PS1043 OUTCOMES OF PATIENTS WITH RELAPSED OR REFRACTORY ACUTE MYELOID LEUKEMIA: A POPULATION‐BASED REAL‐WORLD STUDY
Notice bibliographique
Résumé
Background: Patients (pts) with acute myeloid leukemia (AML) may be treated with intensive or non‐intensive chemotherapy. While some pts achieve complete remission (CR) after initial treatment, a significant proportion become refractory to initial treatment or relapse after the initial response. Aims: To understand treatment patterns and outcomes in pts with relapsed or refractory AML (RR‐AML) in a real‐world setting. Methods: The Alberta Cancer Registry and local databases of the University of Alberta Hospital and the Tom Baker Cancer Centre were interrogated to identify AML pts with RR‐AML aged ≥18 years treated from January 2013 to December 2016. Pts were considered to have refractory AML if they failed to achieve CR or achieved CR with incomplete count recovery (CRi) after 2 cycles of intensive chemotherapy, 6 cycles of azacytidine, or 4 cycles of low‐dose cytarabine. Based on the treatment regimen received following the diagnosis of RR‐AML, pts were grouped as receiving either intensive therapy (IT), non‐intensive therapy (NIT), or best supportive care (BSC) and were followed from relapse to date of death or last follow‐up. Results: Overall, 572 pts with AML were identified from the database search, 199 (124 males, 75 females) of whom met the eligibility criteria for RR‐AML and were included in this analysis. The median age at diagnosis of RR‐AML was 66.8 years; median follow‐up was 4.7 months. According to the European LeukemiaNet (ELN) 2010 classification, 34 pts (17%) had a favorable risk, 102 (51%) intermediate (Int) risk, 59 (30%) adverse risk profile and 4 (2%) with unknown status. After relapse or refractoriness (RR), 88 pts (44%) received BSC, 46 (23%) received IT with fludarabine, cytarabine + granulocyte colony‐stimulating factor (FLAG) (n = 5), FLAG + idarubicin (n = 29), or another regimen (n = 12), while 65 (33%) received NIT with azacitidine ± another agent (n = 49), low‐dose cytarabine ± another agent (n = 12), or an alternative regimen (n = 4). The unadjusted median overall survival (mOS) for the overall study cohort was 5.3 months from the time of RR with a 12‐month OS rate of 29.6% (95% CI 29.0–30.3). The mOS was 13.8, 9.4, and 2.1 months for IT, NIT, and BSC groups, respectively ( P < 0.001) (Figure). The mOS for pts aged <60 years was 8.3 vs 4.5 months for those ≥60 years ( P = 0.009). Following RR, 16 (8%) pts received an allogeneic stem cell transplant (ASCT), for whom median survival was not reached, vs 4.5 months in pts who did not undergo transplantation. The mOS for pts with an ELN favorable, Int‐I, Int‐II, and adverse risk profile was 12.4, 4.5, 4.7, and 4.0 months, respectively ( P = 0.002). In a multivariable Cox regression model incorporating age, ELN risk group, treatment intensity pre‐RR, number of treatment lines pre‐RR, best response pre‐RR, treatment intensity post‐RR, and ASCT post‐RR, treatment intensity post‐RR (NIT vs BSC: hazard ratio [HR] for mortality 0.32; 95% CI 0.23–0.48; IT vs BSC: HR for mortality 0.26; 95% CI 0.16–0.43) and best response pre‐RR (CR/CRi <12 months vs all others: HR for mortality 0.55, 95% CI 0.33–0.92) were significantly associated with OS. Summary/Conclusion: In a real‐world setting, a high proportion of pts only receive BSC, which is associated with very short survival. Treatment regimen post‐RR is the major predictor of survival, with non‐intensively and intensively treated pts having better outcomes compared to pts who received BSC. However, the overall outcomes of pts with RR‐AML remain poor regardless of treatment, and new therapies are urgently needed. image
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 tête enseignante, 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 ».