ABSTRACT
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.
Subject(s)
Kidney Transplantation , Humans , Prognosis , Retrospective Studies , Systematic Reviews as Topic , BiomarkersABSTRACT
The 2022 Banff classification for kidney allograft pathology introduced the category "microvascular inflammation DSA-negative and C4d-negative" for cases without evidence of a humoral cause. Many questions remain about the etiology, prognosis, and treatment of this phenotype. Cristoferi et al. performed a molecular comparison of chronic active antibody-mediated rejection and its seronegative counterpart and suggest a central role for T cells in chronic donor-specific antibody-negative, C4d-negative microvascular inflammation. These results further question how we should classify rejection.
Subject(s)
Kidney Transplantation , Humans , Kidney Transplantation/adverse effects , Isoantibodies , T-Lymphocytes , Kidney/pathology , Inflammation/pathology , Graft Rejection/prevention & control , Graft Rejection/pathology , Biopsy , Peptide Fragments , Complement C4bABSTRACT
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/1.73m2, 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.
Subject(s)
Glomerular Filtration Rate , Kidney Transplantation , Kidney , Humans , Kidney Transplantation/adverse effects , Male , Female , Middle Aged , Retrospective Studies , Kidney/physiopathology , Adult , Time Factors , Belgium , Aged , Germany , Graft Survival , NetherlandsABSTRACT
Lesion scores on procurement donor biopsies are commonly used to guide organ utilization for deceased-donor kidneys. However, frozen sections present challenges for histological scoring, leading to inter- and intra-observer variability and inappropriate discard. Therefore, we constructed deep-learning based models to recognize kidney tissue compartments in hematoxylin & eosin-stained sections from procurement needle biopsies performed nationwide in years 2011-2020. To do this, we extracted whole-slide abnormality features from 2431 kidneys and correlated with pathologists' scores and transplant outcomes. A Kidney Donor Quality Score (KDQS) was derived and used in combination with recipient demographic and peri-transplant characteristics to predict graft loss or assist organ utilization. The performance on wedge biopsies was additionally evaluated. Our model identified 96% and 91% of normal/sclerotic glomeruli respectively; 94% of arteries/arterial intimal fibrosis; 90% of tubules. Whole-slide features of Sclerotic Glomeruli (GS)%, Arterial Intimal Fibrosis (AIF)%, and Interstitial Space Abnormality (ISA)% demonstrated strong correlations with corresponding pathologists' scores of all 2431 kidneys, but had superior associations with post-transplant estimated glomerular filtration rates in 2033 and graft loss in 1560 kidneys. The combination of KDQS and other factors predicted one- and four-year graft loss in a discovery set of 520 kidneys and a validation set of 1040 kidneys. By using the composite KDQS of 398 discarded kidneys due to "biopsy findings", we suggest that if transplanted, 110 discarded kidneys could have had similar survival to that of other transplanted kidneys. Thus, our composite KDQS and survival prediction models may facilitate risk stratification and organ utilization while potentially reducing unnecessary organ discard.
Subject(s)
Deep Learning , Kidney Transplantation , Tissue and Organ Procurement , Humans , Kidney Transplantation/adverse effects , Retrospective Studies , Donor Selection , Kidney/pathology , Tissue Donors , Biopsy , Fibrosis , Graft SurvivalABSTRACT
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.
ABSTRACT
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/1.73m2) 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.
ABSTRACT
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.
Subject(s)
Kidney Transplantation , Humans , Complement C4b , Canada , Kidney/pathology , Inflammation/pathology , Isoantibodies , BiopsyABSTRACT
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.
Subject(s)
Kidney Transplantation , Canada , Graft Rejection/etiology , Graft Rejection/pathology , Kidney/pathology , AllograftsABSTRACT
RATIONALE & OBJECTIVE: Kidneys are vital for vitamin D metabolism, and disruptions in both production and catabolism occur in chronic kidney disease. Although vitamin D activation occurs in numerous tissues, the kidneys are the most relevant source of circulating active vitamin D. This study investigates extrarenal vitamin D activation and the impact of kidney transplantation on vitamin D metabolism in patients who are anephric. STUDY DESIGN: Case series. SETTING & PARTICIPANTS: Adult patients with previous bilateral nephrectomy (anephric) not receiving active vitamin D therapy evaluated at the time of (N=38) and 1 year after (n=25) kidney transplantation. ANALYTICAL APPROACH: Chromatography with tandem mass spectrometry was used to measure vitamin D metabolites. Activity of CYP24A1 [24,25(OH)2D/25(OH)D] and CYP27B1 [1α,25(OH)2D/25(OH)D] is expressed as metabolic ratios. Differences between time points were evaluated by paired t-test or Wilcoxon matched-pairs signed-rank test. RESULTS: At time of transplantation, 1α,25(OH)2D was detectable in all patients (4-36pg/mL). There was a linear relationship between 25(OH)D and 1α,25(OH)2D levels (r=0.58, P<0.001), with 25(OH)D explaining 34% of the variation in 1α,25(OH)2D levels. There were no associations between 1α,25(OH)2D and biointact parathyroid hormone (PTH) or fibroblast growth factor 23 (FGF-23). One year after transplantation, 1α,25(OH)2D levels recovered (+205%), and CYP27B1 activity increased (+352%). Measures of vitamin D catabolism, 24,25(OH)2D and CYP24A1 activity increased 3- to 5-fold. Also, at 12 months after transplantation, 1α,25(OH)2D was positively correlated with PTH (ρ=0.603, P=0.04) but not with levels of 25(OH)D or FGF-23. LIMITATIONS: Retrospective, observational study design with a small cohort size. CONCLUSIONS: Low-normal levels of 1α,25(OH)2D was demonstrated in anephric patients, indicating production outside the kidneys. This extrarenal CYP27B1 activity may be more substrate driven than hormonally regulated. Kidney transplantation seems to restore kidney CYP27B1 and CYP24A1 activity, as evaluated by vitamin D metabolic ratios, resulting in both increased vitamin D production and catabolism. These findings may have implications for vitamin D supplementation strategies in the setting of kidney failure and transplantation. PLAIN-LANGUAGE SUMMARY: Vitamin D activation occurs in multiple tissues, but the kidneys are considered the only relevant source of circulating levels. This study investigates vitamin D activation outside the kidneys by measuring vitamin D metabolites in 38 patients without kidneys. Active vitamin D was detectable in all patients, indicating production outside of the kidneys. There was a strong relationship between active and precursor vitamin D levels, but no association with mineral metabolism hormones, indicating that vitamin D production was more substrate dependent than hormonally regulated. One year after kidney transplantation, active vitamin D levels increased 2-fold and breakdown products increased 3-fold, indicating that production and degradation of the hormone recovers after kidney transplantation. These findings are relevant for future research into vitamin D supplementation in kidney failure.
ABSTRACT
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.
Subject(s)
Kidney Diseases , Kidney Transplantation , Humans , Kidney Transplantation/adverse effects , Prospective Studies , Cross-Sectional Studies , Chemokine CXCL10/urine , Graft Rejection/diagnosis , Kidney Diseases/etiology , Biomarkers/urineABSTRACT
The KDIGO guideline for acute rejection treatment recommends use of corticosteroids and suggests using lymphocyte-depleting agents as second line treatment. Aim of the study was to determine the current practices of detection and treatment of TCMR of kidney allografts amongst European kidney transplant centres. An invitation was sent through ESOT/EKITA newsletters and through social media to transplant professionals in Europe for taking part in the survey. A total of 129 transplant professionals responded to the survey. There was equal representation of small and large sized transplant centres. The majority of centres treat borderline changes (BL) and TCMR (Grade IA-B, IIA-B) in indication biopsies and protocol biopsies with corticosteroids as first line treatment. Thymoglobulin is used mainly as second line treatment for TCMR Grade IA-B (80%) and TCMR IIA-B (85%). Treatment success is most often evaluated within one month of therapy. There were no differences observed between the large and small centres for the management of TCMR. This survey highlights the common practices and diversity in clinics for the management of TCMR in Europe. Testing new therapies for TCMR should be in comparison to the current standard of care in Europe. Better consensus on treatment success is crucial for robust study designs.
Subject(s)
Graft Rejection , Kidney Transplantation , Humans , Graft Rejection/diagnosis , Europe , Surveys and Questionnaires , T-Lymphocytes/immunology , Immunosuppressive Agents/therapeutic use , Adrenal Cortex Hormones/therapeutic use , Biopsy , Antilymphocyte Serum/therapeutic useABSTRACT
An increasing number of sensitized patients awaiting transplantation face limited options, leading to fatalities during dialysis and higher costs. The absence of established evidence highlights the need for collaborative consensus. Donor-specific antibodies (DSA)-triggered antibody-mediated rejection (AMR) significantly contributes to kidney graft failure, especially in sensitized patients. The European Society for Organ Transplantation (ESOT) launched the ENGAGE initiative, categorizing sensitized candidates by AMR risk to improve patient care. A systematic review assessed induction and maintenance regimens as well as antibody removal strategies, with statements subjected to the Delphi methodology. A Likert-scale survey was distributed to 53 European experts (Nephrologists, Transplant surgeons and Immunologists) with experience in kidney transplant recipient care. A rate ≥75% with the same answer was considered consensus. Consensus was achieved in 95.3% of statements. While most recommendations aligned, two statements related to complement inhibitors for AMR prophylaxis lacked consensus. The ENGAGE consensus presents contemporary recommendations for desensitization and immunomodulation strategies, grounded in predefined risk categories. The adoption of tailored, patient-specific measures is anticipated to streamline the care of sensitized recipients undergoing renal allografts. While this approach holds the promise of enhancing transplant accessibility and fostering long-term success in transplantation outcomes, its efficacy will need to be assessed through dedicated studies.
Subject(s)
Consensus , Delphi Technique , Graft Rejection , Kidney Transplantation , Humans , Graft Rejection/prevention & control , Graft Rejection/immunology , Europe , Isoantibodies/immunology , Transplant RecipientsABSTRACT
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.
Subject(s)
Kidney Transplantation , Renal Insufficiency , Humans , Kidney Transplantation/adverse effects , Kidney , Transplantation, Homologous , Machine Learning , Allografts , Graft SurvivalABSTRACT
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 log10 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.
ABSTRACT
Isolated microvascular inflammation (iMVI) without HLA donor-specific antibodies or C4d deposition in peritubular capillaries remains an enigmatic phenotype that cannot be categorized as antibody-mediated rejection (ABMR) in recent Banff classifications. We included 221 kidney transplant recipients with biopsies with ABMR (n = 73), iMVI (n = 32), and normal (n = 116) diagnoses. We compared peripheral blood leukocyte distribution by flow cytometry and inflammatory infiltrates in kidney transplant biopsies among groups. Flow cytometry showed fewer lymphocytes and total, CD4+, and CD8+ peripheral T cells in iMVI compared with ABMR and normal cases. ABMR and iMVI had fewer total natural Killer (NK) cells but more NKG2A+ NK cells. Immunohistochemistry indicated that ABMR and iMVI had greater CD3+ and CD68+ glomerular infiltration than normal biopsies, whereas CD8+ and TIA1+ cells showed only increased iMVI, suggesting they are cytotoxic T cells. Peritubular capillaries displayed more CD3+, CD56+, TIA1+, and CD68+ cells in both ABMR and iMVI. In contrast, iMVI had less plasma cell infiltration in peritubular capillaries and interstitial aggregates than ABMR. iMVI displayed decreased circulating T and NK cells mirrored by T cell and NK cell infiltration in the renal allograft, similar to ABMR. However, the lesser plasma cell infiltration in iMVI may suggest an antibody-independent underlying stimulus.
Subject(s)
Kidney Transplantation , Humans , Kidney Transplantation/adverse effects , Kidney/pathology , Antibodies , Inflammation/pathology , Killer Cells, Natural , HLA Antigens , Graft Rejection/pathologyABSTRACT
Further improvements of outcome after solid organ transplantation will depend on our ability to integrate personalized medicine in clinical routine. Not only better risk stratification or improved diagnostics, also targeted therapies and predictive markers of treatment success are needed, as there is a virtual standstill in the development and implementation of novel therapies for prevention and treatment of allograft rejection. The integration of clinical decision support algorithms and novel biomarkers in clinical practice will require a different reasoning, embracing concepts of uncertainty and probabilistic thinking as the ground truth is often unknown and the tools imperfect. This is important for communication between healthcare professionals, but patients and their caregivers also need to be informed and educated about the levels of uncertainty inherent to personalized medicine. In the translation of research findings and personalized medicine to routine clinical care, it remains crucial to maintain global consensus on major aspects of clinical routine, to avoid further divergence between centres and countries in the standard of care. Such consensus can only be reached when experts with divergent opinions are willing to transcend their own convictions, understand that there is not one single truth, and thus are able to embrace a level of uncertainty.
Subject(s)
Precision Medicine , Humans , Uncertainty , Consensus , Greece, Ancient , BiomarkersABSTRACT
Solid phase immunoassays improved the detection and determination of the antigen-specificity of donor-specific antibodies (DSA) to human leukocyte antigens (HLA). The widespread use of SPI in kidney transplantation also introduced new clinical dilemmas, such as whether patients should be monitored for DSA pre- or post-transplantation. Pretransplant screening through SPI has become standard practice and DSA are readily determined in case of suspected rejection. However, DSA monitoring in recipients with stable graft function has not been universally established as standard of care. This may be related to uncertainty regarding the clinical utility of DSA monitoring as a screening tool. This consensus report aims to appraise the clinical utility of DSA monitoring in recipients without overt signs of graft dysfunction, using the Wilson & Junger criteria for assessing the validity of a screening practice. To assess the evidence on DSA monitoring, the European Society for Organ Transplantation (ESOT) convened a dedicated workgroup, comprised of experts in transplantation nephrology and immunology, to review relevant literature. Guidelines and statements were developed during a consensus conference by Delphi methodology that took place in person in November 2022 in Prague. The findings and recommendations of the workgroup on subclinical DSA monitoring are presented in this article.
Subject(s)
Kidney Transplantation , Organ Transplantation , Humans , Graft Rejection , Isoantibodies , Kidney , HLA Antigens , Graft Survival , Transplant Recipients , Tissue Donors , Histocompatibility Testing , Retrospective StudiesABSTRACT
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.
Subject(s)
Artificial Intelligence , Kidney Transplantation , Humans , Algorithms , Kidney/pathologyABSTRACT
BACKGROUND: Knowledge of the effect of kidney transplantation on bone is limited and fragmentary. The aim of this study was to characterize the evolution of bone disease in the first post-transplant year. METHODS: We performed a prospective, observational cohort study in patients referred for kidney transplantation under a steroid-sparing immunosuppressive protocol. Bone phenotyping was done before, or at the time of, kidney transplantation, and repeated at 12 months post-transplant. The phenotyping included bone histomorphometry, bone densitometry by dual-energy x-ray absorptiometry, and biochemical parameters of bone and mineral metabolism. RESULTS: Paired data were obtained for 97 patients (median age 55 years; 72% male; 21% of patients had diabetes). Bone turnover remained normal or improved in the majority of patients (65%). Bone histomorphometry revealed decreases in bone resorption (eroded perimeter, mean 4.6% pre- to 2.3% post-transplant; P<0.001) and disordered bone formation (fibrosis, 27% pre- versus 2% post-transplant; P<0.001). Whereas bone mineralization was normal in all but one patient pretransplant, delayed mineralization was seen in 15% of patients at 1 year post-transplant. Hypophosphatemia was associated with deterioration in histomorphometric parameters of bone mineralization. Changes in bone mineral density were highly variable, ranging from -18% to +17% per year. Cumulative steroid dose was related to bone loss at the hip, whereas resolution of hyperparathyroidism was related to bone gain at both spine and hip. CONCLUSIONS: Changes in bone turnover, mineralization, and volume post-transplant are related both to steroid exposure and ongoing disturbances of mineral metabolism. Optimal control of mineral metabolism may be key to improving bone quality in kidney transplant recipients. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Evolution of Bone Histomorphometry and Vascular Calcification Before and After Renal Transplantation, NCT01886950.
Subject(s)
Bone Diseases , Kidney Transplantation , Bone Density , Female , Humans , Kidney Transplantation/adverse effects , Male , Middle Aged , Minerals , Prospective Studies , SteroidsABSTRACT
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.