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Enregistrement W2905506084 · doi:10.1182/blood-2018-99-113177

Evaluation of Sustained Minimal Residual Disease (MRD) Negativity in Relapsed/Refractory Multiple Myeloma (RRMM) Patients (Pts) Treated with Daratumumab in Combination with Lenalidomide Plus Dexamethasone (D-Rd) or Bortezomib Plus Dexamethasone (D-Vd): Analysis of Pollux and Castor

2018· article· en· W2905506084 sur OpenAlexaff
Hervé Avet‐Loiseau, Jesús F. San Miguel, Tineke Casneuf, Shinsuke Iida, Sagar Lonial, Saad Z. Usmani, Andrew Spencer, Philippe Moreau, Torben Plesner, Katja Weisel, Jon Ukropec, Linda Okonkwo, Sonali Trivedi, Christopher Joseph Velas, Xiang Qin, Ming Qi, Christopher Chiu, Nizar J. Bahlis

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensInstitute of Cancer ResearchUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésDaratumumabLenalidomideMedicineInternal medicineOncologyMinimal residual diseaseMultiple myelomaDexamethasoneBone marrow

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Daratumumab (DARA) is a human IgGκ mAb targeting CD38 with both direct on-tumor and immunomodulatory mechanisms of action, and has been approved as monotherapy for RRMM and in combination with standard of care (SOC) regimens for RRMM and newly diagnosed MM (NDMM). Across three phase 3 DARA studies in RRMM and NDMM, DARA plus SOC reduced the risk of progression or death by ≥50%, enabled a doubling of CR rates, and elicited a ≥3-fold increase in MRD-negative rates. Among MRD-negative RRMM pts, pts treated with D-Rd or D-Vd rapidly achieved MRD negativity and demonstrated prolonged progression-free survival (PFS) vs MRD-positive pts (Avet-Loiseau H, et al. ASH 2016. Abstract 246). MRD assessment is being investigated as a potential surrogate for established endpoints such as overall survival (OS). When measured sequentially, sustained MRD-negativity provides an index of deep clinical responses that may provide a more robust assessment of disease control (Kumar S, et al. Lancet Oncol 2016. 17[8]:e328-e346). Here, we evaluate sustained MRD negativity with DARA plus SOC regimens and its association with PFS/OS outcomes in RRMM. Methods: Eligible pts in POLLUX and CASTOR received ≥1 prior line of therapy and were randomized (1:1) to receive SOC treatment regimens ± DARA. Pts in the POLLUX study were given lenalidomide (25 mg PO) on Days 1-21 and dexamethasone (40 mg) once per week in each 28-day cycle ± DARA (16 mg/kg IV) given weekly for Cycles 1-2, Q2W for Cycles 3-6, and Q4W thereafter. CASTOR pts received 8 cycles (21 d/cycle) of bortezomib (1.3 mg/m2 SC) on Days 1, 4, 8, and 11 and dexamethasone (20 mg) on Days 1, 2, 4, 5, 8, 9, 11, and 12 ± DARA (16 mg/kg IV) given weekly for Cycles 1-3, Q3W for Cycles 4-8, and Q4W thereafter. MRD was assessed at the time of suspected CR and at 3 and 6 months following confirmed CR in POLLUX, and at time of suspected CR and 6 and 12 months following the first treatment dose in CASTOR. Additional MRD evaluation was required in both studies every 12 months post-CR. MRD was assessed via next generation sequencing using the clonoSEQ® assay V2.0 (Adaptive Biotechnologies, Seattle, WA). Sustained MRD negativity was defined as the maintenance of MRD negativity in the bone marrow confirmed ≥6 or ≥12 months apart and was evaluated in the intent-to-treat (ITT) population. Sustained MRD negativity was also evaluated among ≥CR pts to account for different sustained MRD negativity rates between treatment arms. Results: A total of 569 (D-Rd, n = 286; Rd, n = 283) pts in POLLUX and 498 pts (D-Vd, n = 251; Vd, n = 247) in CASTOR were randomized; median (range) number of prior lines received was 1 (1-11) and 2 (1-10), respectively. Median duration of follow up was 39.5 months in POLLUX and 31.3 months in CASTOR for this analysis. Using the ≥6-month sustained MRD cutoff, a significantly higher proportion of pts achieved sustained MRD negativity for ≥6 months when treated with D-Rd vs Rd (16% vs 0.7%; P <0.0001) and D-Vd vs Vd (9% vs 1%; P = 0.0001) among the ITT population. Among ≥CR pts, the proportion of pts with sustained MRD negativity remained higher for pts treated with D-Rd vs Rd (30% vs 3%; P <0.0001) and D-Vd vs Vd (31% vs 13%; P = 0.11). While significantly fewer pts receiving SOC alone achieved sustained MRD negativity, sustained MRD negativity was associated with longer PFS and OS in all treatment arms vs pts without sustained MRD negativity in the ITT population (Figure 1). For the ≥12-month sustained MRD cutoff, more pts achieved sustained MRD negativity when receiving D-Rd vs Rd (13% vs 0.4%; P <0.0001) and D-Vd vs Vd (3% vs 0%; P = 0.0074) in the ITT population. Similar trends were observed for sustained MRD negativity rates among ≥CR pts treated with D-Rd vs Rd (24% vs 2%; P <0.0001) and D-Vd vs Vd (11% vs 0%; P = 0.19). Achievement of sustained MRD negativity for ≥12 months also consistently demonstrated longer PFS and OS for DARA-containing regimens vs those without sustained MRD negativity in the ITT population (Figure 2). Additional analyses, including an analysis of baseline pt characteristics for pts with sustained MRD negativity, will be presented at the meeting. Conclusions: DARA combinations with SOC regimens enable a significantly higher proportion of pts to achieve deep and durable responses of ≥CR and MRD negativity at 10-5. Importantly, the ability to reach durable MRD negativity is associated with prolonged survival, suggesting that achieving durable MRD negativity should be a treatment goal for RRMM pts. Disclosures San-Miguel: Sanofi: Honoraria; Novartis: Honoraria; BMS: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Roche: Honoraria. Casneuf:Janssen Research & Development: Employment. Iida:Chugai: Research Funding; Astellas: Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Kyowa-Hakko Kirin: Research Funding; MSD: Research Funding; Gilead: Research Funding; Toyama Chemical: Research Funding; Teijin Pharma: Research Funding; Sanofi: Consultancy; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Ono: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Lonial:Amgen: Research Funding. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Spencer:Celgene: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Honoraria, Research Funding, Speakers Bureau; Amgen: Honoraria, Research Funding; BMS: Research Funding; Takeda: Honoraria, Research Funding, Speakers Bureau; STA: Honoraria. Moreau:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Plesner:Celgene: Other: Independent Response Assessment Comittee; Janssen: Consultancy. Weisel:Amgen, BMS, Celgene, Janssen, Juno, Sanofi, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen, BMS, Celgene, Janssen, and Takeda: Honoraria; Amgen, Celgene, Janssen, and Sanofi: Research Funding. Ukropec:Janssen Scientific Affairs, LLC: Employment. Okonkwo:Janssen Research & Development, LLC: Employment. Trivedi:Janssen Research & Development, LLC: Employment. Velas:Janssen Research & Development, LLC: Employment. Qin:Janssen Research & Development, LLC: Employment. Qi:Janssen Research & Development, LLC: Employment. Chiu:Janssen Research & Development, LLC: Employment. Bahlis:Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, 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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,033
Tête enseignante GPT0,306
Écart entre enseignants0,273 · 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'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

Citations19
Publié2018
Routes d'admission1
Résumé présentoui

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