First Report of the Myeloma Canada Research Network (MCRN)-001 Trial Utilizing Bortezomib-Based Induction, Enhanced Conditioning with IV Busulfan + Melphalan (BuMel) and Lenalidomide Maintenance: Feasibility of a National Canadian Study Based on Achievement of Minimal Residual Disease (MRD) Negativity
Notice bibliographique
Résumé
Abstract Conventional immunoglobulin (Ig) markers have been used to define multiple myeloma (MM) responses, but assessment of marrow for minimal residual disease (MRD) may provide better information on disease status/prognosis (Paiva B, et al. Blood 2008; 112: 4017). We therefore initiated a national multi-center ASCT trial with the goal of producing a high rate of MRD-negativity by using bortezomib (btz)-based induction, enhancing the conditioning regimen and utilizing post-ASCT maintenance. This phase 2 open label-trial was conducted in 10 Canadian centers. After btz-based induction (usually CyBorD) in the absence of disease progression, patients (pts) received BuMel conditioning (IV busulfan 3.2 mg/kg days -5 to -3 or days -6 to -4 + melphalan 140 mg/m2 day -2 or day -3), followed by ASCT on day 0. On day 100 post-ASCT, lenalidomide (len) 10 mg/day was commenced, escalated to 15 mg/day after 3 cycles if appropriate, and continued until disease progression. Bone marrow aspirate (BMA) samples were shipped centrally for MRD analysis by 15-color multiparameter flow cytometry (MFC) before any therapy, prior to ASCT, on day 100 post-ASCT, every 3 mos for the 1st year and every 6 mos thereafter until progression. Between 03/2013 - 07/2014, 99 newly diagnosed MM pts provided untreated BMA samples for MRD analysis. To date, 42 of a planned target of 78 pts have completed induction therapy have undergone ASCT and 39 are evaluable so far. 25 of the 99 (25%) who provided initial marrow samples did not meet criteria for enrollment: 3 (3%) had poor BMA samples; 3 (3%) did not have confirmed MM; 6 (6%) did not proceed with ASCT (1 due to progression); 1 (1%) had received dexamethasone prior to MRD analysis; 1 (1%) died during induction and 11 (11%) withdrew consent/opted for standard conditioning. Median age of the 39 evaluable pts is 53 (39-67); 64% are male. Median serum β2-microglobulin level is 3.64 mg/L (1.7-20) and albumin 37 g/L (2.8-48.1); 17 pts have ISS stage I; 9 have stage II; 9 have stage III MM and 4 have missing data. Ig subtype includes IgGκ in 16 (40%), IgGλ in 4 (10%), IgAκ in 5 (13%), IgAλ in 8 (21%), IgMλ in 1 (3%), κ in 1 (3%); non-secretory in 2 (5%) and no data in 2 pts (5%). Post-ASCT, only 4 SAEs have occurred: atrial fibrillation (2), acute kidney injury (1) and sepsis (1). There have been no ASCT-related deaths, and no pt has progressed at a median follow-up of 7.8 mos (range: 4.8-10.1). The best Ig response post-induction in the 31 pts with available restaging data is CR in 5 (16%), VGPR in 9 (29%), PR in 13 (42%), and SD in 1 (3%). 27 pts have reached day 100 post-ASCT and 8 pts have been formally evaluated. In these 8, the Ig response is CR in 2 (25%), VGPR in 5 (63%) and PR in 1 (12%). Table 1 summarizes MRD results to date. Table 1. Comparison of conventional Ig response rates and achievement of MRD negativity # Conventional Ig Responses [# MRD negative] Time point of assessment #Evaluable Total # MRD negative CR VGPR PR MR After btz-based induction 31 6 5 [3] 9 [1] 13 [2] 0 Day 100 post-ASCT 8 2 2 [2] 5[0] 1[0] 0 During len maintenance 5 1 0 5 [1] 0 0 Conclusions: 1) MFC performed on pre-therapy marrow samples to allow subsequent evaluation for MRD was successful in 97% of pts using a central lab; 2) IV BuMel was well-tolerated with few SAEs and no ASCT-related deaths; 3) MRD and conventional Ig responses may not correlate well; 4) Further F/U is required to determine the dynamics of MRD achievement and long term outcomes with this approach. Disclosures Reece: Novartis: Honoraria, Research Funding; BMS: Research Funding; Merck: Research Funding; Millennium: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Amgen: Honoraria. Off Label Use: Lenalidomide maintenance after ASCT. Venner:Celgene: Honoraria, Research Funding; Janssen: Honoraria. White:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Sebag:Novartis: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Song:Celgene: Honoraria; Otsuka: Honoraria; janssen: Honoraria. Tay:Celgene: Honoraria; Janssen: Honoraria. Kukreti:Celgene: Honoraria. Trudel:Glaxo Smith Kline: Honoraria, Research Funding; Novartis: Honoraria; Celgene: Honoraria; Oncoethix: Research Funding. Tiedemann:Celgene: Honoraria; Janssen: Honoraria. Chen:Millennium: Research Funding; Janssen: Honoraria; Celgene: 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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».