graft failure is often multifactorial. In addition, primary endpoints in kidney transplantation studies seek to demonstrate the short-term efficacy and safety of clinical interventions. Although such endpoints might demonstrate short-term improvement in specific aspects of graft function or incidence of rejection, such findings do not automatically translate into meaningful long-term graft survival benefits. Combining many factors into a well-validated model is therefore more likely to predict long-term outcome and better reflect the complexity of late graft failure than using single endpoints. If conditional marketing authorization could be considered for therapies that aim to improve long-term outcomes following kidney transplantation, then the surrogate endpoint for graft failure in clinical trial settings needs clearer definition. This Consensus Report considers the potential benefits and drawbacks of several candidate surrogate endpoints (including estimated glomerular filtration rate, proteinuria, histological lesions, and donor-specific anti-human leukocyte antigen antibodies) and composite scoring systems. The content was created from information prepared by a working group within the European Society for Organ Transplantation (ESOT). The group submitted a Broad Scientific Advice request to the European Medicines Agency (EMA), June 2020: the request focused on clinical trial design and endpoints in kidney transplantation. Following discussion and refinement, the EMA made final recommendations to ESOT in December 2020 regarding the potential to use surrogate endpoints in clinical studies that aim to improving late graft failure.

Proposed Definitions of T Cell-Mediated Rejection and Tubulointerstitial Inflammation as Clinical Trial Endpoints in Kidney Transplantation

The diagnosis of acute T cell-mediated rejection (aTCMR) after kidney transplantation has considerable relevance for research purposes. Its definition is primarily based on tubulointerstitial inflammation and has changed little over time; aTCMR is therefore a suitable parameter for longitudinal data comparisons. In addition, because aTCMR is managed with antirejection therapies that carry additional risks, anxieties, and costs, it is a clinically meaningful endpoint for studies. This paper reviews the history and classifications of TCMR and characterizes its potential role in clinical trials: a role that largely depends on the nature of the biopsy taken (indication vs protocol), the level of inflammation observed (e.g., borderline changes vs full TCMR), concomitant chronic lesions (chronic active TCMR), and the therapeutic intervention planned. There is ongoing variability—and ambiguity—in clinical monitoring and management of TCMR. More research, to investigate the clinical relevance of borderline changes (especially in protocol biopsies) and effective therapeutic strategies that improve graft survival rates with minimal patient morbidity, is urgently required. The present paper was developed from documentation produced by the European Society for Organ Transplantation (ESOT) as part of a Broad Scientific Advice request that ESOT submitted to the European Medicines Agency for discussion in 2020. This paper proposes to move toward refined definitions of aTCMR and borderline changes to be included as primary endpoints in clinical trials of kidney transplantation.

FC031: Validation of a Prediction System for Risk of Allograft Loss (IBOX) in Pediatric Kidney Transplant Recipients

BACKGROUND AND AIMS

Kidney allograft loss is a common cause of end-stage renal disease but accurate prediction models of kidney allograft loss are lacking in children. The iBOX system has been broadly validated among adults. We aimed to validate the iBOX system in a large international cohort of pediatric kTx recipients.

METHOD

In this observational study, we used data from pediatric (&lt;21) patients transplanted between 2005 and 2017 from 20 institutions in Europe and the USA. Patients with functional parameters (eGFR and UPCR), donor specific antibody and biopsy results (Banff scores g, ptc, cg, i, t and IFTA) were included. Individual predictions of allograft loss were obtained by applying the iBOX score on our data. The prediction performances of the model in our population were assessed via discrimination (c-statistics) and calibration.

RESULTS

A total of 573 kTx recipients were included. Median time from transplantation to evaluation was 1.0 (0.5–2.0) year with a mean age at evaluation at 12.1 (5.5) years and mean follow-up after transplantation 5.1 (2.8) years. Five-year death-censored graft survival from evaluation was 95%. At the time of evaluation, mean eGFR and uPCR were 65.5 (29.6) mL/min/1.73 m2 and 0.25 (1.2) g/g, respectively. A total of 118 (20.6%) of the patients had DSA. The iBOX system showed good discrimination with a c-statistic of 0.81 and good calibration (Figure 1).

CONCLUSION

The iBOX system demonstrated high accuracy in predicting kidney allograft loss in children with performances similar to those reported in adults.

MO1021: Long-Term Outcomes After Conversion to a Belatacept-Based Immunosuppression in Kidney Transplant: A Matched Cohort Study

BACKGROUND AND AIMS

Conversion to a belatacept regimen after transplant seems to be safe. However, no studies have reported the long-term efficacy and safety outcomes after conversion to a belatacept regimen and compared it with patients treated with a CNI-based regimen in kidney transplantation. This study aims to investigate the long-term outcomes of patients converted to a belatacept regimen compared with matched patients under a CNI regimen.

METHOD

Kidney transplant recipients transplanted between 1998 and 2019 from two French academic transplant canters were recruited. We used a propensity score to match with a 1:1 ratio of patients at the time of the biopsy, which indicates the conversion to a belatacept regimen to control patients under a CNI regimen with a biopsy after transplant. We used 11 parameters associated with graft survival for the matching, 4 baseline transplant characteristics (recipient age, prior transplant status, donor type and dgf) and 7 at time of the biopsy (time after transplant, eGFR, proteinuria, DSA and Banff scores cv, ah, IFTA). Transplant outcomes defined by graft and patient survival, as well as safety outcomes, were compared between the matched patients.

RESULTS

From 3215 kidney transplant recipients transplanted during the study period with the inclusion criteria (311 patients under belatacept and 2904 patients under CNI). A total of 243 patients under belatacept were matched with 243 controls under CNI. All prognostic parameters were well-balanced before conversion between the two groups, with a mean age of 54.7 ± 15.1 years (P = .4543), a mean time of 2.2 ± 3.2 years after transplant (P = .586), a mean eGFR of 33.0 ± 13.3 mL/min/1.73 m2 (P = .976), a median proteinuria of 0.23 (0.12–0.50) g/g (P = .278) and 30.9% of positive anti-HLA DSA (P = 1.0) in the belatacept group. After a mean follow-up time after conversion of 4.4 ± 2.5 years, 36 (14.8%) patients lost their grafts and 39 (16.0%) patients died in the belatacept cohort. After conversion to a belatacept regimen, the graft survival was significantly improved when we compared with the matched patients’ under CNI P &lt; .0001 (Fig. 1). Patients converted to Belatacept showed a lower death rate of 16.0% compared with 30.0% for the CNI treated patients (P &lt; .001). The safety outcomes showed a similar rate of biopsy proven rejection (P = .08), major adverse cardiovascular events and cancer between the two groups, while a significant higher rate of CMV disease was observed among the belatacept treated patients P &lt; .01).

CONCLUSION

This study confirms that conversion to belatacept post-transplant is associated with improved long-term graft outcome and acceptable safety. Conversion to belatacept after transplant should be considered as a valuable therapeutic option for kidney recipients.

FC 105: Multidimensional Prognostication Tool for Kidney Transplant Patient Survival: The Mortality Mbox

BACKGROUND AND AIMS

Predicting kidney transplant patient mortality has been hampered by registry-based studies and low-level phenotyped cohorts without specific design towards mortality prediction. This represents a limitation for decision making and ultimately patient care. We aimed to build a robust patient mortality prognostication system.

METHOD

We enrolled 1446 patients transplanted in France between 2004 and 2014 in whom a protocol-based collection including more than 160 parameters from the recipient (past medical history, risk factors) donor and graft, biological and imaging data, was performed on the day of transplantation (TX) and during the first year of transplantation. Multivariable Cox model was used to develop an individual predictive score of mortality, further improved by a Lasso regression in order to retain the strongest predictors of mortality.

RESULTS

Among the 1446 kidney transplant recipients included, 309 patients died after a median post-TX follow-up time of 7.6 years (IQR 5.40–10.78).

Among the 120 parameters, 19 predictors were selected using lasso regression. The strongest predictors of patient survival were (1) baseline recipient factors (age, history of cancer, diabetes mellitus, chronic obstructive pulmonary disease, cardiovascular events: myocardial infarction, stroke or arteritis, supraventricular cardiac rhythm disorder, psychiatric history and VHC status); (2) post-TX parameters (need for dialysis, cardiovascular complications and cancer in the first year of TX); and (3) seven biological variables (HbA1c, C-reactive protein, albumin, gamma-glutamyl transferase, uric acid, neutrophils and urinary protein). The mortality score showed accurate calibration and discrimination at 10 years [C-statistic = 0.81; 95% confidence interval (95% CI) 0.78–0.83].

CONCLUSION

We generate the first integrative patient survival score that shows a superior prediction performance when compared to previous prognostic systems, reaching 81% prediction accuracy at 10 years. A reliable survival prediction tool will enable improved patient monitoring and therapeutic decision making to alter the course of an unfavorable patient survival outcome and may provide a surrogate endpoint in clinical trials.

FC 113: Development and Validation of an Integrative DD-CFDNA System to Predict Allograft Rejection: A Population Based Study

BACKGROUND AND AIMS

Post-transplantation patient care requires development and validation of noninvasive biomarkers to improve allograft monitoring and prevention from unnecessary biopsies. Preliminary reports have suggested the association of donor derived cell-free DNA (dd-cfDNA) with allograft rejection. However, there is no proof of its added value beyond standard of care patient management in large and deep phenotyped cohorts.

METHOD

A total of 1210 concomitant evaluations of allograft histology, anti-HLA DSA and functional parameters between 2013 and 2018 were included corresponding to 637 evaluations in the derivation cohort and 573 in the validation cohort. dd-cfDNA was measured in plasma at the time of the evaluation. Diagnoses were assessed using Banff 2019 criteria. Parameters associated with kidney allograft rejection were assessed using uni- and multivariable logistic regression. We developed a risk model using the variables that were independently associated with rejection.

RESULTS

Higher levels of dd-cfDNA were observed for AMR and TCMR or both compared to other diagnoses (Figure 1A). We found incremental dd-cfDNA levels with increasing Banff lesion scores for g, ptc, i, t, cg and C4d (Figure 1B). There was no association of dd-cfDNA levels with allograft inactive lesions. In multivariable analysis, dd-cfDNA (P &lt; 0.0001) was associated with kidney allograft rejection independently of DSA (P &lt; 0.0001), eGFR (P = 0.018), kidney allograft instability (P = 0.013) and previous rejection (P &lt; 0.0001). Based on these parameters, we built an integrative idd-cfDNA model that showed good discrimination (AUC: 0.83), good calibration and added value beyond a model without dd-cfDNA (AUC of the model without dd-cfDNA: 0.77 versus 0.83 for the integrative model; P &lt; 0.0001). We confirmed our results in the validation cohort with a good discrimination (AUC: 0.82) and a good calibration. This integrative score, including the dd-cfDNA, is being validated in Belgium and in the USA.

CONCLUSION

We demonstrate the independent and added value of dd-cfDNA in addition to conventional features to predict rejection. This first integrative system shows improved performance for patient monitoring and could help physicians in decision-making process.

FC 107: Development and Validation of a Machine Learning-Based Virtual Biopsy System in Kidney Transplant Patients

BACKGROUND AND AIMS

Graphical Abstract

In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate lesions inherited from the donor or acquired after transplantation. However, many centres worldwide do not perform those biopsies which remain invasive, costly and may delay the transplant procedure. We aimed to develop and validate a noninvasive virtual biopsy system.

METHOD

A total of 17 centres were included from Europe, North America and Australia from 2000 to 2019. Candidate predictors were assessed following a prespecified protocol. Outcome measures were the day-zero biopsy lesions (Banff classification) including CV, AH, IFTA scores and % of sclerotic glomeruli. Six machine learning models were developed and their performances were assessed.

RESULTS

A total of 12 992 day-zero biopsies were included. Eleven parameters were used to build the classifiers, including donor age, kidney function, hypertension, BMI, proteinuria, diabetes, sex, donor type, cause of death and Hep-C status. The ensemble models (random forests, neural networks, gradient boosting, extreme gradient boosting tree, linear discriminant analysis, and naive Bayes) showed multi-AUC of 0.738, 0.817 and 0.788 for prediction of CV, AH and IFTA scores, and a good performance for predicting glomerulosclerosis (mean absolute error, MAE = 4.766). We confirmed the robustness and generalizability in multiple clinical scenarios and subpopulations and built an online interface for clinicians: https://transplant-pred/Virtual_Biopsy.

CONCLUSION

We developed and validated the first virtual biopsy system that enables the prediction of day-zero biopsy, based on routinely collected parameters. This can assist clinicians in assessing allograft quality, discrimination of donor derived versus acquired lesions after transplantation and prevent overdiagnosis of calcineurin inhibitor (CNI) toxicity.