Maintenance Tyrosine Kinase Inhibitors Following Allogeneic Hematopoietic Stem Cell Transplantation for Chronic Myelogenous Leukemia: A Center for International Blood and Marrow Transplant Research Study
Bibliographic record
Abstract
It remains unknown whether the administration of tyrosine kinase inhibitors (TKIs) targeting BCR-ABL1 after allogeneic hematopoietic cell transplantation (HCT) is associated with improved outcomes for patients with chronic myelogenous leukemia (CML). In this registry study, we analyzed clinical outcomes of 390 adult patients with CML who underwent transplantation between 2007 and 2014 and received maintenance TKI following HCT (n = 89) compared with no TKI maintenance (n = 301), as reported to the Center for International Blood and Marrow Transplant Research. All patients received TKI therapy before HCT. The majority of patients had a disease status of first chronic phase at HCT (n = 240; 62%). The study was conducted as a landmark analysis, excluding patients who died, relapsed, had chronic graft-versus-host disease, or were censored before day +100 following HCT. Of the 89 patients who received TKI maintenance, 77 (87%) received a single TKI and the other 12 (13%) received multiple sequential TKIs. The most common TKIs used for maintenance were dasatinib (n = 50), imatinib (n = 27), and nilotinib (n = 27). As measured from day +100, the adjusted estimates for 5-year relapse (maintenance, 35% versus no maintenance, 26%; P = .11), leukemia-free survival (maintenance, 42% versus no maintenance, 44%; P = .65), or overall survival (maintenance, 61% versus no maintenance, 57%; P = .61) did not differ significantly between patients receiving TKI maintenance or no maintenance. These results remained unchanged in multivariate analysis and were not modified by disease status before transplantation. In conclusion, our data from this day +100 landmark analysis do not demonstrate a significant impact of maintenance TKI therapy on clinical outcomes. The optimal approach to TKI administration in the post-transplantation setting in patients with CML remains undetermined.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".