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Enregistrement W2983625716 · doi:10.1182/blood-2019-122122

Acute Myeloid Leukemia (AML) Treated with Azacitidine: Survival Outcomes for Patients Who Complete More Than Six Cycles Are Similar to High-Risk Myelodysplastic Syndrome/Low Blast Count AML

2019· article· en· W2983625716 sur OpenAlexaffabout
Jill Fulcher, Zahra Abdrabalamir Alshammasi, Nathan Cantor, Christopher Bredeson, Grace Christou, Dawn Maze, Mitchell Sabloff

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity Health NetworkOttawa HospitalPrincess Margaret Cancer CentreUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésAzacitidineMedicineInternal medicineMyelodysplastic syndromesHypomethylating agentInternational Prognostic Scoring SystemMyeloid leukemiaLeukemiaOncologyBone marrowSurgery

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Despite accumulating evidence supporting the efficacy of hypomethylating agents in patients with AML and > 30% bone marrow blasts as well as in relapsed/refractory AML, this therapy is not yet funded by National Health Plans / Healthcare Funding Agencies in a number of countries including Canada. The assistance of an industry-sponsored compassionate program has enabled provision of azacitidine for this group of patients at The Ottawa Hospital. We report here our local "real-world" experience of azacitidine efficacy in this diverse group of AML patients and identify a sub-group whose outcomes are equivalent to that of patients with higher-risk Myelodysplastic Syndrome (MDS) and AML with 20-30% blasts for whom azacitidine therapy has funding approval in Canada. METHODS: All patients who received azacitidine at The Ottawa Hospital between 2009 and 2016 were included in this single-center, retrospective analysis. Azacitidine was administered at a dose of 75mg/m2 subcutaneously daily for 7 consecutive days every 28 days. Response was evaluated with a repeat bone marrow aspirate and trephine biopsy after the 6th cycle. In those patients confirmed to have stable or responsive disease, azacitidine was continued until progression of disease, intolerable side-effects of the drug or the patient chose to discontinue therapy. Overall survival curves were generated using the Kaplan-Meier method and log-rank tests were used to compare subgroups of patients. Actuarial median survival months were calculated with 95% confidence intervals (CI). P-values less than 0.05 were considered statistically significant. RESULTS: During the study period, 109 patients received azacitidine: 54 had MDS /AML with 20-30% blasts (the 'funded' group) and 55 had either AML with > 30 % blasts (n=23), AML relapsed post-intensive chemotherapy (n=14), AML relapsed post-allogeneic stem cell transplant (n=10) or primary refractory AML (n=8) (the 'unfunded' group). Median survival of the 'funded' group was 12.2 months while median survival of the 'unfunded' group was 5.6 months (95% CI 3.3-7.7; p=0.0058). Of the AML patients in the 'unfunded' group, 24% completed more than 6 cycles of azacitidine compared to 52% of patients in the 'funded' group. In both the 'funded' and 'unfunded' groups, patients who completed more than 6 cycles of azacitidine had similar survival outcomes (p=0.7277): the 'funded' group had a median survival of 19 months (95% CI 14.4-25.3) while the median survival of this sub-population of the 'unfunded' AML group was 22 months (95% CI 11.7-24.9). Patients in both groups who failed to complete more than 6 cycles of azacitidine also had a similar outcome (p=0.39), with a median survival of 5.7 months (95% CI 4.0-6.3) for patients with MDS/AML 20-30% blasts and 3.6 months (95% CI 2.2-5.1) for AML patients with > 30% blasts or relapsed/refractory disease. Reasons for patients not completing at least 6 cycles of azacitidine included progression of disease (25%), bacterial infections most commonly pneumonia (53%) and patient preference (7%). CONCLUSION: A significant sub-population of AML patients with > 30% blasts or refractory/relapsed AML can achieve a meaningful survival benefit with the hypomethylating agent, azacitidine. A higher proportion of this AML patient population discontinued azacitidine as a result of infective complications. The provision of routine prophylactic antibiotics may enable more patients with AML to receive an adequate amount of azacitidine to achieve therapeutic benefit and warrants further investigation. Our results add to the growing body of 'real-world' evidence that supports healthcare funding agencies to provide coverage of azacitidine for patients with AML who in some countries at present do not fulfill government funding criteria. Disclosures Bredeson: Otsuka: Research Funding. Maze:Pfizer Inc: Consultancy; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sabloff:Novartis Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; ASTX: Membership on an entity's Board of Directors or advisory committees, Research Funding; Actinium Pharmaceuticals, Inc: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas Pharma Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi Canada: 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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
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
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
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 Opus0,011
Tête enseignante GPT0,248
Écart entre enseignants0,238 · 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'étudeObservationnel
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
Publié2019
Routes d'admission2
Résumé présentoui

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