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Enregistrement W4417009029 · doi:10.1182/blood-2025-5178

Performance of the ELN 2022 risk stratification in a real-world Canadian AML patient population

2025· article· en· W4417009029 sur OpenAlexaffabout
Eric J. Zhao, Sujaatha Narayanan, Florian Kuchenbauer, Stephen H. Nantel, Thomas J. Nevill, Yasser Abou Mourad, Shanee Chung, Donna L. Forrest, Hannah Cherniawsky, Judith Anula Rodrigo, Kevin Song, Cynthia L. Toze, Jennifer White, Claudie Roy, Aly Karsan, Ryan J. Stubbins, David Sanford

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensCanada's Michael Smith Genome Sciences CentreLeukemia & Lymphoma Society of CanadaUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMyeloid leukemiaCohortCEBPARisk stratificationPopulationCohort studyLeukemiaFramingham Risk ScoreSurvival analysis

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction The 2022 European Leukemia Network (ELN) risk stratification system for acute myeloid leukemia (Dohner et al, Blood, 2022) added several myelodysplasia-related (MR) genetic mutations to the adverse risk category, assigned FLT3-ITD mutations to the intermediate risk category, and designated bZIP in-frame mutations in CEBPA as favorable risk. Several studies have validated this system, though many of these are based on clinical trial cohorts with a bias towards younger patients. We performed an analysis of outcomes using this risk stratification system on a Canadian, population-based cohort of intensively treated AML patients. Methods Adults diagnosed with AML in British Columbia (BC) from 2016-2023, who received cytarabine-anthracycline induction, were identified from the provincial Leukemia/BMT registry. All patients had conventional karyotyping and a next-generation sequencing panel performed at diagnosis. The primary outcome was overall survival (OS) according to the ELN 2022 classification. Secondary outcomes included rate of complete remission (CR) or CR with incomplete count recovery (CRi), event-free survival (EFS), outcome within risk categories, and outcome following stem cell transplant. Categorical variables were compared using Chi-square and Fisher's exact tests and continuous variables were compared using paired t-tests. The Kaplan-Meier method was used to estimate survival and log-rank test was used to compare differences between groups. Results Among 499 patients who met our inclusion criteria, the median age was 62 years, with 59.2% males. De novo AML represented 83.4% of cases, 10.8% arose from prior MDS/MPN, and 5.8% had therapy-related AML. Allogeneic stem cell transplant (alloSCT) was performed in 57.1% of cases (48.9% in CR1). The rates of alloSCT in CR1 in ELN 2022 favorable, intermediate and adverse risk categories were 16.2%, 64.5% and 62.8%, respectively. By ELN 2017 and ELN 2022 criteria, 36.6% and 30.9% of patients were favorable risk, 20% and 27.7% were intermediate risk, and 37.9% and 41.5% were adverse risk, respectively; 26 (5%) patients were not classifiable by ELN 2017 as the FLT3-ITD allelic ratio was not available. After a median follow-up of 40 months in surviving patients, median OS of ELN 2022 favorable-risk disease differed significantly from those with intermediate- and adverse-risk disease (75 months vs 30 months and 27 months, p=0.011). Median OS of the intermediate- and adverse-risk groups did not differ significantly. Three-year OS was 61%, 44% and 47% in the favorable, intermediate and adverse risk groups, respectively. After 1 cycle of intensive therapy, the rates of CR/CRi were 85.7%, 62.3% and 43.5% in favorable, intermediate and adverse risk patients (p<0.001). Event-free survival (EFS) was longer for the favorable risk category, but not significantly different between the intermediate and adverse risk categories (3-year median EFS 47%, 35% and 36%, respectively). OS within the defined subtypes of ELN 2022 favorable (p=0.19) and intermediate risk (p=0.16) disease was not significantly different, but differed significantly within the adverse risk group subtypes (p<0.001). Patients with AML with mutated TP53, KMT2A rearrangement, or MECOM rearrangement had a relatively shorter OS with median OS of 6.5 months, 13.5 months and 26 months respectively. In contrast, patients with wild-type TP53 with MR mutations or with complex karyotype, −5/del(5q) or −7 had a median OS 44 months and 46 months, respectively. The median OS for patients with t(6;9) was similar to the favorable risk group, with the median OS was not reached in the small number of patients (n=6). OS of patients following alloSCT was not statistically different according to the ELN 2022 risk groups (p=0.075), although this was performed in CR2 or later for most favorable risk patients. Conclusions In our cohort, which represents an unselected, recent and ethnically diverse real-world population, the ELN 2022 criteria does not discriminate between survival outcomes for intermediate- and adverse-risk patients. A relatively high proportion of patients underwent alloSCT within our cohort, which may have improved the very poor outcome usually associated with the adverse risk group. Further work is needed to refine prognostication, particularly within the currently defined adverse risk group.

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)0,002
score de la tête « metaresearch » (Gemma)0,004
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 enseignants0,060
Score d'incertitude au seuil0,136

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,004
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0010,001
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 Opus0,011
Tête enseignante GPT0,271
Écart entre enseignants0,260 · 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
Publié2025
Routes d'admission2
Résumé présentoui

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