MétaCan
Menu
Retour à la cohorte
Enregistrement W3213659569 · doi:10.1182/blood-2021-147769

Results from a Global Randomized Phase 3 Study of Guadecitabine (G) Vs Treatment Choice (TC) in 302 Patients with Relapsed or Refractory (r/r) Acute Myeloid Leukemia after Intensive Chemotherapy (ASTRAL-2 Study)

2021· article· en· W3213659569 sur OpenAlexaffabout
Gail J. Roboz, Guillermo Sanz, Elizabeth A. Griffiths, Karen Yee, Hagop M. Kantarjian, Christian Récher, Michael Byrne, Elżbieta Patkowska, Hee‐Je Kim, Xavier Thomas, Ine Moors, Wendy Stock, Árpád Illés, Pierre Fenaux, Yasushi Miyazaki, Takahiro Yamauchi, Casey L. O’Connell, Yong Hao, Harold Keer, Mohammad Azab, Hartmut Döhner

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésDecitabineInternal medicineMedicineCytarabineClinical endpointAnthracyclineChemotherapy regimenChemotherapySurrogate endpointGastroenterologyOncologyAzacitidineRefractory (planetary science)Randomized controlled trialBiologyCancerBreast cancer

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Guadecitabine (G) is a next generation subcutaneous (SC) hypomethylating agent (HMA) resistant to degradation by cytidine deaminase which results in prolonged in vivo exposure to the active metabolite decitabine. We conducted a large global randomized phase 3 study (ASTRAL-2) of G vs TC in AML patients who were either refractory to or relapsed (r/r) after prior anthracycline-based intensive chemotherapy with or without hematopoietic cell transplant (HCT). Methods: r/r AML patients were randomized to G (60 mg/m 2 SC/d for 10 days in first 1-2 cycles followed by 5-day cycles Q 28 days) vs Treatment Choice (TC). TC were preselected prior to randomization to either low intensity (LI) treatment; high intensity (HI) chemotherapy; or Best Supportive Care (BSC). LI choices were other HMAs of azacitidine or decitabine, or low-dose Ara-C (LDAC) at their standard doses. HI choices were high-dose Ara-C (HiDAC), MEC, or FLAG± Ida combination chemotherapy at standard doses. Primary endpoint was overall survival (OS) based on ITT analysis with secondary endpoints including 12 and 24-month survival rates, complete response (CR), event-free survival (EFS), and safety. P values for secondary endpoints and subgroups are nominal as there was no adjustment of p values for multiple analyses. Results: 302 patients were randomized to G (148) or TC (154). Preselected TCs were mainly LI (77%) predominantly HMAs (86% of the patients randomized to LI), or HI (21%), with only 6 patients (2%) in the BSC subset. Baseline variables were well balanced across the 2 treatment arms. For G vs TC respectively, age ≥65 y in 51.4% vs 40.3% with median age 65y vs 63y, ECOG PS 2 in 15.5% vs 20.8%, poor risk cytogenetics in 44.6% vs 42.2%, refractory AML in 44.6% vs 33.1%, prior HCT in 18.2% vs 26%, a majority of patients were in second or subsequent relapse after ≥ 2 prior therapies (54.7% vs 56.5%). Median number of treatment cycles was short (3 cycles for G vs 2 cycles for TC). Median follow up was 21.6 months. Most common causes of treatment discontinuation were disease progression (35.2% for G vs 38.1% for TC), or death (15.2% for G vs 18.4% for TC). Median OS on G was 6.4 months vs 5.4 months for TC and not statistically significant (OS HR 0.88, 95% CI 0.67, 1.14, log rank p value 0.3). There was no significant difference in OS between G and each of the LI and HI preselected subsets. However, several other planned prospective subgroups favored G with OS HR 95% CI upper limit ≤ 1.0 including patients <65y (HR 95% CI 0.47, 0.97, p 0.032) ; ECOG PS 0-1 (HR 95% CI 0.57, 1.0, p 0.049); refractory AML (HR 95% CI 0.38, 0.89, p 0.013); lower peripheral blood (PB) disease burden of ≤ 30% PB blasts (HR 95% CI 0.46, 0.92, p 0.015); and those who received at least 4 cycles in either treatment arm (HR 95% CI 0.36, 0.95 , p 0.031). The 12- and 24-month survival rates for G vs TC respectively were 32% vs 26%; and 19% vs 10%. Median EFS was short with 3 months for G vs 2.4 months for TC; log rank p 0.005. CR rate was 12.8% for G vs 7.1% for TC (p 0.051). CR + CR with partial hematologic recovery (CRh) rate was double for G with 16.9% compared to 7.8% for TC (p 0.007). Composite CR (CRc) or CR+ CR with incomplete hematologic recovery (CRi) rate was 27% for G vs 14.3% for TC (p 0.003). Adverse events (AEs) of grade ≥3, regardless of relationship to treatment, were 89% on G vs 84% on TC. Most common Grade ≥3 AEs for G vs TC respectively were febrile neutropenia (38.6% vs 38.1%); neutropenia (32.4% vs 17%); thrombocytopenia (28.3% vs 29.9%); anemia (21.4% vs 24.5%); pneumonia (18.6% vs 20.4%); and sepsis (11.7 vs 10.9%). None of the differences were significant except for neutropenia (p 0.003). Summary/Conclusions: In this randomized study in r/r AML after intensive chemotherapy, G did not significantly improve OS compared to standard of care TC composed mainly of LI treatment with other HMAs. The data suggest that G may be better than TC in in some of the secondary endpoints (24-month survival rate, EFS, CR, CR+CRh, and CRc). Prospective subgroup analyses of OS suggest that younger (<65 y), more fit patients (PS 0-1); with lower PB disease burden (PB blasts ≤ 30%), and those who could receive at least 4 cycles may benefit from G. The results of secondary endpoints and subgroup analyses should be interpreted with caution. Grade ≥3 AEs were the expected hematological and infection AEs with no significant differences between G and TC except for significantly higher incidence of neutropenia with G. Disclosures Roboz: Actinium: Consultancy; Mesoblast: Consultancy; Janssen: Research Funding; AbbVie: Consultancy; Astex: Consultancy; AstraZeneca: Consultancy; Novartis: Consultancy; Agios: Consultancy; Glaxo SmithKline: Consultancy; Blueprint Medicines: Consultancy; Janssen: Consultancy; Jasper Therapeutics: Consultancy; Amgen: Consultancy; Astellas: Consultancy; Bristol Myers Squibb: Consultancy; Celgene: Consultancy; MEI Pharma - IDMC Chair: Consultancy; Helsinn: Consultancy; Bayer: Consultancy; Daiichi Sankyo: Consultancy; Jazz: Consultancy; Otsuka: Consultancy; Pfizer: Consultancy; Roche/Genentech: Consultancy. Sanz: Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Other: Travel, accommodations, and expenses; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Speakers Bureau; Helsinn Healthcare: 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; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Research Funding. Griffiths: Novartis: Honoraria; Abbvie: Consultancy, Honoraria; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Taiho Oncology: Consultancy, Honoraria; Apellis Pharmaceuticals: Research Funding; Astex Pharmaceuticals: Honoraria, Research Funding; Genentech: Research Funding; Boston Biomedical: Consultancy; Alexion Pharmaceuticals: Consultancy, Research Funding; Takeda Oncology: Consultancy, Honoraria. Yee: Forma Therapeutics: Research Funding; Astex: Membership on an entity's Board of Directors or advisory committees, Research Funding; F. Hoffmann La Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; TaiHo: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Paladin: Membership on an entity's Board of Directors or advisory committees; Otsuka: Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Bristol-Myers Squibb/Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Onconova: Research Funding; Tolero: Research Funding; Jazz: Research Funding; MedImmune: Research Funding; Geron: Research Funding; Janssen: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Shattuck Labs: Membership on an entity's Board of Directors or advisory committees. Kantarjian: Daiichi-Sankyo: Research Funding; BMS: Research Funding; Ipsen Pharmaceuticals: Honoraria; Astellas Health: Honoraria; Aptitude Health: Honoraria; KAHR Medical Ltd: Honoraria; Astra Zeneca: Honoraria; Pfizer: Honoraria, Research Funding; Ascentage: Research Funding; Amgen: Honoraria, Research Funding; Immunogen: Research Funding; Novartis: Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Precision Biosciences: Honoraria; Jazz: Research Funding; NOVA Research: Honoraria; Taiho Pharmaceutical Canada: Honoraria. Recher: Incyte: Honoraria; Janssen: Honoraria; Jazz: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Macrogenics: Honoraria, Membership on an entity's Board of Directors or advisory committees; MaatPharma: Research Funding; Astellas: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Daiichi Sankyo: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Agios: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Fundin

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)0,002
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 enseignants0,006
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,002
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,003
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,002
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,016
Tête enseignante GPT0,308
Écart entre enseignants0,292 · 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

Citations4
Publié2021
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueBloodMême sujetAcute Myeloid Leukemia ResearchTravaux en français237 207