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Record W3099980423 · doi:10.1182/blood-2020-143816

Efficacy and Safety Results from ASCEMBL, a Multicenter, Open-Label, Phase 3 Study of Asciminib, a First-in-Class STAMP Inhibitor, vs Bosutinib (BOS) in Patients (Pts) with Chronic Myeloid Leukemia in Chronic Phase (CML-CP) Previously Treated with ≥2 Tyrosine Kinase Inhibitors (TKIs

2020· article· en· W3099980423 on OpenAlexaff
Andreas Hochhaus, Carla Boquimpani, Delphine Réa, Yosuke Minami, Elza Lomaia, Sergey Voloshin, Anna Turkina, Dong‐Wook Kim, Jane F. Apperley, Jörge E. Cortes, André Abdo, Laura Fogliatto, Dennis Dong Hwan Kim, Philipp D. le Coutre, Susanne Saußele, Mario Annunziata, Timothy P. Hughes, Naeem Chaudhri, Lynette Chee, Valentín García‐Gutiérrez, Koji Sasaki, Paola Aimone, Alex Allepuz, Sarah Quenet, Véronique Bédoucha, Michael J. Mauro

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsBosutinibMedicineOpen labelMyeloid leukemiaInternal medicinePhases of clinical researchOncologyAdverse effectClinical trialImatinibNilotinib

Abstract

fetched live from OpenAlex

Introduction: Asciminib, unlike all approved TKIs that bind to the ATP site of the BCR-ABL1 oncoprotein, is a first-in-class STAMP (Specifically Targeting the ABL Myristoyl Pocket) inhibitor with a new mechanism of action. BOS, an ATP-competitive TKI, has shown clinical efficacy in pts who received ≥2 TKIs and in newly diagnosed CML, in prospective clinical trials. We asked if asciminib could provide superior efficacy to BOS beyond 2nd line, based on the clinical activity of asciminib monotherapy in heavily pretreated pts with CML in a phase 1 study. Methods: Adults with CML-CP previously treated with ≥2 TKIs were randomized 2:1 to asciminib 40 mg twice daily (BID) or BOS 500 mg once daily (QD). Randomization was stratified by major cytogenetic response (MCyR; Ph+ metaphases ≤35%) status at baseline. Pts intolerant of their most recent TKI were eligible if they had BCR-ABL1IS >0.1% at screening (19 pts with BCR-ABL1IS <1% enrolled). Pts with treatment failure (per 2013 European LeukemiaNet recommendations) on BOS are permitted to switch to asciminib per investigator judgement. Pts with known bosutinib-resistant T315I or V299L mutations were excluded. The primary endpoint was major molecular response (MMR) rate at 24 wks. We report primary efficacy and safety results from ASCEMBL (cutoff: May 25, 2020). Results: A total of 233 pts with CML-CP was randomized to receive asciminib 40 mg BID (n=157) or BOS 500 mg QD (n=76). Fewer pts on asciminib discontinued their last TKI due to lack of efficacy and fewer received ≥3 prior lines of TKI therapy (Table 1). At cutoff, treatment was ongoing in 97 (61.8%) and 23 (30.3%) pts, respectively; the most common reason for treatment discontinuation was lack of efficacy (asciminib, 33 [21.0%] pts; BOS, 24 [31.6%]) (Table 1). Lack of efficacy was most frequently BCR-ABL1 >10% or Ph+ >65% after 6 months of therapy (asciminib 10.8%, BOS 25.0%). Among the 24 pts who discontinued BOS due to lack of efficacy, 22 switched to asciminib. At baseline, ≥1 BCR-ABL1 mutation was present in 12.7% pts on asciminib (most common: F359C/V) and 17.1% on BOS (most common: M244V, F317L). Median duration of follow-up was 14.9 months from randomization to cutoff. Median duration of exposure was 43.4 wks (range, 0.1-129.9) for asciminib and 29.2 wks (range, 1.0-117.0) for BOS; median relative dose intensity was 99.7% (87-100) and 95.4% (74-100). MMR rate at 24 wks was 25.5% with asciminib and 13.2% with BOS, meeting the primary objective. The between-arm common treatment difference for MMR at 24 wks, after adjustment for MCyR status at baseline, was 12.2% (95% CI, 2.19-22.3: 2-sided P=.029). Among those pts who achieved MMR, median time to MMR was 12.7 wks and 14.3 wks with asciminib and BOS, respectively. At 24 wks, more pts on asciminib (17 [10.8%] and 14 [8.9%]) than on BOS (4 [5.3%] and 1 [1.3%]) achieved deep molecular response (MR4 and MR4.5, respectively). CCyR rate at 24 wks was 40.8% with asciminib vs 24.2% with BOS. Preplanned subgroup analysis showed that the MMR rate at 24 wks was superior with asciminib than BOS across most major demographic and prognostic subgroups, including in pts who received ≥3 prior TKIs, in those who discontinued the prior TKI due to treatment failure, and regardless of baseline cytogenetic response (Figure). Grade ≥3 adverse events (AEs) occurred in 50.6% and 60.5% of pts receiving asciminib and BOS, respectively. The proportion of pts who discontinued treatment due to AEs was lower with asciminib (5.8%) than BOS (21.1%). Grade ≥3 AEs and AEs requiring dose interruption and/or adjustments were reported less frequently with asciminib than BOS (Table 2). Most frequent grade ≥3 AEs (occurring in >10% of pts in any treatment arm) with asciminib vs BOS were thrombocytopenia (17.3%; 6.6%), neutropenia (14.7%; 11.8%), diarrhea (0%, 10.5%), and increased alanine aminotransferase (0.6%, 14.5%). On-treatment deaths occurred in 2 pts (1.3%) on asciminib (ischemic stroke and arterial embolism, 1 pt each) and 1 pt (1.3%) on BOS (septic shock). Conclusions: In this first controlled study comparing treatments for resistant/intolerant (R/I) pts with CML, asciminib, a first-in-class STAMP inhibitor, demonstrated statistically significant and clinically meaningful superiority in efficacy compared with BOS (primary objective), deeper MR rates, and a favorable safety profile. These results support the use of asciminib as a new treatment option in CML, particularly in R/I pts who received ≥2 prior TKIs. Disclosures Hochhaus: Novartis: Research Funding; Incyte: Research Funding; Pfizer: Research Funding; Bristol Myers Squibb: Research Funding. Boquimpani:Novartis: Speakers Bureau. Rea:BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees. Minami:Pfizer Japan Inc.: Honoraria; Takeda: Honoraria; Bristol-Myers Squibb Company: Honoraria; Novartis Pharma KK: Honoraria. Lomaia:Bristol Myers Squibb: Speakers Bureau; Pfizer: Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Voloshin:Novartis: Honoraria, Speakers Bureau. Turkina:Pfizer: Honoraria; Novartis Pharma: Honoraria; BMS: Honoraria. Kim:Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; ILYANG: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Sun Pharma.: Research Funding. Apperley:Bristol Myers Squibb: Honoraria, Speakers Bureau; Incyte: Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Pfizer: Honoraria, Research Funding, Speakers Bureau. Cortes:Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BioPath Holdings: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Telios: Research Funding; Astellas: Research Funding; Amphivena Therapeutics: Research Funding; Arog: Research Funding; BiolineRx: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Immunogen: Research Funding; Merus: Research Funding; Sun Pharma: Research Funding. Abdo:Novartis: Honoraria; Takeda: Honoraria. Kim:Paladin: Consultancy, Honoraria, Research Funding; Pfizer: Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Research Funding. le Coutre:Pfizer: Honoraria; Incyte: Honoraria; Novartis: Honoraria. Saussele:Novartis: Honoraria, Research Funding; Incyte: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Pfizer: Honoraria. Hughes:BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Chee:Novartis: Other: Travel support for attendance at investigator meeting. García Gutiérrez:Novartis Pharma AG: Consultancy, Honoraria, Other: travel/accommodations/expenses, Research Funding; Pfizer: Honoraria, Other: travel/accommodations/expenses, Research Funding; Incyte: Consultancy, Honoraria, Other: travel/accommodations/expenses, Research Funding. Sasaki:Pfizer Japan: Consultancy; Otsuka: Honoraria; Novartis: Consultancy, Research Funding; Daiichi Sankyo: Consultancy. Aimone:Novartis: Current Employment. Allepuz:Novartis: Current Employment. Quenet:Novartis: Current Employment. Bédoucha:Novartis: Current Employment. Mauro:Bristol-Myers Squibb: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Novartis: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Takeda: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Pfizer: Consultancy, Honoraria, Other: Travel, Accommodation, Expenses, Research Funding; Sun Pharma/SPARC: Research Funding.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.284
Teacher spread0.261 · 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 teacher head, not a consensus.

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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Citations26
Published2020
Admission routes1
Has abstractyes

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