Stem cell allografting for chronic Myeloid leukemia in the tyrosine kinase era – forgotten but not gone
Bibliographic record
Abstract
Due to the remarkable success of tyrosine kinase inhibitors (TKI) in chronic myeloid leukemia (CML), allogeneic stem cell transplantation (alloSCT) is not first-line treatment for delivering durable, long-term survival. Consequently, alloSCT is reserved for patients with TKI-resistant or TKI-intolerant chronic phase CML (CP-CML) and advanced phase CML (AP-CML). Advances in transplant technology, such as high-resolution HLA typing, introduction of reduced intensity conditioning and increased alternative donor availability, coupled with improved supportive care, have significantly reduced transplant-related mortality and expanded the pool of transplant-eligible patients. Refinement of conditioning regimens, innovative use of post-transplant cellular and pharmacological therapies, and judicious post-transplant monitoring are important strategies for reducing risk of relapse. Given its potential to cure, alloSCT will invariably remain a key part of the treatment algorithm. This article reviews the data underpinning the role and outcomes of alloSCT and provides an update on current recommendations.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".