Late vs Early Response and Depth of Response Are Associated with Improved Outcomes in Newly Diagnosed Multiple Myeloma (NDMM) Patients (pts) Treated with Ixazomib-Lenalidomide-Dexamethasone (IRd) or Placebo-Lenalidomide-Dexamethasone (pbo-Rd) in the Phase 3 TOURMALINE-MM2 Trial
Notice bibliographique
Résumé
Abstract Introduction: Depth of response is associated with long-term outcomes in multiple myeloma (MM); however, the effect of response kinetics on outcomes in NDMM is variable and less clear. Although some studies have shown that achieving a ≥very good partial response (VGPR) at 4 months (mos) from diagnosis is associated with increased overall survival (Garderet Leukemia 2018), other reports have shown worse outcomes in pts with early vs late responses (Yan Blood Adv 2019). The double-blind, randomized TOURMALINE-MM2 (NCT01850524) trial (Facon Blood 2021) showed a clinical meaningful progression-free survival (PFS) benefit with IRd vs pbo-Rd (median 35.3 vs 21.8 mos; hazard ratio, 0.830; 95% confidence interval, 0.676-1.018; P=0.073; median follow-up, 53.3 and 55.8 mos, respectively) in NDMM pts. Safety data were consistent with the established toxicity profile of IRd. We evaluated PFS and duration of response (DOR) by depth of best confirmed response and time to best response in TOURMALINE-MM2. Methods: Pts were randomized to receive oral ixazomib 4 mg (n=351) or placebo (n=354) on days 1, 8, and 15, plus oral lenalidomide 25 mg (10 mg if creatinine clearance ≤60 mL/min) on days 1-21 and oral dexamethasone 40 mg (20 mg in pts aged >75 years) on days 1, 8, 15, and 22 in 28-day cycles. After 18 cycles, treatment was continued without dexamethasone and reduced doses of ixazomib (3 mg) and lenalidomide (10 mg) until progressive disease (PD)/toxicity. Response assessments were performed every cycle until PD, or every 4 weeks in pts who discontinued treatment prior to PD. PFS and DOR were analyzed post-hoc in subgroups defined by depth of response and in subgroups defined by time to best confirmed response; 'early' and 'late' responses were defined by time to best confirmed response of 0-4 and >4 mos, respectively (additional analyses were performed by time to best confirmed response of 0-6 and >6 mos). Pts in either subgroup could have recorded an initial response prior to their best response. PFS and DOR were evaluated from randomization to progression and time of initial response to progression, respectively. To address potential guarantee-time bias in the PFS analysis, and to eliminate potential bias due to transient responses in DOR analysis, sensitivity analyses were conducted in pts with PFS / DOR of ≥6 mos. Results: Among the 705 pts in the intention-to-treat (ITT) population, 20% (26% IRd vs 14% placebo-Rd) had a best confirmed response of complete response (CR) or stringent CR, 35% (37 vs 34%) had VGPR, 26% (19 vs 32%) had PR, 10% (9 vs 10%) had stable disease (SD), 3% (1 vs 4%) had PD. 7% (8 vs 6%) of pts were not evaluable. In a pooled analysis of both arms, achieving a deeper response was associated with longer PFS (Figure, A) and DOR (median not reached [NR], 42.8, and 15.0 mos for pts with ≥CR, VGPR, and PR, respectively). In 570 pts with ≥PR (288 IRd; 282 pbo-Rd), 152 (53%) and 136 (47%) in the IRd arm and 143 (51%) and 139 (49%) pts in the pbo-Rd arm were defined as early (0-4 mos) and late (>4 mos) responders, respectively. For early vs late responders, 46% vs 40% were aged ≥75 years, 21% vs 12% had International Staging System stage III MM, and 44% vs 33% had expanded high-risk cytogenetic abnormalities. Median PFS was prolonged among late vs early responders with IRd (65.7 vs 21.2 mos) and pbo-Rd (62.6 vs 18.2 mos), as was median DOR (IRd, NR vs 22.6 mos; pbo-Rd, 64.1 vs 17.2 mos). The PFS sensitivity analysis among pts with PFS of ≥6 mos confirmed the association of late response with improved outcomes; among late vs early responders achieving ≥PR, median PFS was 65.7 vs 23.9 mos with IRd and 62.6 vs 18.4 mos with pbo-Rd (Figure, B), and among late vs early responders achieving ≥VGPR, median PFS was 65.7 vs 35.3 mos with IRd and 64.4 vs 21.7 with pbo-Rd. Conclusions: Achieving a deeper response was associated with prolonged PFS and DOR in NDMM patients in TOURMALINE-MM2. PFS benefit on the ITT analysis was driven by the higher rates of deep responses (≥VGPR) with IRd vs pbo-Rd. PFS and DOR were also longer in pts achieving a late vs early best confirmed response of ≥PR or ≥VGPR. Consistent with results from a similar analysis in relapsed/refractory MM in the TOURMALINE-MM1 trial (Garderet Leukemia 2018), our findings support the continuation of therapy with the aim of achieving a deeper response over time. Additional sensitivity analyses will be presented. Figure 1 Figure 1. Disclosures Richardson: Sanofi: Consultancy; AstraZeneca: Consultancy; Celgene/BMS: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Regeneron: Consultancy; Oncopeptides: Consultancy, Research Funding; Protocol Intelligence: Consultancy; Secura Bio: Consultancy; Janssen: Consultancy; Takeda: Consultancy, Research Funding; AbbVie: Consultancy; Karyopharm: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding. Venner: Takeda: Honoraria; BMS: Honoraria; Janssen: Honoraria; Pfizer: Honoraria; Sanofi: Honoraria; GSK: Honoraria. Bahlis: GlaxoSmithKline: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Genentech: Consultancy; Sanofi: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. White: Amgen: Consultancy, Honoraria; Antengene: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Forus: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria. Karlin: Celgene-BMS: Honoraria, Other: member of advisory board; Sanofi: Honoraria; oncopeptide: Honoraria; Janssen: Honoraria, Other: member of advisory board, travel support; Abbvie: Honoraria; GSK: Honoraria, Other: member of advisory board; Amgen: Honoraria, Other: travel support and advisory board ; Takeda: Honoraria, Other: member of advisory board. Rigaudeau: Takeda: Membership on an entity's Board of Directors or advisory committees. Suzuki: Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; ONO: Honoraria; Novartis: Honoraria; Sanofi: Honoraria; Abie: Honoraria; Janssen: Consultancy, Honoraria. Shibayama: Mundi Pharma: Honoraria; Otsuka: Honoraria; Pfizer: Honoraria; Bristol-Myers Squibb: Honoraria; Sanofi: Honoraria; Nippon Shinyaku: Honoraria; Fujimoto: Honoraria; Daiichi Sankyo: Honoraria; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Essentia Pharma Japan: Research Funding; Chugai: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Eisai: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Avvie: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Ono: Honoraria, Research Funding; Celgene: Research Funding. Zhang: Takeda: Current Employment. Kumar: Takeda: Current Employment, Current holder of stock options in a privately-held company. Twumasi-Ankrah: Takeda: Current Employment. Labotka: Takeda: Current Employment. Rifkin: Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Fresenius-Kabi: Membership on an entity's Board of Directors or advisory committees; Coherus: Membership on an entity's Board of Directors or advisory committees; McKesson: Current Employment, Current equity holder in publicly-traded company; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb (Celgene): Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Lonial: AMGEN: Consultancy, Honoraria; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Merck: Honoraria. Kumar: Antengene: Consultancy, Honoraria; Carsgen: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Beigene: Consultancy; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Novartis: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi:
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».