MétaCan
Menu
← Retour à la cohorte
Enregistrement W4389243107 · doi:10.1182/blood-2023-181886

Influence of Pre-Treatment Features and Therapy Choice By Physicians on Overall Survival in Older Adults with Acute Myeloid Leukemia: A Report from the Beat AML Master Trial

2023· article· en· W4389243107 sur OpenAlexfundno aff
Uma Borate, Ying Huang, Rina Li Welkie, Ronan Swords, Elie Traer, Eytan M. Stein, Tara L. Lin, Yazan F. Madanat, Prapti A. Patel, Robert H. Collins, Maria R. Baer, Vu H. Duong, William Blum, Martha Arellano, Wendy Stock, Olatoyosi Odenike, Robert L. Redner, Tibor Kovacsovics, Michael W. Deininger, Joshua F. Zeidner, Rebecca L. Olin, Catherine C. Smith, James M. Foran, Gary J. Schiller, Emily Curran, Kristin L Koenig, Nyla A. Heerema, Timothy F. Chen, Molly Martycz, Mona Stefanos, Sonja Marcus, Leonard Rosenberg, Brian Druker, Ross L. Levine, Amy Burd, Ashley O. Yocum, Alice S. Mims, John C. Byrd

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensnon disponible
Organismes subventionnairesGenentechSierra OncologyMorphoSysAstellas PharmaActuate TherapeuticsKaryopharm TherapeuticsRevolution MedicinesIncyteSyndax PharmaceuticalsOregon Health and Science UniversityBeiGeneBristol-Myers SquibbConstellation PharmaceuticalsAgios PharmaceuticalsAscentage PharmaActinium PharmaceuticalsMateon TherapeuticsJazz PharmaceuticalsAstex PharmaceuticalsDaiichi Sankyo EuropeNational Cancer InstituteServierFoghorn TherapeuticsGilead SciencesIterion TherapeuticsCelgeneAstraZenecaOno PharmaceuticalEli Lilly and CompanyAmgen
Mots-clésMedicineVenetoclaxAzacitidineInternal medicineOncologyMyeloid leukemiaClinical trialHematologyChemotherapyLeukemiaDNA methylation

Résumé

récupéré en direct d'OpenAlex

Background: Acute myeloid leukemia (AML) therapy in older patients (age ≥ 60) has undergone a transformation with the introduction of multiple targeted therapies, which has allowed more patients to receive therapy than before. The most successful has been the combination of venetoclax + azacitidine (VA) which generated higher overall complete response rates in phase 2 studies than would be expected with azacitidine alone, leading to accelerated FDA approval on 21Nov2018. The VIALE-A phase 3 study confirmed the improved overall survival (OS, median 14.7 versus 9.6 months) of VA, leading to full FDA approval for marketing. This retrospective analysis provides real world data on the impact of baseline clinical and genomic markers of individuals receiving intensive chemotherapy versus VA. Methods: The precision medicine Beat AML Master Trial (NCT03013998) assigns patients to biomarker specific sub-study treatments based on targeted DNA sequencing and cytogenetics. However, a large subset of patients did not enroll on a sub-study, but were followed for off-study treatment and OS. From this subset, patients enrolled onward from 21Nov2018, when VA received accelerated approval, were examined for differences in clinical/genetic characteristics and OS in those receiving venetoclax + hypomethylating agent (V/HMA), any form of intensive chemotherapy (IC), alternative non-intensive therapy (NIT), or no therapy. The genetic mutations identified in this study are characterized by a variant allele frequency of 20%+, as defined in the trial for determining the dominant clone. The method of Kaplan-Meier was used to estimate OS, and the Cox model was fit to associate patient characteristics with OS. Results: From 21Nov2018, a total of 468 AML patients consented to the Beat AML trial and did not enroll to a sub-study. Treatment was chosen by the investigator based upon available clinical and genomic data. Of these 468 patients, 62 did not receive treatment, 2 had treatment data missing, 226 were treated with V/HMA, 112 with IC, and 66 with NIT. Demographics for all patients include median age 71 (60-90), 40% female, performance status (PS) (0-20%; 1-55%; 2-22%; 3-3%), median white blood cell (WBC) 4.1 (range 0.3-298.6), complex karyotype (CK) 20.6%, core binding factor (CBF) 7.8%, KMT2A-rearranged 3.6%, NPM1-mutated (m) 15.6%, IDH2m 14.6%, TP53m 13.2%, FLT3-ITD/TKD 12.9%, and NRASm/ PTPN11m/ KRASm/ NF1m/ CBLm 23.6%. Demographics that were significantly different (p<0.01) among the three groups (V/HMA, IC, and NIT) include age (younger in IC), PS (worse in NIT), AST/ALT (worse in NIT), CBF (more in IC), CK and TP53m (less in IC). Of the 404 patients who underwent treatment with V/HMA, IC, or NIT, 208 have died with those surviving having a median follow-up of 22.3 months. Figure 1 summarizes the OS of each treatment group. The median OS (95% CI) from time of initiating therapy is 13.6 (10.9-16.8) for V/HMA, 33.8 (20.7-not reached) for IC, and 11.6 (5.2-21.3) months for NIT. Univariable analysis for OS was significant at p<0.05 for increased age, WBC, PS, hemoglobin, CBF, CK, NPM1m, TP53m, TET2m and IC versus V/HMA. Multivariable analysis was significant at p<0.05 (hazard ratio) for increased age (1.14), PS (1.83), WBC (1.08), hemoglobin (0.91), and select genomic aberrations including CBF (0.37), NPM1m (0.35), and TP53m (2.1). Conclusions: These results from a large cohort of older AML patients treated with V/HMA, IC, or NIT show that their outcome is best defined by pre-treatment clinical features previously identified including age, performance status, WBC and hemoglobin along with limited genomic characteristics including CBF, NPM1m, and TP53m. While univariate analysis of OS favored IC over V/HMA and NIT, multivariable analysis supports that this advantage was most likely due to the favorable clinical and genomic features. The OS of V/HMA patients in this cohort is similar to that in the VIALE-A registration study of VA, providing further justification for this treatment for older AML patients deemed ineligible for intensive chemotherapy. Additionally, this data supports use of the patient cohort in this study for ongoing work in understanding and/or validating biomarkers associated with survival with V/HMA.

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)0,010
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 enseignants0,004
Score d'incertitude au seuil0,023

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
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 Opus0,013
Tête enseignante GPT0,278
Écart entre enseignants0,264 · 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

Explorer davantage

Même revueBlood→Même sujetAcute Myeloid Leukemia Research→Travaux en français237 207→