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Enregistrement W4387790893 · doi:10.4103/1319-2442.388196

Implications of Banff Classification Schema: A Journey of Three Decades

2022· letter· en· W4387790893 sur OpenAlexaboutno aff
Praveen Kumar Etta

Notice bibliographique

RevueSaudi Journal of Kidney Diseases and Transplantation · 2022
Typeletter
Langueen
DomaineMedicine
ThématiqueRenal Transplantation Outcomes and Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineSchema (genetic algorithms)Information retrieval

Résumé

récupéré en direct d'OpenAlex

To the Editor, The first Banff meeting to standardize descriptions of kidney allograft pathology was held in 1991 and is celebrating three decades of journey now. In the past, several authors have reviewed the evolution of the Banff classification schema, few years ago.[1,2] After these publications, the Banff classification has been modified with each successive meeting, especially with regard to the diagnosis of rejection, both antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR). Here, we have discussed briefly the recent changes in this classification as it has finished three decades since inception. Till the early 1990s, there was considerable heterogeneity among pathologists in the characterization of kidney allograft biopsies. Hence, it was felt that standardization of allo-graft pathology was necessary to allow comparisons of the efficacy of different therapies and to help guide treatment. Initial classification systems that have been introduced include the Banff classification and the Cooperative Clinical Trials in Transplantation (CCTT) classification.[3] Kidney allograft pathology has been standardized with the introduction of Banff classification schema three decades ago, in the year 1991. It represented the first attempt to formulate an international consensus based and structured classification system for the diagnosis and categorization of kidney allograft pathology. In this regard, the first Banff meeting was held at Banff, Alberta, Canada in 1991 and the first publication appeared in 1993 (Banff ’93).[4] The Banff group comprised a group of pathologists, immunologists, physicians, surgeons, and immunogeneticists. Subsequent follow-up meetings have taken place every two years and the Banff schema has undergone considerable evolution over the last three decades. The Banff ’93 and the CCTT systems were both incorporated into the Banff ’97 classification. With its regular updates, the classification has changed with every success-sive meeting. Banff has introduced a numerical grading system for each of the kidney compartments – interstitium (i), tubules (t), vessels (v), and glomeruli (g). The precise histological characterization and differentiation have led to a better understanding of pathogenesis with its therapeutic implications. This has indirectly led to early, accurate diagnosis of graft pathology including rejection, its histological differentiation, differentiating TCMR and ABMR, grading the severity, and determining the degree of irreversible kidney damage [interstitial fibrosis and tubular atrophy (IFTA)], which enabled implementation of preemptive strategies and thereby better long-term graft survival. The presence of linear staining for C4d, a degradation product of the complement pathway that binds covalently to the endothelium, is highly suggestive of ABMR. C4d serves as an immunologic footprint of complement activation and ABMR. It was agreed that C4d staining in at least 10% of peritubular capillaries (C4d2 or C4d3) by immuno-fluorescence (IF) on frozen sections or in any peritubular capillaries by immunoperoxidase on paraffin sections (C4d score >0) should be regarded as “positive.” Some patients have morphologic evidence of ABMR and positive donor-specific antibodies (DSA) with little or no C4d staining. Diagnostic criteria for C4d-negative ABMR were incorporated into the 2013 Banff update.[5] Patients with the evidence of tissue injury and C4d positivity but no evidence of DSAs are typically managed as patients with ABMR.[6] Cases in which C4d staining is positive but DSA cannot be detected may result from DSA being below the level of detection due to immunoadsorption by the graft (sink effect) or it can also be due to the presence of nonhuman leukocyte antigen antibodies. This issue has been particularly discussed in the 2017 Banff conference.[7] Although molecular diagnostics were first introduced into the 2013 Banff, its 2017 update has recommended indications for the use of these tests in kidney allograft biopsy diagnosis. The inflammation in areas of the cortex with IFTA (i-IFTA) is the morphologic correlate of active injury and predicts disease progression. The total cortical inflammation (Banff ti score) was more predictive of graft loss than inflammation in non-sclerotic areas of cortex (Banff i score), indicating the impact of i-IFTA on graft outcomes.[8] The long-term deterioration of kidney allograft function study also showed a strong association between the severity of i-IFTA and graft loss, far stronger than that of IFTA alone.[9] The clinical implications of i-IFTA and its relationship to chronic active (CA) TCMR were well described in 2017 Banff. The alternatives to the DSA criterion were suggested in ABMR diagnosis. C4d and molecular classifiers were recognized as surrogate markers for DSA. The removal of the term “acute” from “acute/active” ABMR was suggested, to mention it simply as “active” ABMR. Tubulitis should be noted both within and outside of scarred areas. It is suggested to score tubulitis independently both in areas of preserved cortex (t score) and within areas of cortical IFTA (t-IFTA score), providing that severely atrophic tubules are not scored. The diagnostic criteria for CA TCMR were modified. In addition to i-IFTA score of ≥2, CA TCMR requires (1) at least a moderate degree of total cortical inflammation (ti score ≥2) and (2) moderate tubulitis involving cortical tubules other than severely atrophic tubules (t or t-IFTA score ≥2). The most recent, XV Banff conference was held in conjunction with the annual meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh, USA, in 2019.[10] It focused on refining recent updates to the classification of ABMR, CA TCMR, and borderline (suspicious) for acute TCMR, advances from the Banff working groups, and standardization of molecular diagnostics. This recent update supported 2017 Banff criteria for CA TCMR, but also suggested to indicate additionally, the level of active inflammation in the non-scarred cortex (i score). In cases of CA TCMR associated with i-IFTA, inflammation within non-scarred areas (i score) meeting criteria for additional borderline acute TCMR or acute TCMR Grade IA or IB, should also be specifically reported as a separately reported diagnosis. This also applies to cases where intimal arteritis (v score) is present in addition to CA TCMR. In addition, in the latest Banff update of 2019, a new classification of polyomavirus nephropathy (PVN) was proposed based on two histologic markers predictive for graft survival: the Banff interstitial fibrosis (ci) score and a new score termed “the intrarenal polyomavirus load level (pvl).” The pvl score is based on the fraction of tubules with evidence of polyomavirus replication either by light microscopy or immunohistochemical staining of epithelial cell nuclei for SV40 large T antigen (pvl1 ≤1%, pvl2 >1%, and <10%, pvl3 ≥10%). The pvl and ci scores were used to define 3 PVN classes (Table 1).[10]Table 1.: Updated Banff 2019 classification of kidney allograft pathology.[ 10 ]In conclusion, the updated Banff diagnostic criteria for kidney allograft rejection and related lesions have led to improved diagnostic accuracy and better clinicopathologic correlations. The need for the development of additional diagnostic modalities, including molecular diagnostics will be addressed at the XVI Banff meeting, which will be held in Banff, Canada, celebrating the 30-year anniver-sary at the original location of its inception. Conflict of interest: None declared.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,721
Score d'incertitude au seuil0,742

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,038
Tête enseignante GPT0,308
Écart entre enseignants0,270 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission1
Résumé présentoui

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