Allogeneic Hematopoietic Stem Cell Transplantation Is an Effective Salvage Therapy for Patients with Chronic Myeloid Leukemia Failing Treatment with Tyrosine Kinase Inhibitors
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".