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Enregistrement W3211572770 · doi:10.1182/blood-2021-145362

Impact of <i>FLT3</i> Mutation Clearance after Front-Line Treatment with Gilteritinib Plus Azacitidine, or Gilteritinib or Azacitidine Alone in Patients with Newly Diagnosed AML: Results from the Phase 2/3 Lacewing Trial

2021· article· en· W3211572770 sur OpenAlexaff
Eunice S. Wang, Jessica K. Altman, Mark D. Minden, Ruishan Wu, Elizabeth Rich, Jason E. Hill

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineAzacitidineInternal medicineSurgeryGastroenterologyChemotherapyBiology

Résumé

récupéré en direct d'OpenAlex

Abstract Background: The presence of measurable residual disease (MRD) after achievement of remission with induction therapy is a prognostic marker of relapse risk in patients with acute myeloid leukemia (AML). Gilteritinib is an oral FLT3 inhibitor approved as a single agent for the treatment of patients with FLT3-mutated (FLT3mut+) relapsed or refractory AML. Evaluation of gilteritinib in the front-line setting is under way. We evaluated FLT3 internal tandem duplication (FLT3-ITD) mutation clearance using two different thresholds and correlated mutation clearance with survival outcomes in patients with newly diagnosed AML ineligible for intensive chemotherapy who were treated with front-line gilteritinib plus azacitidine (AZA) or either agent alone in the phase 2/3 LACEWING trial. Methods: Adult patients with newly diagnosed FLT3mut+ AML ineligible for intensive induction chemotherapy received 28-day cycles of once-daily gilteritinib plus AZA in the Safety Cohort (80 or 120 mg/day gilteritinib plus 75 mg/m 2 AZA, Days 1-7) and in Arm AC (120 mg/day gilteritinib plus 75 mg/m 2 AZA, Days 1-7), gilteritinib (120 mg/day) alone in Arm A, or AZA (75 mg/m 2, Days 1-7) alone in Arm C. A subset of patients who had a best overall response of composite complete remission (CRc; defined as the sum of patients who achieved complete remission with or without complete hematologic or platelet recovery) and who had bone marrow-derived DNA samples available at baseline and at least one additional post-baseline timepoint were assessed for FLT3-ITD mutation clearance using next-generation sequencing. An Illumina ® sequencing platform was used to quantify FLT3-ITD and total FLT3 alleles. The FLT3-ITD variant allelic frequency (VAF) was defined as the ratio of FLT3-ITD to total FLT3 frequency. Data were analyzed using two different mutation clearance thresholds, FLT3-ITD VAF <10 −4 or <10 −3, where 10 −4 was based on previously published findings in patients with relapsed or refractory FLT3mut+ AML who were treated with gilteritinib (Altman JK et al., Cancer Med. 2021;10[3]:797-805) and 10 -3 was an additional exploratory threshold used because it provided a more balanced distribution of patients, given the small number of patients achieving mutation clearance at the 10 -4 threshold. Results: The median age of patients enrolled in LACEWING was 77 years (range, 59-90), with 73% of patients aged >75 years. Although baseline characteristics of the overall LACEWING population were generally well balanced across treatment arms, higher proportions of patients treated with gilteritinib plus AZA (47%) or gilteritinib alone (59%) had an Eastern Cooperative Oncology Group (ECOG) performance status of ≥2 compared with patients treated with AZA alone (33%). Overall, 40 patients who achieved CRc and had sufficient DNA samples from bone marrow aspirates obtained at baseline and at least one additional post-baseline timepoint were included in the analysis (Safety Cohort, n=8; Arm A, n=7; Arm AC, n=17; and Arm C, n=8). Across both thresholds, the proportions of patients with FLT3 mutation clearance did not markedly differ between patients treated with gilteritinib or AZA (Table). In patients who received gilteritinib, FLT3-ITD mutation clearance using either threshold was associated with a similar increase in median overall survival (OS) compared to patients who did not achieve mutation clearance (Figure). Conclusions: Regardless of MRD threshold, rates of MRD negativity were not substantially different between newly diagnosed FLT3mut+ AML patients ineligible for intensive induction chemotherapy who received gilteritinib alone, gilteritinib plus AZA, or AZA alone. Advanced age coupled with a worse baseline ECOG performance score at baseline may have compromised treatment response and achievement of FLT3 mutation clearance in patients treated with gilteritinib. The mutation clearance thresholds used in this analysis showed similar median OS in patients who received gilteritinib. Figure 1 Figure 1. Disclosures Wang: Pfizer: Consultancy, Honoraria, Other: Advisory Board, Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, Honoraria, Other: Advisory Board; Novartis: Consultancy, Honoraria, Other: Advisory Board; Kura Oncology: Consultancy, Honoraria, Other: Advisory board, steering committee, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Honoraria, Other: Advisory Board; Takeda: Consultancy, Honoraria, Other: Advisory board; Kite Pharmaceuticals: Consultancy, Honoraria, Other: Advisory Board; Stemline Therapeutics: Consultancy, Honoraria, Other: Advisory board, Speakers Bureau; Mana Therapeutics: Consultancy, Honoraria; BMS/Celgene: Membership on an entity's Board of Directors or advisory committees; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; DAVA Oncology: Consultancy, Speakers Bureau; Rafael Pharmaceuticals: Other: Data safety monitoring committee; Gilead: Consultancy, Honoraria, Other: Advisory board; Daiichi Sankyo: Consultancy, Honoraria, Other: Advisory board; PTC Therapeutics: Consultancy, Honoraria, Other: Advisory board; Genentech: Consultancy; MacroGenics: Consultancy. Altman: Kartos: Research Funding; Theradex: Consultancy, Other: Advisory boards; Biosight: Consultancy, Other: Travel fees, Research Funding; Daiichi Sankyo: Consultancy; AbbVie: Consultancy, Other: Advisory Board, Research Funding; BMS: Research Funding; Amgen: Research Funding; Astellas: Consultancy, Other: Advisory Board, Research Funding; Fujifilm: Research Funding; ALZ Oncology: Research Funding; Immunogen: Research Funding; GlycoMimetics: Other: Participation on an advisory board; Syros: Consultancy; Kura Oncology: Consultancy; Boehringer Ingelheim: Research Funding; Aprea: Research Funding; Kura: Research Funding. Minden: Astellas: Consultancy. Wu: Astellas: Current Employment. Rich: Astellas Pharma Global Development, Inc.: Current Employment. Hill: Ligacept, LLC: Current holder of individual stocks in a privately-held company, Other: Stockholder; Astellas Pharma Global Development: Current Employment.

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: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
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 Opus0,029
Tête enseignante GPT0,315
Écart entre enseignants0,286 · 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

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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