Outcomes of Allogeneic Transplantation in Patients Aged ≤ 60 Years with Acute Myeloid Leukemia in Second Complete Remission: A CIBMTR ® Cohort Analysis
Notice bibliographique
Résumé
Abstract Introduction: Allogeneic hematopoietic cell transplantation (HCT) has demonstrated survival benefit in younger patients with intermediate/high-risk acute myeloid leukemia (AML), while data for older patients transplanted in CR2 in particular are limited. The purpose of the presented study was to retrospectively investigate within the CIBMTR database parameters that influence post-transplant outcome for patients aged ≥60 undergoing allogeneic HCT for AML in CR2. Methods: Using the CIBMTR database, patients aged ≥60 years with AML in CR2 who underwent HCT between 2001 and 2012 were identified. A number of patient, disease and transplant-related variables were analysed, and outcomes studied included overall survival (OS), leukemia-free survival (LFS), cumulative incidence of relapse (CIR), and non-relapse mortality (NRM). Results: Intotal, 196 patients with AML in CR2 met the eligibility criteria for this study. Median follow-up of survivors was 73 (6-123) months. Median age at transplant was 64 years (range 60-78), 81 patients (41%) were female. Seventy one percent had a Karnofsky performance status ≥90%. De novo AML was diagnosed in 147 patients (75%). Concerning cytogenetics at diagnosis (SWOG/ECOG), 16 patients (8%) were favorable, 133 (68%) were intermediate and 17 (9%) were unfavorable risk, while 30 patients (15%) had missing data. Concerning duration of CR1, 48 patients (24%) demonstrated <6 months, 48 patients (24%) 6-12 months and 74 patients (38%) ≥12 months, missing data in 26(13%). Myeloablative conditioning regimens were used in 37 patients (19%). Fifty-eight patients (30%) had matched sibling donors, 99 (51%) were well-matched unrelated and 39 (20%) were partially matched unrelated. Peripheral blood stem cells were used in 171 patients (87%), 58 patients (30%) received in vivo T-cell depletion. Univariate analysis demonstrated a 3-year OS of 42% (95% confidence intervals [CI] 35-49), LFS of 37% (95% CI 30-44), NRM of 25% (95% CI 19-32), and CIR of 38% (95% CI 31-45). Cumulative incidence of acute GvHD at 100 days was 33% (95% CI 26-40) while chronic GvHD at 3-years was 54% (95% CI 46-61). Cytogenetics was the only independent risk factor (relative risk [RR] 1.14 (95% CI 0.59-2.19) and 2.32 (95% CI 1.05-5.14) for intermediate and unfavorable risk respectively) for survival in multivariate analysis. For CIR, cytogenetic risk was the predominant prognostic factor (RR 1.10 (95% CI 0.47-2.56) and 2.98 (95% CI 1.11-8.00) for intermediate and unfavorable risk respectively, p=0.008). A higher NRM was observed with bone marrow graft source (RR 2.75, p=0.002) and male gender (RR 2.04, p=0.02). Conclusion: This study demonstrates the potential of long-term remissions with HCT in selected older patients with AML in CR2. Patients with adverse risk cytogenetics had very poor outcome due to higher risk of post-transplant relapse, and novel strategies are required for these patients. Disclosures Gupta: Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Honoraria, Research Funding.
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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 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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 ».