Extramedullary disease in AML: A high-risk feature beyond ELN 2022 classification
Notice bibliographique
Résumé
Abstract Background Extramedullary disease (EMD) in acute myeloid leukemia (AML) involves leukemic infiltration outside the bone marrow and is observed in up to 25% of patients. Despite its frequency, EMD is not currently incorporated into the European LeukemiaNet (ELN) 2022 risk stratification system. Recent studies have demonstrated molecular discordance between leukemic cells in the bone marrow and those found at extramedullary (EM) sites, raising concerns that molecular profiling based solely on bone marrow samples may not adequately guide clinical management of patients with EMD. Objective To characterize the clinical features, treatment outcomes, and prognostic implications of EMD in a large, retrospective cohort of AML patients treated over two decades at Princess Margaret Cancer Centre. Methods We conducted a retrospective analysis of 617 adult AML patients, categorizing them into non-EMD (n=371) and EMD groups (n=246). The EMD group was further subdivided into isolated EM involvement (n=53) and concurrent marrow and EM involvement (n=193). We compared complete remission (CR) rates, relapse rates, rates of allogeneic hematopoietic stem cell transplantation (allo-HSCT), overall survival (OS), and event-free survival (EFS). Propensity score matching (PSM) was used to adjust for differences in age, ELN risk category, induction regimen, and allo-HSCT. Multivariate analyses (MVA) were performed to identify independent prognostic factors. Results Among the 246 patients with EMD, 53 (21.5%) had isolated EMD, while 193 (78.5%) presented with concurrent bone marrow involvement. CR rates following induction therapy were similarly high in both groups (96% in isolated EMD vs. 89% in combined involvement; p=0.18). Relapse rates (32% vs. 34%; p=0.77) and rates of allogeneic HSCT (40% vs. 32%; p=0.32) were also comparable, indicating similar outcomes between isolated EMD and concurrent marrow involvement with EMD.Prior to PSM, comparing non-EMD from 2015-2018 (n=371) patients to EMD patients (n=246), EMD patients were significantly younger (p=0.04) and had more intermediate-risk disease (60% vs. 19%, p<0.01) and NPM1 mutations (48% vs. 25%, p<0.01). They received intensive induction therapy more frequently (89% vs. 74%, p<0.01) but underwent allo-HSCT less often (34% vs. 43%, p=0.02). OS and EFS were significantly inferior in the EMD group (median OS: 14.2 vs. 53.2 months; median EFS: 10.6 vs. 43.7 months; both p<0.0001). After PSM (168 matched pairs), EM remained associated with inferior OS (median 14.2 vs. 64.1 months; and EFS :9.5 vs. 55.9 months; both p<0.0001).MVA confirmed EMD as an independent adverse prognostic factor for OS (HR 1.87, 95% CI 1.2–2.91, p=0.005) and EFS (HR 1.93, 95% CI 1.36–2.75, p=0.0002). Among EMD patients, allo-HSCT was associated with improved EFS (HR 0.49, 95% CI 0.24–0.99, p=0.048), although OS benefit did not reach significance (HR 0.60, p=0.20).The most common EM involvement sites were the skin (39%) and central nervous system (CNS; 15%). Neither specific EM site involvement, nor mutations frequently identified in EMD patients (NPM1, TET2, ASXL1, DNMT3A) were significantly associated with differences in OS or EFS.Notably, within the ELN 2022 favorable-risk subgroup, EMD presence was associated with higher relapse rates (31% vs. 14%, p=0.059) and trends toward inferior median OS (54.7 months vs. not reached, p=0.08) and EFS (40.6 months vs. not reached, p=0.05), highlighting its prognostic significance even in traditionally lower-risk AML patients. Conclusions This large, retrospective study emphasizes the negative prognostic impact of EMD in AML, independent of ELN risk stratification, even among patients classified as favorable-risk. Although allo-HSCT may offer some improvement in disease control, it does not fully overcome the poor prognosis linked to EMD. Additionally, these results underscore the importance of site-specific molecular profiling in guiding therapeutic decisions. EMD warrants inclusion in future AML risk stratification models and prospective therapeutic trials.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».