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Enregistrement W4379981977 · doi:10.1002/hon.3164_288

Indolent lymphoma: Bendamustine, rituximab and acalabrutinib in Waldenstroms Macroglobulinemia (BRAWM)

2023· article· en· W4379981977 sur OpenAlexaffabout
Neil L. Berinstein, Kees-Peter de Roos, G. Klein, Rebecca F. McClure, Nicholas Forward, Mona Shafey, Alexandra Nikonova, David MacDonald, Diego Villa, Irwindeep Sandhu, Mohammed A. Aljama, Jean-François Larouche, KATHRYN MANGOFF

Notice bibliographique

RevueHematological Oncology · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Lymphocytic Leukemia Research
Établissements canadiensUniversité LavalCanadian Red Cross SocietyHealth CanadaBaker Hughes (Canada)Queen Elizabeth II Health Sciences CentreHealth Sciences CentreSunnybrook HospitalSunnybrook Health Science CentreAgricultural Research Institute of OntarioHealth Sciences NorthJuravinski Cancer CentreMcGill University Health Centre
Organismes subventionnairesnon disponible
Mots-clésBendamustineMedicineRituximabAdverse effectInternal medicineWaldenstrom macroglobulinemiaLymphoplasmacytic LymphomaClinical trialIbrutinibOncologyLymphomaLeukemiaChronic lymphocytic leukemia

Résumé

récupéré en direct d'OpenAlex

Background: Waldenström’s macroglobulinaemia (WM) is an uncommon lymphoproliferative disorder. Many options are available, however, an optimal first-line therapy for WM has not be defined. We postulated that combining bendamustine and rituximab (BR) with a next generation BTK inhibitor would result in deeper responses as measured by complete response (CR) and very good partial response (VGPR) rates, and provide a longer duration of response. Objectives: The primary objective of this trial is to document the CR and VGPR rates Methods: The BRAWM clinical trial combines BR with acalabrutinib in a fixed duration treatment course including six cycles of BR and 12 months of acalabrutinib. This trial is taking place at 8 clinical sites across Canada and 33 patients have been enrolled, with a recruitment goal of 59. Results: A pre-defined interim analysis of the first 30 enrolled patients showed; median age of patients was 66; 25 were male; two patients were low risk, 14, intermediate and 15 high risk. Seventeen patients completed combination therapy, 9 completed monotherapy and 2 were followed-up at 18 months (6 months post therapy). Clinical results to date: Two patients discontinued treatment early; 1 at cycle 7 (with a VGPR) but experienced an adverse event requiring treatment; 1 at cycle 3 with possible disease progression. There were 186 treatment related adverse events (TRAEs) among 25 of 30 participants; 5 participants did not experience a TRAE; 163 of these occurred during combination therapy; 23 during monotherapy in 7 of 17 participants, where 10 participants did not experience a TRAE. During combination therapy, 16 of the 163 TRAE’s were grade 3; neutropenia (n = 8), including 2 that were febrile neutropenia, n = 1 for each: atrial fibrillation, transaminitis, cellulitis, fatigue and pulmonary emphysema. An additional five were also considered serious and included febrile neutropenia (n = 2), and n = 1 for each fever, allergic reaction and bowel obstruction. During monotherapy, there were no serious TRAEs. There were 2 grade 3 events during monotherapy in two different patients; decreased neutrophil count, and syncope. There were 21 dose interruptions in 11 participants, all but one of whom returned to regular dosage. Of assessed patients, 20/20 have MyD88 mutations, 4/20 have a CXCR4 mutation, and none had a TP53 mutation. Minimal residual disease (MRD) analysis using next generation sequencing of the IgV regions will be reported. Conclusions: Bendamustine, rituximab and acalabrutinib front-line therapy for WM is safe and well tolerated and initial clinical results show that this treatment induces a high percentage of VGPRs. The research was funded by: AstraZeneca Keywords: Combination Therapies, Indolent non-Hodgkin lymphoma Conflicts of interests pertinent to the abstract. N. L. Berinstein Consultant or advisory role: AstraZeneca Research funding: AstraZeneca, Merck, IMV N. Forward Honoraria: AstraZeneca, AbbVie, BeiGene, Celgene/BMS, IMV, Kite, Janssen, Pfizer, Roche, Servier Research funding: Astellas, AstraZeneca, IMV, Merk, MorphoSys, Seattle Genetics, Roche Other remuneration: Speaker Fees: Pfizer, BeiGene, AstraZeneca M. Shafey Consultant or advisory role: Jansen, Roche Canada, Kite/Gilead, Novartis, BeiGene, Incyte, Abbvie, BMS, AstraZeneca A. Nikonova Consultant or advisory role: Forus, Janssen, Astra Zeneca, Apotex, Incyte Educational grants: Janssen D. MacDonald Honoraria: Abbvie, Astra Zeneca, Beigene, BMS, Incyte, Kite Gilead, Roche, and Seattle Genetics D. Villa Consultant or advisory role: AZ, BeiGene, Janssen, Roche, Kite/Gilead, Merck, BMS/Celgene, ONO Pharmaceuticals. Honoraria: AZ, BeiGene, Janssen, Roche, Kite/Gilead, Merck, BMS/Celgene, ONO Pharmaceuticals. Research funding: Roche, AstraZeneca I. Sandhu Honoraria: Celgene/BMS, Kite/Gilead, Janssen, Sanofi, FORUS, Pfizer M. Aljama Consultant or advisory role: Jansen, Sanofi, Pfizer, Beigene J. Larouche Consultant or advisory role: Incyte, Gilead Research funding: Incyte, Astra-Zeneca, Genmab

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,408
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
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 savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

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 Opus0,043
Tête enseignante GPT0,370
Écart entre enseignants0,327 · 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.

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

Citations2
Publié2023
Routes d'admission2
Résumé présentoui

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