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.

Comparison of artificial intelligence and human-based prediction and stratification of the risk of long-term kidney allograft failure

BACKGROUND

Clinical decisions are mainly driven by the ability of physicians to apply risk stratification to patients. However, this task is difficult as it requires complex integration of numerous parameters and is impacted by patient heterogeneity. We sought to evaluate the ability of transplant physicians to predict the risk of long-term allograft failure and compare them to a validated artificial intelligence (AI) prediction algorithm.

METHODS

We randomly selected 400 kidney transplant recipients from a qualified dataset of 4000 patients. For each patient, 44 features routinely collected during the first-year post-transplant were compiled in an electronic health record (EHR). We enrolled 9 transplant physicians at various career stages. At 1-year post-transplant, they blindly predicted the long-term graft survival with probabilities for each patient. Their predictions were compared with those of a validated prediction system (iBox). We assessed the determinants of each physician's prediction using a random forest survival model.

RESULTS

Among the 400 patients included, 84 graft failures occurred at 7 years post-evaluation. The iBox system demonstrates the best predictive performance with a discrimination of 0.79 and a median calibration error of 5.79%, while physicians tend to overestimate the risk of graft failure. Physicians' risk predictions show wide heterogeneity with a moderate intraclass correlation of 0.58. The determinants of physicians' prediction are disparate, with poor agreement regardless of their clinical experience.

CONCLUSIONS

This study shows the overall limited performance and consistency of physicians to predict the risk of long-term graft failure, demonstrated by the superior performances of the iBox. This study supports the use of a companion tool to help physicians in their prognostic judgement and decision-making in clinical care.

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.