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Enregistrement W2903157580 · doi:10.1182/blood-2018-99-115024

Primary Mediastinal B-Cell Lymphoma: Evaluation of Clinicopathologic Diagnosis Compared to Gene Expression Based Diagnosis in a Clinical Trial with CD30+ B-Cell Lymphomas

2018· article· en· W2903157580 sur OpenAlexaff
Jakub Svoboda, Steven M. Bair, Christian Steidl, Marco Ruella, Daniel J. Landsburg, Sunita D. Nasta, Stefan K. Barta, Majid Nejati, James N. Gerson, Lauren E. Strelec, Matthew R. Youngman, Elise A. Chong, Olga A. Kutovaya, Stacy Hung, Agata M. Bogusz, Megan S. Lim, Stephen J. Schuster

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensBC Cancer AgencySpinal Cord Injury BC
Organismes subventionnairesnon disponible
Mots-clésMedicineLymphomaCD30Clinical trialBiopsyPathologyFollicular lymphomaDiffuse large B-cell lymphomaLarge-cell lymphomaOncologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background: PMBCL is a unique subtype of aggressive B-cell lymphoma representing about 5% of lymphoma cases. The diagnosis is generally based on a combination of clinical features (e.g., mediastinal mass) and pathological findings on tissue biopsy (e.g., large neoplastic B-cells with variable CD30 positivity by immunohistochemistry). However, the histopathologic diagnostic criteria are not well defined and the distinction between PMBCL and diffuse large B-cell lymphoma (DLBCL) or gray zone lymphoma (GZL) involving the mediastinum can be challenging. Most PMBCL trials use the traditional diagnostic criteria for study entry. Specific treatment approaches based on results of these trials are designed for patients with PMBCL. In this study, we hypothesized that a gene expression based assay that characterizes the molecular signature of PMBCL using formalin-fixed, paraffin-embedded (FFPE) tissue may improve the diagnostic criteria and allow more accurate interpretation of results for lymphoma patients enrolled in clinical trials. Methods: This exploratory study compared the PMBCL diagnosis established by clinicopathologic criteria alone to the diagnosis assigned by a combination of clinicopathologic features and gene expression-based assay on FFPE tissue specimens of patients enrolled in a multisite phase I/II prospective trial using brentuximab vedotin (BV) in combination with rituximab - cyclophosphamide-hydroxydoxorubicin-prednisone (R-CHP) for CD30+ B-cell lymphomas (Svoboda, Blood 2017). The original diagnostic categories of PMBCL vs. DLBCL vs. GZL were assigned by investigators based on traditional clinicopathologic features. For exploratory Nanostring based diagnostic categorization, we used previously described and validated Lymph3Cx assay which consists of 64 probes with cut‐points defined at the 0.1 and 0.9 probability scores to distinguish between DLBCL and PMBCL (Mottok, Hematol Oncol 2017). The tissue was examined by a hematopathologist for adequate tumor content and nucleic acids were extracted from 10 mm FFPE scrolls or unstained slides. Survival curves were generated for PMBCL patients as categorized by investigator assessment alone and by investigator assessment plus molecular classification using STATA. Results: We enrolled 31 treatment-naïve patients with CD30+ B-cell lymphomas between January 2014 and April 2017 (NCT01994850). Based on investigator assessment, patients were categorized as PMBCL (N=23), DLBCL (N=6), and GZL (N=2). As of June 15, 2018, we obtained and analyzed diagnostic FFPE tissue using the Lymph3Cx assay on 14 pts with all 3 subtypes of CD30+ B-cell lymphomas: PMBCL (N=11), DLBCL (N=2), and GZL (N=1). Of 11 pts with PMBCL by investigator assessment alone, 8 pts (73%) had Lymph3Cx probability scores > 0.9 which was consistent with a diagnosis of PMBCL by gene expression; 2 pts (18%) scored in the indeterminate category (0.1 to 0.9); 1 pt (9%) scored as DLBCL (< 0.1). All 8 pts with a concordant diagnosis of PMBCL by investigator assessment and gene expression assay achieved complete remission (CR) and remain progression free after completing BV+R-CHP with median follow-up of 18 months. However, 1 pt re-classified as DLBCL by Lymph3Cx and 1 of 2 pts with an indeterminate score by Lymph3Cx achieved only partial responses and ultimately progressed; 1 pt with an indeterminate score remains in CR. None of the non-PMBCL pts in our exploratory analysis (2 DLBCL; 1 GZL) as assessed by investigators were categorized as PMBCL by Lymph3Cx. The CR rate for patients categorized as PMBCL by investigator assessment alone was 82% compared to 100% in those categorized as PMBCL by both investigator and gene expression assay (Table 1). The reportable progression free survival would also be different for these two cohorts (Figure 1). We will complete Lymph3Cx testing of diagnostic tissue for all 31 enrolled patients with CD30+ B-cell lymphomas enrolled on our clinical trial by the meeting. Conclusion: Preliminary results of this ongoing study suggest that a diagnosis of PMBCL by clinicopathologic assessment alone that is not supported by molecular classification may include non-PMBCL pts and affect treatment outcomes. We recommend that future clinical trials for PMBCL include gene expression based diagnostic assays to improve diagnostic accuracy and interpretation of results. Disclosures Svoboda: TG Therapeutics: Research Funding; Kyowa: Consultancy; KITE: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding; Regeneron: Research Funding; Merck: Research Funding; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding. Steidl:Seattle Genetics: Consultancy; Juno Therapeutics: Consultancy; Roche: Consultancy; Tioma: Research Funding; Nanostring: Patents & Royalties: patent holding; Bristol-Myers Squibb: Research Funding. Ruella:University of Pennsylvania: Patents & Royalties. Landsburg:Curis: Consultancy, Research Funding; Takeda: Consultancy. Dwivedy Nasta:Takeda/Millenium: Research Funding; Incyte: Research Funding; Debiopharm: Research Funding; Pharmacyclics: Research Funding; Rafael/WF: Research Funding; Aileron: Research Funding; Roche: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Merck: Other: DSMC. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Chong:Novartis: Consultancy. Schuster:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis Pharmaceuticals Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Honoraria, Research Funding; Dava Oncology: Consultancy, Honoraria; Nordic Nanovector: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Merck: Consultancy, Honoraria, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,012
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,012
Score d'incertitude au seuil0,061

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0120,009
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,080
Tête enseignante GPT0,352
Écart entre enseignants0,272 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
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

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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