Competing and Noncompeting Risk Models for Predicting Kidney Allograft Failure

BACKGROUND

Prognostic models are becoming increasingly relevant in clinical trials as potential surrogate endpoints, and for patient management as clinical decision support tools. However, the impact of competing risks on model performance remains poorly investigated. We aimed to carefully assess the performance of competing risk and noncompeting risk models in the context of kidney transplantation, where allograft failure and death with a functioning graft are two competing outcomes.

METHODS

We included 11,046 kidney transplant recipients enrolled in 10 countries. We developed prediction models for long-term kidney graft failure prediction, without accounting (i.e., censoring) and accounting for the competing risk of death with a functioning graft, using Cox, Fine-Gray, and cause-specific Cox regression models. To this aim, we followed a detailed and transparent analytical framework for competing and noncompeting risk modelling, and carefully assessed the models' development, stability, discrimination, calibration, overall fit, clinical utility, and generalizability in external validation cohorts and subpopulations. More than 15 metrics were used to provide an exhaustive assessment of model performance.

RESULTS

Among 11,046 recipients in the derivation and validation cohorts, 1,497 (14%) lost their graft and 1,003 (9%) died with a functioning graft after a median follow-up post-risk evaluation of 4.7 years (IQR 2.7-7.0). The cumulative incidence of graft loss was similarly estimated by Kaplan-Meier and Aalen-Johansen methods (17% versus 16% in the derivation cohort). Cox and competing risk models showed similar and stable risk estimates for predicting long-term graft failure (average mean absolute prediction error of 0.0140, 0.0138 and 0.0135 for Cox, Fine-Gray, and cause-specific Cox models, respectively). Discrimination and overall fit were comparable in the validation cohorts, with concordance index ranging from 0.76 to 0.87. Across various subpopulations and clinical scenarios, the models performed well and similarly, although in some high-risk groups (such as donors over 65 years old), the findings suggest a trend towards moderately improved calibration when using a competing risk approach.

CONCLUSIONS

Competing and noncompeting risk models performed similarly in predicting long-term kidney graft failure.

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.

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.

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.

Evaluation of non-invasive biomarkers of kidney allograft rejection in a prospective multicenter unselected cohort study (EU-TRAIN)

Non-invasive biomarkers are promising tools for improving kidney allograft rejection monitoring, but their clinical adoption requires more evidence in specifically designed studies. To address this unmet need, we designed the EU-TRAIN study, a large prospective multicentric unselected cohort funded by the European Commission. Here, we included consecutive adult patients who received a kidney allograft in nine European transplant centers between November 2018 and June 2020. We prospectively assessed gene expression levels of 19 blood messenger RNAs, four antibodies targeting non-human leukocyte antigen (HLA) endothelial antigens, together with circulating anti-HLA donor-specific antibodies (DSA). The primary outcome was allograft rejection (antibody-mediated, T cell-mediated, or mixed) in the first year post-transplantation. Overall, 412 patients were included, with 812 biopsies paired with a blood sample. CD4 gene expression was significantly associated with rejection, while circulating anti-HLA DSA had a significant association with allograft rejection and a strong association with antibody-mediated rejection. All other tested biomarkers, including AKR1C3, CD3E, CD40, CD8A, CD9, CTLA4, ENTPD1, FOXP3, GZMB, ID3, IL7R, MS4A1, MZB1, POU2AF1, POU2F1, TCL1A, TLR4, and TRIB1, as well as antibodies against angiotensin II type 1 receptor, endothelin 1 type A receptor, C3a and C5a receptors, did not show significant associations with allograft rejection. The blood messenger RNAs and non-HLA antibodies did not show an additional value beyond standard of care monitoring parameters and circulating anti-HLA DSA to predict allograft rejection in the first year post-transplantation. Thus, our results open avenues for specifically designed studies to demonstrate the clinical relevance and implementation of other candidate non-invasive biomarkers in kidney transplantation practice.

Concepts and applications of digital twins in healthcare and medicine

The digital twin (DT) is a concept widely used in industry to create digital replicas of physical objects or systems. The dynamic, bi-directional link between the physical entity and its digital counterpart enables a real-time update of the digital entity. It can predict perturbations related to the physical object's function. The obvious applications of DTs in healthcare and medicine are extremely attractive prospects that have the potential to revolutionize patient diagnosis and treatment. However, challenges including technical obstacles, biological heterogeneity, and ethical considerations make it difficult to achieve the desired goal. Advances in multi-modal deep learning methods, embodied AI agents, and the metaverse may mitigate some difficulties. Here, we discuss the basic concepts underlying DTs, the requirements for implementing DTs in medicine, and their current and potential healthcare uses. We also provide our perspective on five hallmarks for a healthcare DT system to advance research in this field.

Cell-free DNA for the detection of kidney allograft rejection

Donor-derived cell-free DNA (dd-cfDNA) is an emerging noninvasive biomarker that has the potential to detect allograft injury. The capacity of dd-cfDNA to detect kidney allograft rejection and its added clinical value beyond standard of care patient monitoring is unclear. We enrolled 2,882 kidney allograft recipients from 14 transplantation centers in Europe and the United States in an observational population-based study. The primary analysis included 1,134 patients. Donor-derived cell-free DNA levels strongly correlated with allograft rejection, including antibody-mediated rejection (P < 0.0001), T cell-mediated rejection (P < 0.0001) and mixed rejection (P < 0.0001). In multivariable analysis, circulating dd-cfDNA was significantly associated with allograft rejection (odds ratio 2.275; 95% confidence interval (CI) 1.902-2.739; P < 0.0001) independently of standard of care patient monitoring parameters. The inclusion of dd-cfDNA to a standard of care prediction model showed improved discrimination (area under the curve 0.777 (95% CI 0.741-0.811) to 0.821 (95% CI 0.784-0.852); P = 0.0011) and calibration. These results were confirmed in the external validation cohorts (n = 1,748) including a cohort of African American patients (n = 439). Finally, dd-cfDNA showed high predictive value to detect subclinical rejection in stable patients. Our study provides insights on the potential value of assessing dd-cfDNA, in addition to standard of care monitoring, to improve the detection of allograft rejection. ClinicalTrials.gov registration: NCT05995379 .

Antibody Mediated Rejection and T-cell Mediated Rejection Molecular Signatures Using Next-Generation Sequencing in Kidney Transplant Biopsies

Recently, interest in transcriptomic assessment of kidney biopsies has been growing. This study investigates the use of NGS to identify gene expression changes and analyse the pathways involved in rejection. An Illumina bulk RNA sequencing on the polyadenylated RNA of 770 kidney biopsies was conducted. Differentially-expressed genes (DEGs) were determined for AMR and TCMR using DESeq2. Genes were segregated according to their previous descriptions in known panels (microarray or the Banff Human Organ Transplant (B-HOT) panel) to obtain NGS-specific genes. Pathway enrichment analysis was performed using the Reactome and Kyoto Encyclopaedia of Genes and Genomes (KEGG) public repositories. The differential gene expression using NGS analysis identified 6,141 and 8,478 transcripts associated with AMR and TCMR. While most of the genes identified were included in the microarray and the B-HOT panels, NGS analysis identified 603 (9.8%) and 1,186 (14%) new specific genes. Pathways analysis showed that the B-HOT panel was associated with the main immunological processes involved during AMR and TCMR. The microarrays specifically integrated metabolic functions and cell cycle progression processes. Novel NGS-specific based transcripts associated with AMR and TCMR were discovered, which might represent a novel source of targets for drug designing and repurposing.

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.

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.

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.

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 .

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.

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.

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.