Allogeneic Hematopoietic Stem Cell Transplantation Is an Effective Salvage Therapy for Patients with Chronic Myeloid Leukemia Failing Treatment with Tyrosine Kinase Inhibitors
Notice bibliographique
Résumé
Abstract Tyrosine kinase inhibitor (TKI) therapy has revolutionized the treatment of patients (pts) with chronic myeloid leukemia (CML). While allogeneic hematopoietic stem cell transplantation (HSCT) remains the only known curative therapy for CML, it is now rarely utilized given the excellent long-term results with TKI treatment. Therefore, only a few reports are available detailing HSCT outcome for this pt population. The purpose of this study is to examine HSCT outcome for pts with CML who received TKI therapy and identify predictors of survival, relapse and non-relapse mortality (NRM). Between January 2002 and April 2012, 55 pts with CML underwent HSCT at the Leukemia/BMT Program of BC. Transplant indications were advanced disease at diagnosis (15), TKI resistance as defined by the ELN treatment guidelines (30), TKI intolerance (2), physician preferance (4). Four pts had not received TKI therapy during this time period and were excluded from further analysis. Of the 51 pts examined in this study there were 34 males and 17 females. The median age at HSCT was 45 years and the Sokal score at diagnosis was low risk or intermediate risk (22), high risk (28) and unknown (1). The median time from diagnosis to HSCT was 307 days. Therapy prior to HSCT was imatinib (IM) only (22); IM with chemotherapy (19); IM followed by dasatinib and/or nilotinib (10). Disease status at HSCT was first chronic phase (CP1) (19), accelerated phase (9), CP2 (19), CP3 (3), BP (1). Four pts had kinase domain mutations identified at HSCT. EBMT score was 1-4 (33), and 5-7 (18). HSCT was myeloablative in 48 pts [TBI-based (25); BuCY (23)] and reduced intensity in 3 pts. Stem cell source was bone marrow (8) or PBSC (43) from a HLA matched sibling (24), HLA matched unrelated donor (UD) (18) or mismatched UD (9). At a median follow-up of 5.9 years, 18 pts have relapsed [molecular (7), cytogenetic (1), hematologic (10)] and 16 pts have died [relapse (8), GVHD (3), infection (2) regimen related toxicity (2), cerebral hemorrhage (1)]. The overall survival (OS), event-free survival (EFS), relapse and NRM at 8 years was 68%, 46%, 41% and 23% respectively. The corresponding results for the 32 pts transplanted for TKI resistance/intolerance were 75% (OS), 52% (EFS), 39% (relapse) and 15% (NRM). In univariate analysis, disease status at HSCT (p=.0005), lower EBMT score (p=.04), complete molecular response (CMR) to HSCT (p<.0001), and Sokal score (p=.05) predicted for better OS. Donor (female) to pt (male) gender combination (p=.02), presence of cGVHD (p=.04) and CMR to HSCT (p<.0001) predicted for lower relapse. Predictors of NRM included disease status at HSCT (p=.008), lower EBMT score (p=.004) and CMR to HSCT (p<.0001). In multivariate analysis, CMR to HSCT remained an independent predictor of OS [odds ratio (OR) 43], EFS (OR 56), relapse (OR 29) and NRM. Donor (female) to pt (male) also remained an independent predictor of EFS (OR 6) and relapse (OR 3). In conclusion, HSCT remains an effective salvage therapy for pts with CML in the TKI era who present with advanced disease or resistance/intolerance to TKI therapy. Disease status at HSCT and achievement of CMR are strong predictors of OS, EFS, relapse and NRM. Disclosures No relevant conflicts of interest to declare.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».