Choice of conditioning regimens for bone marrow transplantation in severe aplastic anemia
Bibliographic record
Abstract
Allogeneic bone marrow transplantation (BMT) is curative therapy for the treatment of patients with severe aplastic anemia (SAA). However, several conditioning regimens can be used for BMT. We evaluated transplant conditioning regimens for BMT in SAA after HLA-matched sibling and unrelated donor BMT. For recipients of HLA-matched sibling donor transplantation (n = 955), fludarabine (Flu)/cyclophosphamide (Cy)/antithymocyte globulin (ATG) or Cy/ATG led to the best survival. The 5-year probabilities of survival with Flu/Cy/ATG, Cy/ATG, Cy ± Flu, and busulfan/Cy were 91%, 91%, 80%, and 84%, respectively (P = .001). For recipients of 8/8 and 7/8 HLA allele-matched unrelated donor transplantation (n = 409), there were no differences in survival between regimens. The 5-year probabilities of survival with Cy/ATG/total body irradiation 200 cGy, Flu/Cy/ATG/total body irradiation 200 cGy, Flu/Cy/ATG, and Cy/ATG were 77%, 80%, 75%, and 72%, respectively (P = .61). Rabbit-derived ATG compared with equine-derived ATG was associated with a lower risk of grade II to IV acute graft-versus-host disease (GVHD) (hazard ratio [HR], 0.39; P < .001) but not chronic GVHD. Independent of conditioning regimen, survival was lower in patients aged >30 years after HLA-matched sibling (HR, 2.74; P < .001) or unrelated donor (HR, 1.98; P = .001) transplantation. These data support Flu/Cy/ATG and Cy/ATG as optimal regimens for HLA-matched sibling BMT. Although survival after an unrelated donor BMT did not differ between regimens, use of rabbit-derived ATG may be preferred because of lower risks of acute GVHD.
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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".