MétaCan
Menu
← Retour à la cohorte
Enregistrement W2595988118 · doi:10.1182/blood.v128.22.4632.4632

Myeloma Canada Research Network (MCRN)-001 ASCT Study of Busulfan + Melphalan (BuMel) Conditioning Followed By Lenalidomide (Len) Maintenance: Updated Results Including Serial Minimal Residual Disease (MRD) and Involved Serum Hevylite™ Chain (HLC) Ratio Assessments

2016· article· en· W2595988118 sur OpenAlexaffabout
Donna Reece, Giovanni Piza Rodriguez, Mariela Pantoja, Darrell White, Christopher P. Venner, Julie Stakiw, Michaël Sébag, Terrance Comeau, Kevin Song, Jean Roy, Martha Louzada, Arleigh McCurdy, Vishal Kukreti, Suzanne Trudel, Anca Prica, Rodger E. Tiedemann, Christine Chen, Harminder Paul

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensLondon Health Sciences CentreCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalHôpital Maisonneuve-RosemontUniversité de MontréalLeukemia & Lymphoma Society of CanadaUniversity of British ColumbiaMcGill University Health CentreSaint John Regional HospitalOttawa HospitalSaskatchewan Cancer AgencyQueen Elizabeth II Health Sciences CentrePrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMelphalanMinimal residual diseaseLenalidomideBusulfanMultiple myelomaInternal medicineMaintenance therapyAutologous stem-cell transplantationOncologyThalidomideSurgeryUrologyBone marrowTransplantationHematopoietic stem cell transplantationChemotherapy

Résumé

récupéré en direct d'OpenAlex

Abstract MRD negativity has become an important goal of the initial treatment of MM pts. Our phase 2 multi-center clinical trial, conducted in 10 major Canadian transplant centers, was designed to increase the MRD negativity rate after ASCT by using conditioning with 2 high-dose alkylating agents followed by len maintenance. In addition to conventional response criteria, this trial evaluated serial bone marrow aspirate (BMA) samples for MRD analysis by 8-color multiparameter flow cytometry (MFC) along with serum Hevylite™ assays of the involved HLC that were obtained before and after ASCT and during maintenance therapy. After bortezomib (btz)-based induction therapy off study, pts without MM progression received BuMel (busulfan 3.2 mg/kg IV days -5 to -3 or days -6 to -4 + melphalan 140 mg/m2 day -2 or day -3) conditioning, followed by ASCT on day 0. On day 100 post-ASCT, len 10 mg/day was started, escalated after 3 cycles to 15 mg/day if appropriate, and continued until progression. BMA and serum samples were shipped centrally for MRD and Hevylite analysis before induction therapy, before ASCT, on day 100 post-ASCT, every 3 mos for the 1st year and every 6 mos until progression. Between 03/2013 - 05/2016, 125 newly diagnosed pts provided BMA samples for MRD analysis. To date, 76 pts (target 78), have completed induction therapy and undergone ASCT; 2 pts have provided initial samples and are expected to be enrolled. 46 of the 125 (36.8%) who provided BMA samples did not proceed to BuMel due to: poor samples - 4 (3.2%); MM not confirmed - 3 (2.4%); prior therapy - 1 (0.8%); death during induction - 1 (0.8%); consent withdrawal/opted for standard conditioning - 21 (16.8%); and no ASCT - 16 (12.8%) (8 were unfit, 4 had comorbidities, 2 progressed, 1 failed mobilization and 1 underwent preferential tandem ASCT). Median follow-up is 27.4 mos (range: 10.4-37.6). Median age is 57 (34-69); 65.8% are male. Median serum β2-microglobulin level is 3.07 mg/L (1.5-20) and albumin 37 g/L (2.8-48.1); 34 pts have ISS stage I; 21 stage II; 17 stage III MM and 5 have missing data. Ig isotype includes IgGκ in 34 (44.7%), IgGλ in 16 (21.1%), IgAλ in 10 (13.2%), IgAκ in 9 (11.8%) and κ in 7 (9.2%). Post-ASCT, 26 SAEs have occurred: Grade 2: atrial fibrillation (1) and URI (1); Grade 3: atrial fibrillation (1), acute kidney injury (4), infectious enterocolitis (2), gallbladder infection (1), URI (1), febrile neutropenia (3), bacteremia (1), pain in extremity (1), hypoxia (1), pleural effusion (1), and 3 lung infection (4); and Grade 4: sepsis (1), AML [with spontaneous regression] (1), respiratory distress (1) and acute kidney injury (1). There have been no ASCT-related deaths; 11(14.4%) pts have progressed. The best conventional Ig response post-induction in the 76 evaluable pts is CR in 6 (7.9%), VGPR in 29 (38.2%), PR in 35 (46.1%), MR in 5 (6.6%) and SD in 1 (1.3%). At day 100 after ASCT, the Ig response in the 73 evaluable pts is CR in 9 (12.3%), VGPR in 41 (56.2%), PR in 22 (30.1%) and MR in 1 (1.4%). The rates of MRD negativity also increased from 29% after btz-based induction to 41%, while the rates of achievement of a normal HLC ratio were 50% after induction and 48% at day 100 (Table 1). Among evaluable pts, 77.3% of those after induction and 53.3% of those at day 100 who were MRD-negative also had had normal involved HLC ratios, while 38.9% and 44.2% of those, who were MRD-positive, respectively, had had normal involved HLC ratios. At month 6 and 12 post-ASCT, 43% and 35% of evaluable pts, respectively, are MRD-negative. Individual patient patterns of len dose, MRD negativity and involved HLC ratios are under assessment and will be presented. Conclusions: 1) IV BuMel conditioning + ASCT is well-tolerated with few SAEs and no ASCT-related deaths; 2) at day 100 post-ASCT, 98.6% had achieved ≥ PR (≥ VGPR in 68.5% and CR in 12.3%); 3) MRD negativity rates improved from 29% to 41% after ASCT; 4) the rates of normalization of the involved HLC ratio remained stable (50% to 48%) pre- and post-ASCT; 4) conventional Ig and MRD responses were often discordant as only 41% of CR pts were MRD-negative at day 100; 5) the majority of MRD-negative patients (53.3%) also had normalization of their involved HLC ratios; 5) with a median follow-up of over 2 years, only 14% of pts have progressed; 6) the serial marrow samples mandated by this study will allow determination of relationships between len dose, conventional Ig response rates, MRD status and involved HLC ratios as these pts are followed for longer periods of time. Disclosures Reece: Takeda: Consultancy, Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Merck: Research Funding; BMS: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. White:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria. Venner:Takeda: Honoraria; Celgene: Honoraria, Research Funding; J+J: Research Funding; Janssen: Honoraria; Amgen: Honoraria. Stakiw:Roche: Research Funding; BMS: Honoraria; Novartis: Honoraria, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Jansen: Honoraria, Speakers Bureau. Sebag:Celgene: Honoraria; Novartis: Honoraria; Janssen: Honoraria. Comeau:Seattle Genetics: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy. Song:Otsuka: Honoraria; Janssen: Honoraria; Celgene: Honoraria, Research Funding. Louzada:Pfizer: Honoraria; Bayer: Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. McCurdy:Celgene: Honoraria. Kukreti:Celgene: Honoraria. Trudel:Glaxo Smith Kline: Honoraria, Research Funding; Celgene: Honoraria; Novartis: Honoraria; Oncoethix: Research Funding. Prica:Janssen: Honoraria; Celgene: Honoraria. Tiedemann:Novartis: Honoraria; Takeda Oncology: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; BMS Canada: Honoraria. Chen:Takeda: Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding.

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)0,002
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,246
Score d'incertitude au seuil0,489

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,045
Tête enseignante GPT0,340
Écart entre enseignants0,295 · 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

Citations1
Publié2016
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueBlood→Même sujetMultiple Myeloma Research and Treatments→Travaux en français237 207→