Influence of conditioning regimen intensity on outcomes post‐allogeneic hematopoietic cell transplantation for acute myeloid leukemia in complete morphological remission
Bibliographic record
Abstract
INTRODUCTION: The literature comparing outcomes between myeloablative (MAC) and reduced intensity conditioning (RIC) for acute myeloid leukemia (AML) is conflicting. METHODS: We retrospectively analyzed 451 patients who underwent allogenic hematopoietic cell transplantation (alloHCT) for AML in complete remission (CR) with either RIC (n = 331) or MAC (n = 120) with the use of dual T-cell depletion as graft-versus-host disease (GVHD) prophylaxis. RESULTS: Univariate analysis demonstrated nonrelapse mortality (NRM) at 2 years was 19.1% for MAC and 22.5% for RIC (p = .44). Two-year cumulative incidence of relapse (CIR) was 19.8% for MAC and 24.5% for RIC (p = .15). Two-year overall survival (OS) was 61% and 53% for MAC and RIC, respectively (p = .02). Two-year graft-versus-host disease relapse-free survival (GRFS) was 40.8% for MAC and 33.7% for RIC (p = .30). A propensity score-matched analysis was done matching patients for age, HLA match, in vivo T-cell depletion, and Disease Risk Index (DRI). Two-year OS was 67% for MAC, 66% for RIC (p = .95). A subgroup analysis identified that matched related donor transplants benefit from MAC with OS at 2 years 82.6% versus 57.3% for RIC (p = .006). CONCLUSIONS: In the matched-related donor setting, MAC regimens may offer superior survival. Overall, for our cohort of predominantly in vivo T-cell depleted patients the outcomes of MAC and RIC were similar.
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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 | 0.001 | 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 | 0.000 |
| 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".