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Enregistrement W2589026218 · doi:10.1182/blood.v126.23.4893.4893

Front-Line FLAG-IDA and Nove-HiDAC Chemotherapy Improves Overall Survival (OS) and Complete Remission Rates (CR) for Patients with Secondary or Therapy-Related AML Compared to 3&7

2015· article· en· W2589026218 sur OpenAlexaff
Sita Bhella, Eshetu G. Atenafu, Andre C. Schuh, Mark D. Minden, Aaron D. Schimmer, Vikas Gupta, Matthew D. Seftel, Mohamed Shanavas, Andrzej Lutynski, Amr Rostom, Anna Rydlewski, Dina Khalaf, Karen Yee

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity Health NetworkPrincess Margaret Cancer CentreCancerCare ManitobaUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineFlag (linear algebra)CytarabineInternal medicineEtoposideIdarubicinMitoxantroneSalvage therapyFludarabineRefractory (planetary science)OncologySurgeryGemcitabineGastroenterologyChemotherapyCyclophosphamide

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Therapy for patients (pts) with high risk AML remains unsatisfactory. Retrospective studies have demonstrated activity of fludarabine, cytarabine, GCSF and idarubicin (FLAG-IDA) and of mitoxantrone, etoposide and cytarabine (NOVE-HiDAC) as salvage therapy in pts with relapsed or refractory AML. A recent randomized trial indicated high complete remission (CR) rates with improved relapsed-free survival when FLAG-IDA is administered as frontline induction therapy (Burnett et al. J Clin Oncol 2013). Since 01/2011, we have used FLAG-IDA as a first line therapeutic option in pts with high risk AML (poor risk cytogenetics, antecedent myeloproliferative neoplasm or myelodysplastic syndrome, and/or therapy-related AML) in an attempt to improve CR rates and permit more patients with AML to advance to allogeneic hematopoietic cell transplantation (alloHCT). Prior to 2011, either 3&7 or NOVE-HiDAC was used as first line therapy in patients with AML. Methods: We conducted a retrospective review of consecutive patients with high risk AML treated with front-line (a) FLAG-IDA between 01/2011 to 03/2015, (b) NOVE-HiDAC from 01/2006 to 12/2014, or (c) 3&7 from January 01/2011 to 12/2014 at the Princess Margaret Cancer Centre, to determine the CR rates and overall survival (OS) associated with the different regimens. Results: Patients characteristics are in Table 1. Fifty-two, 32, and 30 pts received FLAG-IDA, NOVE-HiDAC or 3&7 as first induction, respectively. Patients receiving FLAG-IDA had more high-risk features (i.e. complex cytogenetics, more azacytidine failures) compared to those receiving 3&7. Overall CR rate (i.e. CR + [CRi] + [CRp]) with FLAG-IDA, NOVE-HiDAC, and 3&7 respectively was 86% (n=42/49), 84% (n=21/25) and 50% (n=13/26), respectively. Median CR duration, censored at time of transplant, for pts receiving FLAG-IDA, NOVE-HiDAC and 3&7 was 3 mos (0.5-15), 3.5 mos (1-9) and 5.5 mos (0.5-42), respectively. OS at 1 year with FLAG-IDA, NOVE-HiDAC and 3&7 was 61% (95% CI, 41% -75%), 55% (95% CI, 34%-72%) and 21.6% (95% CI, 7.4%-40.7%), respectively (log-rank test p-value=0.0076). On subgroup analysis, there was no statistical difference in OS for pts ≥70 years. Of those with a donor identified, 35% (n=13/37), 73% (n=11/15) and 29% (n=5/17) of pts who were treated with FLAG-IDA, NOVE-HiDAC and 3&7 underwent an alloSCT, respectively. Pts with sAML may have had a higher transplant rate due to donor searches initiated earlier. Probable and possible invasive aspergillosis infections in pts receiving FLAG-IDA, NOVE-HiDAC and 3&7 were 50%, 34% and 33% respectively. Institution of earlier bronchoscopies led to increased fungal detection in the FLAG-IDA group. Median length of stay and ICU transfers were similar between groups. Induction deaths were secondary to sepsis, respiratory failure, invasive aspergillosis, and hemorrhage; these were similar across groups. Two pts receiving NOVE-HiDAC, with prior MPN, died of progressive splenomegaly and liver failure. Conclusions: Toxicities associated with frontline FLAG-IDA and NOVE-HIDAC induction are acceptable. FLAG-IDA and NOVE-HiDAC induction can result in durable CR, permitting patients with high risk AML to proceed to alloSCT and providing more favourable survival rates than frontline 3&7. Randomized studies are needed to confirm these findings for pts with poor-risk sAML and tAML. Table 1. Patient Characteristics FLAG-IDA(2013-2015) NOVE-HiDAC(2006-2014) 3&7(2011-2014) N=52 N=32 N=30 Median Age,y (range) Age <70 Age ≥ 70 Sex (M:F) 59.5 (21-76) 47 (90%) 5 (10%) 25:27 54.5 (24-74) 31 (97%) 1 (3%) 18:14 61.5 (20-78) 21 (70%) 9 (30%) 23:7 Cytogenetics by MRC Classification Good Intermediate Poor Not available 0 (0%) 25 (48%) 23 (44%) 4 (8%) 0 (0%) 18 (56%) 9 (28%) 5 (16%) 0 (0%) 20 (67%) 6 (20%) 4 (13%) Molecular (Pts ≤70 y with normal karyotype) FLT3-NPM1+ FLT3+ NPM1+ FLT3+ NPM1- FLT3-NPM1- 1/11 (9%) 5/11 (45%) 2/11 (18%) 3/11 (27%) 0/7 (0%) 2/7 (29%) 1/7 (14%) 4/7 (57%) 0/7 (0%) 1/7 (14%) 0/7 (0%) 6/7 (86%) WBC (x 109/L) (range) 5.15 (0.6 -239) 13 (1.3-182.4) 3.2 (0.7-164) sAML IBMFS MPN MDS Prior AZA 27 (52%) 0/27 (0%) 10/27 (37%) 17/27 (63%) 9/17 (53%) 29 (91%) 1/29 (4%) 15/29 (51%) 13/29 (45%) 2/13 (15%) 20 (67%) 2/20 (10%) 0/20 (0%) 18/20 (90%) 5/18 (28%) Therapy-Related (%) 14 (27%) 6 (19%) 15 (50%) De Novo AML with Complex Cytogenetics FLT3+ Other (ie MLL) 15 (29%) 7/15 (47%) 5/15 (33%) 3/15 (20%) 0 (0%) 0 (0%) Donor Identified (%) 37(71%) 16(50%) 17(57%) Disclosures Gupta: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Research Funding.

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)0,000
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 non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,044
Tête enseignante GPT0,306
Écart entre enseignants0,261 · 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 non 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

Citations2
Publié2015
Routes d'admission1
Résumé présentoui

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