Impact of cytogenetics on outcome of matched unrelated donor hematopoietic stem cell transplantation for acute myeloid leukemia in first or second complete remission
Bibliographic record
Abstract
We compared the treatment-related mortality, relapse rate, disease-free survival (DFS), and overall survival (OS) by cytogenetic risk group of 261 patients with acute myeloid leukemia in first complete remission (CR1) and 299 patients in CR2 in undergoing matched unrelated donor hematopoietic stem cell transplantation (HSCT). For patients in first CR, the DFS and OS at 5 years were similar for the favorable, intermediate, and unfavorable risk groups at 29% (95% confidence interval [CI], 8%-56%) and 30% (22%-38%); 27% (19%-39%) and 29% (8%-56%); and 30% (95% CI, 22%-38%) and 30% (95% CI, 20%-41%), respectively. For patients in second CR, the DFS and OS at 5 years were 42% (95% CI, 33%-52%) and 35% (95% CI, 28%-43%); 38% (95% CI, 23%-54%) and 45% (95% CI, 35%-55%); and 37% (95% CI, 30%-45%) and 36% (95% CI, 21%-53%), respectively. Cytogenetics had little influence on the overall outcome for patients in first CR. In second CR, outcome was modestly, but not significantly, better for patients with favorable cytogenetics. The graft-versus-leukemia effect appeared effective, even in patients with unfavorable cytogenetics. However, treatment-related mortality was high. Matched unrelated donor HSCT should be considered for all patients with unfavorable cytogenetics who lack a suitable HLA-matched sibling donor.
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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".