MétaCan
Menu
← Retour à la cohorte
Enregistrement W4405043418 · doi:10.1182/blood-2024-201057

Phase 3 Randomized Study of Daratumumab Monotherapy Versus Active Monitoring in Patients with High-Risk Smoldering Multiple Myeloma: Primary Results of the Aquila Study

2024· article· en· W4405043418 sur OpenAlexaff
Meletios Α. Dimopoulos, Peter M. Voorhees, Fredrik Schjesvold, Yaël C. Cohen, Vânia Hungria, Irwindeep Sandhu, Jindriska Lindsay, Ross Baker, Kenshi Suzuki, Hiroshi Kosugi, Mark‐David Levin, Meral Beksac, Keith Stockerl‐Goldstein, Albert Oriol, Gábor Mikala, Gonzalo Garate, Koen Theunissen, Ivan Špıčka, Anne K. Mylin, Sara Galimberti, Katarina Uttervall, Bartosz Michal Pula, Eva Medvedova, Andrew J. Cowan, Philippe Moreau, María‐Victoria Mateos, Hartmut Goldschmidt, Tahamtan Ahmadi, Linlin Sha, Els Rousseau, Liang Li, Robyn M. Dennis, Robin Carson, S. Vincent Rajkumar

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésDaratumumabMedicineMultiple myelomaInternal medicineOncologyLenalidomide

Résumé

récupéré en direct d'OpenAlex

Introduction: High-risk smoldering multiple myeloma (SMM) is an asymptomatic precursor disorder to active multiple myeloma (MM) without approved treatment options. However, recent evidence suggests patients at high risk of progression to MM may benefit from early treatment. Daratumumab (DARA) is a human IgGκ monoclonal antibody targeting CD38 with direct on-tumor and immunomodulatory mechanisms of action. DARA is approved as monotherapy for relapsed/refractory MM (RRMM) and in combination with standard-of-care regimens for RRMM and newly diagnosed MM. Based on the encouraging activity and tolerability observed with DARA monotherapy in patients with intermediate- or high-risk SMM in the phase 2 CENTAURUS study, the phase 3 AQUILA study sought to determine if DARA could delay progression to MM versus active monitoring. Here we report the primary analysis from the AQUILA study. Methods: Eligible patients had a confirmed diagnosis of high-risk SMM for ≤5 years, defined as clonal bone marrow plasma cells (BMPCs) ≥10% and ≥1 risk factor (serum M protein ≥30 g/L, IgA SMM, immunoparesis with reduction of 2 uninvolved Ig isotypes, serum involved:uninvolved free light chain ratio ≥8 and <100, and/or clonal BMPCs >50% to <60%). Focal and lytic lesion assessment was performed in screening by CT and MRI and centrally reviewed prior to study enrollment. Patients were randomized 1:1 to receive DARA SC versus active monitoring. DARA (QW in Cycles 1 and 2, Q2W in Cycles 3-6, and Q4W thereafter) was given in 28-day cycles until cycle 39, 36 months, or disease progression, whichever came first. The primary endpoint was progression-free survival (PFS), defined as progression to active MM as assessed by an independent review committee and according to IMWG diagnostic criteria for MM (SLiM-CRAB) or death. Major secondary endpoints included overall response rate (ORR), PFS on first-line MM treatment (PFS2), and overall survival (OS). Results: A total of 390 patients (DARA, n = 194; active monitoring, n = 196) were randomized. Median (range) age (64 [31-86] years) and time from initial SMM diagnosis to randomization (0.72 [0-5.0] years) were balanced between treatment groups. Median treatment duration in the DARA group was 38 cycles (35.0 months). At a median (range) follow-up of 65.2 (0-76.6) months, PFS was significantly improved with DARA versus active monitoring (HR, 0.49; 95% CI, 0.36-0.67; P <0.0001). Median PFS was not reached in the DARA group versus 41.5 months for active monitoring; estimated 60-month PFS rates were 63.1% versus 40.8%, respectively. Prespecified analyses showed generally consistent PFS improvement with DARA versus active monitoring across subgroups. ORR was 63.4% with DARA versus 2.0% with active monitoring (P <0.0001). As of the clinical cutoff, 64 (33.0%) patients in the DARA group and 102 (52.0%) patients in the active monitoring group had started first-line MM treatment. Median time from randomization to the date of first-line MM treatment was not reached with DARA versus 50.2 months with active monitoring (HR, 0.46; 95% CI, 0.33-0.62; nominal P <0.0001). There was a positive trend in favor of DARA for PFS2 (HR, 0.58; 95% CI, 0.35-0.96) and OS (60-month OS rates: DARA, 93.0%; active monitoring, 86.9%; HR, 0.52; 95% CI, 0.27-0.98). A total of 41 deaths were observed, 15 for the DARA group and 26 for the active monitoring group. Grade 3/4 treatment-emergent adverse events (TEAEs) occurred in 40.4% and 30.1% of patients in the DARA and active monitoring groups, respectively. The most common (≥5% in either group) grade 3/4 TEAE was hypertension (DARA, 5.7%; active monitoring, 4.6%). The frequency of TEAEs leading to DARA discontinuation was low (5.7%), as was the incidence of fatal TEAEs in both groups (DARA, 1.0%; active monitoring, 2.0%). Conclusions: DARA monotherapy was well tolerated and demonstrated a clinically meaningful and significant benefit in preventing or delaying progression to active MM compared with active monitoring in patients with high-risk SMM. ORR was significantly higher and time to first-line MM treatment was prolonged with DARA compared with active monitoring. This was accompanied by positive trends for PFS2 and OS in favor of DARA. These results strongly support the benefit of early intervention with DARA monotherapy versus active monitoring, the current standard of care, in patients with high-risk SMM.

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)0,004
score de la tête « metaresearch » (Gemma)0,003
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 enseignants0,010
Score d'incertitude au seuil0,032

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,003
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,003
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0100,001

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 Opus0,019
Tête enseignante GPT0,300
Écart entre enseignants0,281 · 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

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

Explorer davantage

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