Search

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., (Copyright © 2024 by the American Society of Nephrology.)

Baseline kidney function following kidney transplantation is often used in research and clinical decision-making yet is not well defined. Here, a method to determine baseline function was proposed and validated on three single-center retrospective cohorts consisting of 922 patients from Belgium (main cohort) and two validation cohorts of 987 patients from the Netherlands and 519 patients from Germany. For each transplant, a segmented regression model was fitted on the estimated glomerular filtration rate (eGFR) evolution during the first-year post-transplantation. This yielded estimates for change point timing, rate of eGFR change before and after change point and eGFR value at change point, now considered the "baseline function". Associations of eGFR evolution with recipient/donor characteristics and the graft failure rate were assessed with linear regression and Cox regression respectively. The change point occurred on average at an eGFR value of 43.7±14.6 mL/min/1.73m 2 , at a median time of 6.5 days post-transplantation. Despite significant associations with several baseline donor-recipient characteristics (particularly, donor type; living vs deceased), the predictive value of these characteristics for eGFR value and timing of the change point was limited. This followed from a large heterogeneity within eGFR trajectories, which in turn indicated that favorable levels of kidney function could be reached despite a suboptimal initial evolution. Segmented regression consistently provided a good fit to early eGFR evolution, and its estimate of the change point can be a useful reference value in future analyses. Thus, our study shows that baseline kidney function after transplantation is heterogeneous and partly related to pretransplant donor characteristics., (Copyright © 2024 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

Graft failure and recipient death with functioning graft are important competing outcomes after kidney transplantation. Risk prediction models typically censor for the competing outcome thereby overestimating the cumulative incidence. The magnitude of this overestimation is not well-described in real-world transplant data. This retrospective cohort study analyzed data from the European Collaborative Transplant Study (CTS; n = 125 250) and from the American Scientific Registry of Transplant Recipients (SRTR; n = 190 258). Separate cause-specific hazard models, using donor and recipient age as continuous predictors, were developed for graft failure and recipient death. The hazard of graft failure increased quadratically with increasing donor age and decreased decaying with increasing recipient age. The hazard of recipient death increased linearly with increasing donor and recipient age. The cumulative incidence overestimation due to competing risk-censoring was largest in high-risk populations for both outcomes (old donors/recipients), sometimes amounting to 8.4 and 18.8 percentage points for graft failure and recipient death, respectively. In our illustrative model for post-transplant risk prediction, the absolute risk of graft failure and death is overestimated when censoring for the competing event, mainly in older donors and recipients. Prediction models for absolute risks should treat graft failure and death as competing events., (Copyright © 2024 American Society of Transplantation & American Society of Transplant Surgeons. Published by Elsevier Inc. All rights reserved.)

The Banff 2022 consensus introduced probable antibody-mediated rejection (AMR), characterized by mild AMR histologic features and human leukocyte antigen (HLA) donor-specific antibody (DSA) positivity. In a single-center observational cohort study of 1891 kidney transplant recipients transplanted between 2004 and 2021, 566 kidney biopsies were performed in 178 individual HLA-DSA-positive transplants. Evaluated at time of the first HLA-DSA-positive biopsy of each transplant (N = 178), 84 of the 178 (47.2%) of first biopsies were scored as no AMR, 22 of the 178 (12.4%) as probable AMR, and 72 of the 178 (40.4%) as AMR. The majority (77.3%) of probable AMR cases were first diagnosed in indication biopsies. Probable AMR was associated with lower estimated glomerular filtration rate (mL/min/1.73m 2 ) than no AMR (20.2 [8.3-32.3] vs 40.1 [25.4-53.3]; P = .001). The one-year risk of (repeat) AMR was similar for probable AMR and AMR (subdistribution hazard ratio (sHR), 0.99; 0.42-2.31; P = .97) and higher than after no AMR (sHR, 3.05; 1.07-8.73; P = .04). Probable AMR had a higher five-year risk of transplant glomerulopathy vs no AMR (sHR, 4.29; 0.92-19.98; P = 06), similar to AMR (sHR, 1.74; 0.43-7.04; P = .44). No significant differences in five-year risk of graft failure emerged between probable AMR and AMR (sHR, 1.14; 0.36-3.58; P = .82) or no AMR (sHR, 2.46; 0.78-7.74; P = .12). Probable AMR is a rare phenotype, however, sharing significant similarities with AMR in this single-center study. Future studies are needed to validate reproducible diagnostic criteria and associated clinical outcomes to allow for defining best management of this potentially relevant phenotype., (Copyright © 2024 American Society of Transplantation & American Society of Transplant Surgeons. Published by Elsevier Inc. All rights reserved.)

Solid phase detection and identification of HLA antibodies in kidney transplantation currently relies on single antigen bead (Luminex®) assays, which is more sensitive than the previously used enzyme-linked immunosorbent assays (ELISA). To evaluate the impact of more sensitive HLA testing on antibody-mediated rejection (AMR) occurrence and allograft survival, we analysed 1818 renal allograft recipients transplanted between March 2004 and May 2021. In 2008, solid phase testing switched from ELISA to Luminex. We included 393 (21.6%) transplantations before and 1425 (78.4%) transplantations after transition from ELISA- to Luminex-based testing. For this study, bio-banked ELISA era samples were tested retrospectively with Luminex. Significantly less pretransplant DSA were found in patients transplanted with pre-existing HLA antibodies in the Luminex (109/387) versus the ELISA period (43/90) (28% vs. 48%, p < 0.01). Throughout histological follow-up, 169 of 1818 (9.3%) patients developed AMR. After implementing Luminex-based testing, the rate of AMR significantly decreased (p = 0.003). However, incidence of graft failure did not significantly differ between both eras. In conclusion, less patients with pretransplant DSA were transplanted since the implementation of Luminex HLA testing. Transition from ELISA- to Luminex-based HLA testing was associated with a significant decrease in AMR occurrence post-transplantation. Since the decline of AMR did not translate into improved graft survival, Luminex-based testing has the added value of preventing low-risk AMR cases. Therefore, Luminex' high sensitivity must be balanced against waiting time for a suitable organ., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Rationale & Objective: Prior studies have demonstrated the diagnostic potential of urinary chemokines C-X-C motif ligand 9 (CXCL9) and CXCL10 for kidney transplant rejection. However, their benefit in addition to clinical information has not been demonstrated. We evaluated the diagnostic performance for detecting acute rejection of urinary CXCL9 and CXCL10 when integrated with clinical information., Study Design: Single-center prospective cohort study., Setting & Participants: We analyzed 1,559 biopsy-paired urinary samples from 622 kidney transplants performed between April 2013 and July 2019 at a single transplant center in Belgium. External validation was performed in 986 biopsy-paired urinary samples., Tests Compared: We quantified urinary CXCL9 (uCXCL9) and CXCL10 (uCXCL10) using an automated immunoassay platform and normalized the values to urinary creatinine. Urinary chemokines were incorporated into a multivariable model with routine clinical markers (estimated glomerular filtration rate, donor-specific antibodies, and polyoma viremia) (integrated model). This model was then compared with the tissue diagnosis according to the Banff classification for acute rejection., Outcome: Acute rejection detected on kidney biopsy using the Banff classification., Results: Chemokines integrated with routine clinical markers had high diagnostic value for detection of acute rejection (n=150) (receiver operating characteristic area under the curve 81.3% [95% CI, 77.6-85.0]). The integrated model would help avoid 59 protocol biopsies per 100 patients when the risk for rejection is predicted to be below 10%. The performance of the integrated model was similar in the external validation cohort., Limitations: The cross-sectional nature obviates investigating the evolution over time and prediction of future rejection., Conclusions: The use of an integrated model of urinary chemokines and clinical markers for noninvasive monitoring of rejection could enable a reduction in the number of biopsies. Urinary chemokines may be useful noninvasive biomarkers whose use should be further studied in prospective randomized trials to clarify their role in guiding clinical care and the use of biopsies to detect rejection after kidney transplantation., Plain-Language Summary: Urinary chemokines CXCL9 and CXCL10 have been suggested to be good noninvasive biomarkers of kidney transplant rejection. However, defining a context of use and integration with clinical information is necessary before clinical implementation can begin. In this study, we demonstrated that urinary chemokines CXCL9 and CXCL10, together with clinical information, have substantial diagnostic accuracy for the detection of acute kidney transplant rejection. Application of urinary chemokines together with clinical information may guide biopsy practices following kidney transplantation and potentially reduce the need for kidney transplant biopsies., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Systematic screening for BKPyV-DNAemia has been advocated to aid prevention and treatment of polyomavirus associated nephropathy (PyVAN), an important cause of kidney graft failure. The added value of performing a biopsy at time of BKPyV-DNAemia, to distinguish presumptive PyVAN (negative SV40 immunohistochemistry) and proven PyVAN (positive SV40) has not been established. Therefore, we studied an unselected cohort of 950 transplantations, performed between 2008-2017. BKPyV-DNAemia was detected in 250 (26.3%) transplant recipients, and positive SV40 in 91 cases (9.6%). Among 209 patients with a concurrent biopsy at time of first BKPyV-DNAemia, 60 (28.7%) biopsies were SV40 positive. Plasma viral load showed high diagnostic value for concurrent SV40 positivity (ROC-AUC 0.950, 95% confidence interval 0.916-0.978) and the semiquantitatively scored percentage of tubules with evidence of polyomavirus replication (pvl score) (0.979, 0.968-0.988). SV40 positivity was highly unlikely when plasma viral load is below 4 log 10 copies/ml (negative predictive value 0.989, 0.979-0.994). In SV40 positive patients, higher plasma BKPyV-DNA load and higher pvl scores were associated with slower viral clearance from the blood (hazard ratio 0.712, 95% confidence interval 0.604-0.839, and 0.327, 0.161-0.668, respectively), whereas the dichotomy positivity/negativity of SV40 immunohistochemistry did not predict viral clearance. Although the pvl score offers some prognostic value for viral clearance on top of plasma viral load, the latter provided good guidance for when a biopsy was unnecessary to exclude PyVAN. Thus, the distinction between presumptive and proven PyVAN, based on SV40 immunohistochemistry, has limited clinical value. Hence, management of BKPyV-DNAemia and immunosuppression reduction should be weighed against the risk of occurrence of rejection, or exacerbation of rejection observed concomitantly., (Copyright © 2023 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

Background: Autosomal dominant polycystic kidney disease (ADPKD) has occasionally been associated with lower peripheral white blood cell (WBC) counts. This study aimed to investigate the peripheral blood cell counts in a large cohort of kidney transplant recipients before and after kidney transplantation and its potential impact on post-transplant outcomes., Methods: This was a retrospective study with long-term follow-up data of 2090 patients who underwent a first kidney transplantation in the Leuven University Hospitals, of whom 392 had ADPKD., Results: In total, 2090 patients who underwent a first kidney transplantation in the Leuven University Hospitals were included, of whom 392 had ADPKD. Both pre- and post-transplantation, ADPKD patients had significantly lower total WBC counts, and more specifically lower neutrophil, lymphocyte and eosinophil counts compared with the non-ADPKD patients. This observation was independent of potential confounders such as level of inflammation, smoking habit, vitamins and pre-transplant medication. Overall survival and kidney transplant survival were significantly better in ADPKD vs non-ADPKD transplant recipients and a longer time to first infection was observed. However, no association between blood cell counts and outcome differences was found., Conclusions: In conclusion, this large single-center study reports a strong and independent association between ADPKD and lower peripheral WBC counts both before and after kidney transplantation. Considering the role of inflammation in disease progression, further investigation into the role of WBC in ADPKD is needed., Competing Interests: The research activities described in this manuscript are supported by Otsuka and Sanofi. Pieter Schellekens is supported by the Research Foundation Flanders (F.W.O.). EVL, holds a fellowship grant (1143919N) from The Research Foundation Flanders (F.W.O). DM reports research grants from Otsuka and serves in advisory boards for Otsuka, Sanofi Genzyme and Reata, all outside the submitted work and all paid to her institutions UZ Leuven and KU Leuven, Belgium., (© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.)

Rationale & Objective: The relationship between human leukocyte antigen (HLA) molecular mismatches and T-cell-mediated rejection (TCMR) is unknown. We investigated the associations between the different donor HLA-derived T-cell targets and the occurrence of TCMR and borderline histologic changes suggestive of TCMR after kidney transplantation., Study Design: Retrospective cohort study., Setting & Participants: All kidney transplant recipients at a single center between 2004 and 2013 with available biopsy data and a DNA sample for high-resolution HLA donor/recipient typing (N = 893)., Exposure: Scores calculated by the HLA matching algorithm PIRCHE-II and HLA eplet mismatches., Outcome: TCMR, borderline changes suggestive of TCMR, and allograft failure., Analytical Approach: Multivariable cause-specific hazards models were fit to characterize the association between HLA epitopes targets and study outcomes., Results: We found 277 patients developed TCMR, and 134 developed only borderline changes suggestive of TCMR on at least 1 biopsy. In multivariable analyses, only the PIRCHE-II scores for HLA-DRB1 and HLA-DQB1 were independently associated with the occurrence of TCMR and with allograft failure; this was not the case for HLA class I molecules. If restricted to rejection episodes within the first 3 months after transplantation, only the T-cell epitope targets originating from the donor's HLA-DRB1 and HLA-DQB1, but not class I molecules, were associated with the early acute TCMR. Also, the median PIRCHE-II score for HLA class II was statistically different between the patients with TCMR compared to the patients without TCMR (129 [IQR, 60-240] vs 201 [IQR, 96-298], respectively; P < 0.0001). These differences were not observed for class I PIRCHE-II scores., Limitations: Observational clinical data and residual confounding., Conclusions: In the absence of HLA-DSA, HLA class II but not class I mismatches are associated with early episodes of acute TCMR and allograft failure. This suggests that current immunosuppressive therapies are largely able to abort the most deleterious HLA class I-directed alloimmune processes; however, alloresponses against HLA-DRB1 and HLA-DQB1 molecular mismatches remain insufficiently suppressed., Plain-Language Summary: Genetic differences in the human leukocyte antigen (HLA) complex between kidney transplant donors and recipients play a central role in T-cell-mediated rejection (TCMR), which can lead to failure of the transplanted kidney. Evaluating this genetic disparity (mismatch) in the HLA complex at the molecular (epitope) level could contribute to better prediction of the immune response to the donor organ posttransplantation. We investigated the associations of the different donor HLA-derived T-cell epitope targets and scores obtained from virtual crossmatch algorithms with the occurrence of TCMR, borderline TCMR, and graft failure after kidney transplantation after taking into account the influence of donor-specific anti-HLA antibodies. This study illustrates the greater importance of the molecular mismatches in class II molecules compared to class I HLA molecules., (Copyright © 2022 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.)

Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Background and Objectives: The histology of antibody-mediated rejection after kidney transplantation is observed frequently in the absence of detectable donor-specific anti-HLA antibodies. Although there is an active interest in the role of non-HLA antibodies in this phenotype, it remains unknown whether HLA mismatches play an antibody-independent role in this phenotype of microcirculation inflammation., Design, Setting, Participants, & Measurements: To study this, we used the tools HLAMatchmaker, three-dimensional electrostatic mismatch score, HLA solvent accessible amino acid mismatches, and mismatched donor HLA-derived T cell epitope targets to determine the degree of HLA molecular mismatches in 893 kidney transplant recipients with available biopsy follow-up. Multivariable Cox proportional hazards models were applied to quantify the cause-specific hazard ratios of the different types of HLA mismatch scores for developing antibody-mediated rejection or histology of antibody-mediated rejection in the absence of donor-specific anti-HLA antibodies. In all survival analyses, the patients were censored at the time of the last biopsy., Results: In total, 121 (14%) patients developed histology of antibody-mediated rejection in the absence of donor-specific anti-HLA antibodies, of which 44 (36%) patients had concomitant T cell-mediated rejection. In multivariable Cox analysis, all different calculations of the degree of HLA mismatch associated with developing histology of antibody-mediated rejection in the absence of donor-specific anti-HLA antibodies. This association was dependent neither on the presence of missing self (potentially related to natural killer cell activation) nor on the formation of de novo HLA antibodies. Also, glomerulitis and complement C4d deposition in peritubular capillaries associated with the degree of HLA mismatch in the absence of anti-HLA antibodies., Conclusions: The histology of antibody-mediated rejection and its defining lesions are also observed in patients without circulating anti-HLA antibodies and relate to the degree of HLA mismatch., (Copyright © 2022 by the American Society of Nephrology.)

Despite the critical role of cytokines in allograft rejection, the relation of peripheral blood cytokine profiles to clinical kidney transplant rejection has not been fully elucidated. We assessed 28 cytokines through multiplex assay in 293 blood samples from kidney transplant recipients at time of graft dysfunction. Unsupervised hierarchical clustering identified a subset of patients with increased pro-inflammatory cytokine levels. This patient subset was hallmarked by a high prevalence (75%) of donor-specific anti-human leukocyte antigen antibodies (HLA-DSA) and histological rejection (70%) and had worse graft survival compared to the group with low cytokine levels (HLA-DSA in 1.7% and rejection in 33.7%). Thirty percent of patients with high pro-inflammatory cytokine levels and HLA-DSA did not have histological rejection. Exploring the cellular origin of these cytokines, we found a corresponding expression in endothelial cells, monocytes, and natural killer cells in single-cell RNASeq data from kidney transplant biopsies. Finally, we confirmed secretion of these cytokines in HLA-DSA-mediated cross talk between endothelial cells, NK cells, and monocytes. In conclusion, blood pro-inflammatory cytokines are increased in kidney transplant patients with HLA-DSA, even in the absence of histology of rejection. These observations challenge the concept that histology is the gold standard for identification of ongoing allo-immune activation after transplantation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Van Loon, Lamarthée, Barba, Claes, Coemans, de Loor, Emonds, Koshy, Kuypers, Proost, Senev, Sprangers, Tinel, Thaunat, Van Craenenbroeck, Schols and Naesens.)

Importance: Like other clinical biomarkers, trajectories of estimated glomerular filtration rate (eGFR) after kidney transplant are characterized by intra-individual variability. These fluctuations hamper the distinction between alarming graft functional deterioration or harmless fluctuation within the patient-specific expected reference range of eGFR., Objective: To determine whether a deep learning model could accurately predict the patient-specific expected reference range of eGFR after kidney transplant., Design, Setting, and Participants: A multicenter diagnostic study consisted of a derivation cohort of 933 patients who received a kidney transplant between 2004 and 2013 with 100 867 eGFR measurements from University Hospitals Leuven, Belgium, and 2 independent test cohorts: with 39 999 eGFR measurements from 1 170 patients, 1 from University Hospitals Leuven, Belgium, receiving transplants between 2013 and 2018 and 1 from Hannover Medical School, Germany, receiving transplants between 2003 and 2007. Patients receiving a single kidney transplant, with consecutive eGFR measurements were included. Data were analyzed from February 2019 to April 2021., Exposures: In the derivation cohort 100 867 eGFR measurements were available for analysis and 39 999 eGFR measurements from the independent test cohorts., Main Outcomes and Measures: A sequence-to-sequence model was developed for prediction of a patient-specific expected range of eGFR, based on previous eGFR values. The primary outcome was the performance of the deep learning sequence-to-sequence model in the 2 independent cohorts., Results: In this diagnostic study, a total of 933 patients in the training sets (mean [SD] age, 53.5 [13.3] years; 570 male [61.1%]) and 1170 patients in the independent test sets (cohort 1 [n = 621]: mean [SD] age, 58.5 [12.1] years; 400 male [64.4%]; cohort 2 [n = 549]: mean [SD] age, 50.1 [13.0] years; 316 male [57.6%]) who received a single kidney transplant most frequently from deceased donors, the sequence-to-sequence models accurately predicted future patient-specific eGFR trajectories within the first 3 months after transplant, based on the previous graft eGFR values (root mean square error, 6.4-8.9 mL/min/1.73 m2). The sequence-to-sequence model predictions outperformed the more conventional autoregressive integrated moving average prediction model, at all input/output number of eGFR values., Conclusions and Relevance: In this diagnostic study, a sequence-to-sequence deep learning model was developed and validated for individual forecasting of kidney transplant function. The patient-specific sequence predictions could be used in clinical practice to guide physicians on deviations from the expected intra-individual variability, rather than relating the individual results to the reference range of the healthy population.