Reduced-toxicity conditioning therapy with allogeneic stem cell transplantation for acute leukemia
Bibliographic record
Abstract
We hypothesized that standardized systemic drug delivery would improve treatment safety and provide better leukemia control. We therefore developed an intravenous busulfan formulation and combined it with fludarabine instead of cyclophosphamide in preparation for allogeneic stem cell transplantation (alloSCT). We used a Bayesian method to compare the outcomes of 67 acute myeloid leukemia (AML)/myelodysplastic syndrome (MDS) patients who received intravenous busulfan-cyclophosphamide (BuCy2) with 148 subsequent AML/MDS patients who received busulfan-fludarabine (Bu-Flu). The groups had comparable pretreatment characteristics, except that the Bu-Flu patients were older, more often had unrelated donors and had a shorter follow-up. A greatly improved outcome in the Bu-Flu group is unlikely to be explained by improved supportive care during this time period. Overall, the data support replacing BuCy2 with or without antithymocyte globulin (ATG) with Bu-Flu with or without rabbit-ATG for AML or MDS. We further suggest that the high level of safety and fast recovery from conditioning therapy-related side effects after the Bu-Flu regimen makes it a suitable platform technology for testing additional adjuncts for improved posttransplant immune recovery and long-term disease control in patients who are at high risk of rapidly recurrent disease after alloSCT. The extremely low one-year treatment-related mortality as well as high overall and event-free survival of patients in the Bu-Flu group indicate that it is time to revisit the value of alloSCT compared with conventional maintenance chemotherapy for patients in first complete remission of AML/MDS.
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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 | 0.001 |
| 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".