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Enregistrement W4389244310 · doi:10.1182/blood-2023-188464

Outcomes of Patients with Acute Myeloid Leukemia with Myelodysplasia Related Changes (AML-MRC) Receiving Intensive Vs. Non-Intensive First Line Treatment

2023· article· en· W4389244310 sur OpenAlexaff
Signy Chow, Alexandra Misura, Olga Bigun, Sila Usta, Renato Sasso, Dylan Gowlett-Park, Katarina Czibere, Rena Buckstein, Lee Mozessohn, Lisa Chodirker, Theodore A. Kennedy, Hubert Tsui

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineInternal medicineCytarabineAzacitidineMyeloid leukemiaDecitabineHypomethylating agentIdarubicinOncologyFlag (linear algebra)FludarabineLeukemiaHematologyChemotherapyCyclophosphamide

Résumé

récupéré en direct d'OpenAlex

Background: Acute myeloid leukemia with myelodysplasia related changes (AML-MRC) a distinct clinico-pathologic subtype of AML recognized in the WHO and ICC 2022 classifications of hematolymphoid neoplasms (AML-MRC and AML-MR respectively). Compared to other subtypes, patients with AML-MRC/AML-MR have a worse prognosis and are less likely to respond to treatment. Traditionally, patients who are eligible for allogenic stem cell transplant (SCT) with AML-MRC/AML-MR are given high intensity chemotherapy (IC), such as daunorubicin and cytarabine (“7+3”), liposomal 7+3 or fludarabine+cytarabine+idarubicin (FLAG-IDA) whereas patients who are not transplant-eligible were treated with hypomethylating agents (i.e. azacitidine). Recently, azacitidine + venetoclax (aza/ven) has emerged as an important option for all AML patients over 75 years of age or with significant comorbidities who are not eligible for IC. However, the efficacy of aza/ven compared to IC for AML-MRC who are candidates for either has not been clearly established. Methodology: We conducted a single centre retrospective review of patients diagnosed with AML-MRC/AML-MR at Sunnybrook Health Science Centre (SHSC). A list of patients with AML-MRC/AML-MR was compiled from records from the Sunnybrook Hematology Biobank, which collects specimens and clinical data from 95% of acute leukemia patients presenting to SHSC. 65 patient charts were reviewed, and 60 patients were included in the study. 3 patients were not treated at SHSC and 2 were more appropriately classified as AML with recurrent genetic abnormalities. Treatment with a “7+3” backbone or FLAG-IDA were considered ‘intensive’ regimens; treatment with azacitidine with or without venetoclax, and low dose cytarabine (LDAC), with or without venetoclax were considered ‘non-intensive.‘ ELN 2022 criteria were used to evaluate responses to therapy. Results: 60 patients with AML-MRC/AML-MR were treated at SHSC from January 2021 to April 2023. The median age was 74 (37-99) y.o. 34 patients were male. The upper age of eligibility for allogeneic stem cell transplant was considered 72 years for this study. 28 patients were SCT eligible (31-72y.o.) and 32 patients were SCT ineligible (73-99y.o.). For SCT eligible patients, 14/28 were treated intensively and 10/28 were treated non intensively. 4 patients did not receive treatment. Of the SCT eligible group, 6/14 intensively treated patients achieved a CR/CRi compared to 5/10 non-intensively treated patients. For SCT ineligible patients, 8/32 did not receive treatment and the remaining 24 were treated non intensively. 12/24 SCT ineligible patients receiving treatment were given azacitidine+ venetoclax (aza/ven) and 9/12 achieved a CR/CRi. 7/24 patients received LDAC + venetoclax and 3/7 achieved a CR. In total, 14/60 patients were treated intensively, 21/60 patients were treated with aza/ven, 7/60 received LDAC+venetoclax, 5/60 azacitidine alone and 1/60 LDAC alone. 12/60 patients did not receive leukemia-directed therapy, either due to concomitant illness precluding treatment or a decision to decline treatment. Notably, 14/21 patients receiving aza/ven achieved a CR/CRi compared to 6/14 intensively treated patients, though more intensively treated patients ultimately proceeded to transplant (Figure 1). 48 patients who underwent therapy had next generation sequencing data for mutations of interest in AML. The most common mutations found in this cohort were ASXL1 (32), SRSF2 (20), RUNX1 (18), TET2 (17), IDH2 (16) and TP53 (12). No differences were found between patients that responded to first line therapy compared to those that did not, or those that responded to intensive chemotherapy compared to those responding to non-intensive treatment (Figure 2). Conclusion: Aza/Ven is an effective treatment regimen for AML-MRC/AML-MR, with 14/21 patients achieving CR/CRi after firstline treatment compared to 6/14 patients after IC. 4/4 patients achieved CR/CRi with salvage aza/ven after failing to respond to IC. Our study suggests that aza/ven should be considered as a firstline treatment option even in patients who are fit for intensive therapy as a means to achieve adequate responses to bridge to allogenic stem cell transplant without attendant toxicities associated with IC. Further studies are required to determine if specific mutations can predict response to either aza/ven or intensive treatment.

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)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
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 savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,014
Tête enseignante GPT0,259
Écart entre enseignants0,245 · 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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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