Allogeneic hematopoietic cell transplantation for adults with acute myeloid leukemia: myths, controversies, and unknowns
Bibliographic record
Abstract
Progress in the last decade has improved the understanding of leukemia biology. Molecular markers in combinations with cytogenetics have improved the risk stratification of acute myeloid leukemia (AML) and informed decision-making. In parallel, several important advances in the transplant field, such as better supportive care, improved transplant technology, increased availability of alternative donors, and reduced-intensity conditioning have improved the safety as well as access of allogeneic hematopoietic cell transplantation (HCT) for a larger number of patients. In this review, the positioning of HCT in the management of patients with AML is evaluated in view of changing risk/benefit ratios associated with both conventional treatments and transplantation, and some of the controversies are addressed in light of emerging data. Increasing data demonstrate outcomes of alternative donor transplantation approaching HLA-identical sibling donors in high-risk AML supporting the inclusion of alternative donors in trials of prospective studies evaluating post remission strategies for high-risk AML. The use of reduced-intensity conditioning has expanded the eligibility of HCT to older patients with AML, and outcome data are encouraging. Continued study of HCT versus alternative therapies is required to optimize patients' outcomes in AML.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| 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".