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Record W3213371026 · doi:10.1182/blood-2021-148481

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

2021· article· en· W3213371026 on OpenAlexaff
Paul G. Richardson, Thierry Façon, Christopher P. Venner, Nizar J. Bahlis, Fritz Offner, Darrell White, Lionel Karlin, Lotfi Benboubker, Sophie Rigaudeau, Éric Voog, Sung‐Soo Yoon, Kenshi Suzuki, Hirohiko Shibayama, Xiaoquan Zhang, Arun Kumar, Philip Twumasi‐Ankrah, Richard Labotka, Robert M. Rifkin, Sagar Lonial, Shaji Kumar, S. Vincent Rajkumar, Philippe Moreau

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsDalhousie UniversityQueen Elizabeth II Health Sciences CentreInstitute of Cancer ResearchUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsLenalidomideIxazomibDexamethasoneMultiple myelomaMedicineInternal medicineOncologyPlaceboCarfilzomibPathology

Abstract

fetched live from OpenAlex

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:

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.301
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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