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Enregistrement W2594442364 · doi:10.1182/blood.v128.22.675.675

Final Results of a Phase 2 Trial of Extended Treatment (tx) with Carfilzomib (CFZ), Lenalidomide (LEN), and Dexamethasone (KRd) Plus Autologous Stem Cell Transplantation (ASCT) in Newly Diagnosed Multiple Myeloma (NDMM)

2016· article· en· W2594442364 sur OpenAlexaff
Todd M. Zimmerman, Noopur Raje, Ravi Vij, Donna Reece, Jesús G. Berdeja, Leonor A Stephens, Kathryn McDonnell, Cara A. Rosenbaum, Jagoda Jasielec, Paul G. Richardson, Sandeep Gurbuxani, Jennifer Nam, Erica Severson, Brittany Wolfe, Shaun Rosebeck, Andrew Stefka, Dominik Dytfeld, Kent A. Griffith, Andrzej Jakubowiak

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésCarfilzomibLenalidomideMultiple myelomaMedicineAutologous stem-cell transplantationTransplantationDexamethasoneOncologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction In a phase 1/2 study designed to assess KRd w/o ASCT, KRd provided a high rate of stringent complete response (sCR) (55%) in NDMM patients (pts) after a median of 24 cycles and 47.5 months (mo) of follow-up (f/u), with 4-year (yr) progression-free survival (PFS) and overall survival (OS) rates of 64% and 93%, respectively (Jakubowiak et al. Blood. 2012;120:1801-9; Jakubowiak et al, EHA 2016). To further improve response and outcomes, we designed a phase 2 study to assess KRd with ASCT. Methods The study enrolled ASCT-eligible pts with NDMM requiring tx per International Myeloma Working Group (IMWG) criteria with no age limitation. Pts received initial four 28-day cycles of KRd induction with CFZ IV 20/36 mg/m2 on Days (D) 1, 2, 8, 9, 15, 16 (20 mg/m2 given on D1, 2 in Cycle [C] 1 only); LEN PO D1-21 at 25 mg, DEX PO 40 mg/week followed by stem cell collection using G-CSF and plerixafor, melphalan 200 mg/m2 and ASCT, and KRd consolidations (C 5-8) using the same doses and schedule except LEN 15 mg in C5 with option to escalate to prior dose and DEX reduced to 20 mg weekly. After C8, pts received maintenance KRd for an additional 10 cycles using the same doses as in C8 except CFZ on D 1, 2, 15, 16 only. Single-agent LEN was recommended off-study after C18. The primary endpoint was rate of sCR at the end of C8, with minimal residual disease (MRD) among secondary endpoints. We estimated that an sCR rate of 50% or better for KRd plus ASCT would indicate superior outcome compared with a historical sCR rate of 30% for KRd w/o ASCT at this time point. Responses were assessed using current IMWG criteria. MRD was evaluated by 10-color multiparameter flow cytometry (MFC) with 10-4-10-5 sensitivity and by next generation sequencing (NGS) at landmark time-points: after KRd induction (after C4), ASCT, and KRd consolidation (after C8); at the end of KRd tx (after C18); and then yearly. NGS analysis was done using the immunoSEQ® MRDplatform with a threshold at 10-6 for MRD negativity. MRD-negative status required CR, as per current IMWG criteria. Results As of July 1, 2016, enrollment was completed (76 pts); 72 pts completed KRd induction, 71 ASCT, 66 KRd consolidation, and 44 KRd maintenance with 25 pts remaining on protocol tx. Median age was 59 y (range 40-76), ISS stage II/III 57%, high-risk cytogenetics 36% as per IMWG criteria. Efficacy and toxicity data were available for 73 pts. Based on January 1, 2016 cut-off date, response rates at the end of C8 were 96% VGPR, 73% CR, and 69% sCR. The rate of sCR has been improving during the post-transplant phase of the KRd tx, from 20% post-ASCT to 69% after 4 cycles of KRd consolidation (C8), and to 82% after 10 additional cycles of KRd maintenance (C18). MRD rates in pts evaluated to date were 82% by MFC (N=33) and 66% by NGS (N=29) at the end of C8, and 90% (N=20) and 71% (N=16), respectively, at the end of C18. MRD rates in a subset of high-risk pts evaluated for MRD were 90% by MFC (10 of 11 pts with high-risk) and 63% by NGS (6 of 8 pts) at the end of C8, and 100% (6 of 6 pts) by MFC and 80% (4 of 5) by NGS at the end of C18. After median f/u of 17.5 mo, 2-yr PFS was 97% and 2-yr OS 99% for all 76 pts. For NGS and/or MFC MRD-negative pts at the end of C8, 2-yr PFS/OS was 100% and for MRD-positive/unknown PFS was 93% and OS 98%. For high-risk disease pts (N=27), 2-yr PFS was 96%. KRd-related adverse events (AEs) were generally Grade (G) 1/2, and included (any G) for hematologic AEs thrombocytopenia (57%), lymphopenia (39%), anemia (39%), and neutropenia (28%) and for non-hematologic AEs fatigue (53%), peripheral neuropathy (39%), diarrhea (3%), and infection (34%). Most common G3/4 AEs were lymphopenia (28%), neutropenia (18%), and infections (8%). Two of 71 pts evaluated pre-transplant had asymptomatic decrease of ejection fraction (EF) 45-50%, with no baseline ECHO or MUGA, all remaining pts had normal pre-transplant EF. Updated results, including larger sample of MRD data, will be presented at the meeting, with nearly all patients completing 18 KRd cycles at the next data cut. Conclusions These results show that extended KRd tx with incorporated ASCT results in high rates of sCR and MRD-negative disease in both standard and high risk disease, which correspond to high rates of PFS and OS. These results compare favorably with data from the KRd w/o ASCT study, based on pre-specified improvement of sCR rate at the end of 8 cycles and beyond, and with historical studies in NDMM. These results will require validation in ongoing and planned randomized trials. Disclosures Vij: Janssen: Honoraria; Amgen: Honoraria, Research Funding; Karyopharm: Honoraria; Celgene: Consultancy; Takeda: Honoraria, Research Funding; Novartis: Honoraria; Bristol-Myers Squibb: Honoraria. Reece:Merck: Research Funding; Otsuka: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding. Berdeja:Abbvie, Acetylon, Amgen, Bluebird, BMS, Calithera, Celgene, Constellation, Curis, Epizyme, Janssen, Karyopharm, Kesios, Novartis, Onyx, Takeda, Tragara: Research Funding. Rosenbaum:Celgene: Speakers Bureau. Richardson:Celgene: Membership on an entity's Board of Directors or advisory committees. Dytfeld:Janssen Poland: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees. Jakubowiak:BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; SkylineDx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, 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)0,003
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 randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,038
Tête enseignante GPT0,300
Écart entre enseignants0,263 · 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 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

Citations45
Publié2016
Routes d'admission1
Résumé présentoui

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