Clinical Outcomes and Treatment Patterns in Adults With FLT3-ITDmut+ Acute Myeloid Leukemia Undergoing Allogeneic Hemopoietic Cell Transplantation in the United States and Canada
Notice bibliographique
Résumé
Allogeneic hematopoietic cell transplantation (alloHCT) is used to treat patients with acute myeloid leukemia (AML) with internal tandem duplication of the FMS-like tyrosine kinase 3 gene (FLT3-ITDmut+). However, the effect of different characteristics on outcomes after transplant is not fully understood. To determine the impact of patient, disease, and transplant characteristics on clinical outcomes and trends in maintenance therapy for patients with FLT3-ITDmut+ AML who underwent their first alloHCT. This was an observational cohort study of adults ≥18 years who were recipients of human leukocyte antigen identical sibling, haploidentical, 8/8 or 7/8 unrelated, or cord blood donor alloHCT in the United States and Canada between 2014‒2019. Patient, disease, and transplant characteristics were collected from CIBMTR (Center for International Blood & Marrow Transplant Research) between 2014‒2022. Patients enrolled in the MORPHO clinical trial (NCT02997202) were excluded. Clinical outcomes were measured from the time of alloHCT by disease status: first complete remission (CR1), second or greater CR (≥CR2) or relapsed/refractory (R/R). The primary endpoints of this study were overall survival (OS) and leukemia-free survival (LFS). Key secondary endpoints included relapse after alloHCT, non-relapse mortality (NRM), time from diagnosis to complete remission, time from complete remission to alloHCT, and maintenance therapy before and after alloHCT. Univariate analyses were conducted with Gray's test and log-rank test, while multivariable analyses were conducted using Cox proportional hazards models. A total of 3147 eligible patients (CR1, n=2389; ≥CR2, n=340; R/R, n=418) were included. Most patient, disease, and transplant characteristics were similar between different disease statuses. In univariate analyses, disease status of CR1 compared with ≥CR2 or R/R was significantly (p<0.001) associated with improved OS and LFS, and decreased probability of relapse; NRM likely differed across cohorts after alloHCT (p=0.003). In multivariable analyses, patients with a disease status of ≥CR2 and R/R compared with CR1 had significantly shorter OS (hazard ratio [HR] 95% confidence interval [CI], 1.43 [1.19–1.72], p=0.0001, and 2.14 [1.88–2.44], p<0.0001, respectively). Patients with a disease status of CR1 at ≤2.6 months had better LFS compared with ≥CR2 and R/R (HR [95% CI], 2.03 [1.56–2.63], p<0.0001 and 3.98 [3.07–5.17], p<0.0001, respectively). Patients with a ≥CR2 or R/R disease status at ≤2.6 months had an increased likelihood of relapse compared with CR1 (HR [95% CI], 2.46 [1.82–3.33], p<0.0001 and 4.68 [3.46–6.34], p<0.0001, respectively). Disease status was not significantly associated with NRM. We also identified several additional patient, disease, and transplant characteristics that may be associated with inferior OS and/or LFS and greater relapse and/or NRM. Maintenance therapy usage after alloHCT increased from 2014 to 2019 primarily due to increased FLT3 inhibitor use. In this largest study to date of patients from the US and Canada with FLT3-ITDmut+ AML, disease status of CR1 at the time of alloHCT was associated with better clinical outcomes. Additional factors were identified that may also impact clinical outcomes, and in total, have the potential to inform clinical decision-making.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».