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Enregistrement W2473614468 · doi:10.1182/blood.v126.23.1982.1982

Myeloma Canada Research Network (MCRN)-001 Trial Utilizing Bortezomib (btz)-Based Induction, Enhanced Conditioning with IV Busulfan + Melphalan (BuMel) and Lenalidomide (len) Maintenance in Multiple Myeloma Patients Eligible for Autologous Stem Cell Transplant (ASCT): A National Canadian Study Evaluating Achievement of Minimal Residual Disease (MRD) Negativity and Involved Serum HevyliteTMÂ chain (HLC) Normalization

2015· article· en· W2473614468 sur OpenAlexaffabout
Donna Reece, Giovanni Piza Rodriguez, Mariela Pantoja, Darrell White, Christopher P. Venner, Julie Stakiw, Michaël Sébag, Terrance Comeau, Kevin Song, Jean Roy, Leonard Minuk, Jason Tay, Vishal Kukreti, Suzanne Trudel, Prica Anca, Rodger E. Tiedemann, Christine Chen, Harminder Paul

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensLondon Health Sciences CentreHôpital Maisonneuve-RosemontUniversity of British ColumbiaMcGill UniversitySaint John Regional HospitalSaskatchewan Cancer AgencyUniversity of AlbertaQueen Elizabeth II Health Sciences CentreOttawa HospitalPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMelphalanLenalidomideBusulfanMultiple myelomaMaintenance therapyInternal medicineUrologyThalidomideSurgeryOncologyTransplantationHematopoietic stem cell transplantationChemotherapy

Résumé

récupéré en direct d'OpenAlex

Abstract As therapy for MM improves, methods more sensitive than conventional serum/urine electrophoresis/immunofixation are required to optimally evaluate response. Our phase 2 multi-center clinical trial, conducted in 10 Canadian centers, utilized serial bone marrow aspirate (BMA) samples for MRD analysis by 8-color multiparameter flow cytometry (MFC), along with serum Hevylite assay of the involved heavy light chains (HLC), to assess responses after ASCT and during maintenance therapy. After btz-based induction therapy (usually CyBorD), pts without progression received enhanced conditioning with BuMel (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 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. From 03/2013 - 07/2015, 122 newly diagnosed pts provided BMA samples for MRD analysis. To date, 70 pts (target 78), have completed induction therapy and undergone ASCT; 8 others provided pre-induction samples and are expected to be enrolled. 44 of the 122 (36%) who provided BMA samples did not proceed to BuMel due to: poor samples-4 pts (3.2%); MM not confirmed-3 pts (2.5%); prior therapy-1 pt (0.8%); death during induction-1 pt (0.8%); consent withdrawal/opted for standard conditioning-19 pts (15.6%); and no ASCT-16 pts (13.1%; 8 were unfit, 4 had comorbidities, 2 progressed, 1 failed mobilization and 1 received tandem ASCT for high-risk MM). Median follow-up is 17.4 mos (range: 6.3-25.6). Median age is 57 (34-69); 64% are male. Median serum β2-microglobulin level is 3.07 mg/L (1.5-20) and albumin 37 g/L (2.8-48.1); 31 pts have ISS stage I; 18 stage II; 15 stage III MM and 6 have missing data. Ig subtype includes IgGκ in 30 (43%), IgGλ in 14 (20%), IgAκ in 8 (12%), IgAλ in 9 (13%), κ in 5 (7%); λ in 1 (1%) and missing data in 3 pts (4%). Post-ASCT, 14 SAEs have occurred: Grade 3 atrial fibrillation (2), acute kidney injury (3), increased creatinine (1), upper respiratory infection (2), febrile neutropenia (2), bacteremia (1), hypoxia (1) and lung infection (1) and Grade 4 sepsis (1). There have been no ASCT-related deaths; 4 pts have progressed. The best conventional Ig response post-induction in the 66 pts with available data is CR in 5 (7.6%), VGPR in 25 (38%), PR in 31 (47%), MR in 4 (6%) and SD in 1 (1.5%). The Ig response at day 100 in the 60 evaluable pts includes CR in 10 (17%), VGPR in 30 (50%), PR in 18 (30%), MR in 1 (1.5%) and SD in 1 (1.5%). MRD negativity improved from 18/67 (27%) after induction to 22/60 (37%) at day 100 (Table 1). Among evaluable pts, 83.3% of those after induction and 68.2% of those at day 100 who were MRD-negative had normal involved HLC ratios, while 42.6% and 51.5% of those who were MRD-positive, respectively, had normal ratios. Table 1. Response Rates by Conventional Serum/Urine Parameters and Marrow Flow Cytometry for MRD MRD Negativity by Conventional Ig Response # Evaluable Normal Hevylite ratio (# normal /evaluable) (%) # MRD Negative (%) CR VGPR PR MR SD Missing Total MRD(-) Total MRD(-) Total MRD(-) Total MRD(-) Total MRD(-) Total MRD(-) After Induction 67 15/18 (83.3%) 18 (27%) 5 4 25 9 31 5 4 0 1 0 1 0 Day 100 Post-ASCT 60 15/22 (68.2%) 22 (37%) 10 4 30 16 18 2 1 0 1 0 0 0 Conclusions: 1) IV BuMel conditioning + ASCT was well-tolerated with few SAEs and no ASCT-related deaths; 2) at day 100 post-ASCT, 97% had achieved ≥ PR (≥ VGPR in 67% and CR in 17%); 3) MRD negativity rates improved from 27% to 37% after ASCT; 3) conventional Ig and MRD responses were often discordant as only 40% of CR pts were MRD-negative at day 100; 4) the majority of MRD-negative patients also had normalization of their involved HLC ratios; 5) further F/U is required to determine the rate of achievement of MRD negativity during maintenance therapy; relationships between conventional Ig response, MRD status and involved HLC ratio; and long-term outcomes with this approach. Disclosures Reece: Janssen: Consultancy, Honoraria, Research Funding; Osuka: Honoraria, Research Funding; Merck: Research Funding; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Millennium: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Off Label Use: Lenalidomide maintenance after autologous stem cell transplantation. White:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria. Venner:Amgen: Honoraria; Celgene: Honoraria, Research Funding; J&J: Honoraria, Research Funding. Sebag:Celgene: Honoraria; Janssen: Honoraria; Novartis: Honoraria. Song:Celgene: Honoraria; Otsuka: Honoraria; Janssen: Honoraria. Tay:Celgene: Honoraria; Janssen: Honoraria. Kukreti:Janssen: Honoraria; Celgene: Honoraria. Trudel:Amgen: Honoraria, Speakers Bureau; Oncoethix: Research Funding; BMS: Honoraria; Novartis: Honoraria; Celgene: Equity Ownership, Honoraria, Speakers Bureau; Trillium Therapeutics Inc.: Research Funding. Anca:Janssen: Honoraria; Celgene: Honoraria. Tiedemann:Janssen: Honoraria; Celgene: Honoraria. Chen:Celgene: Honoraria, Research Funding; Millennium: Research Funding; Janssen: Honoraria.

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)0,001
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 enseignants0,485
Score d'incertitude au seuil0,977

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
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 recherche0,0010,002
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 Opus0,069
Tête enseignante GPT0,316
Écart entre enseignants0,247 · 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
Publié2015
Routes d'admission2
Résumé présentoui

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