Intravenous Busulfan Compared with Total Body Irradiation Pretransplant Conditioning for Adults with Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
Total body irradiation (TBI) has been included in standard conditioning for acute lymphoblastic leukemia (ALL) before hematopoietic cell transplantation (HCT). Non-TBI regimens have incorporated busulfan (Bu) to decrease toxicity. This retrospective study analyzed TBI and Bu on outcomes of ALL patients 18-60 years old, in first or second complete remission (CR), undergoing HLA-compatible sibling, related, or unrelated donor HCT, who reported to the Center for International Blood and Marrow Transplant Research from 2005 to 2014. TBI plus etoposide (25%) or cyclophosphamide (75%) was used in 819 patients, and intravenous Bu plus fludarabine (41%), clofarabine (30%), cyclophosphamide (15%), or melphalan (13%) was used in 299 patients. Bu-containing regimens were analyzed together, since no significant differences for patient outcomes were noted between them. Bu patients were older, with better performance status; took longer to achieve first CR and receive HCT; were treated more recently; and were more likely to receive peripheral blood grafts, antithymocyte globulin, or tyrosine kinase inhibitors. With median follow-up of 3.6 years for Bu and 5.3 years for TBI, adjusted 3-year outcomes showed treatment-related mortality Bu 19% versus TBI 25% (P = .04); relapse Bu 37% versus TBI 28% (P = .007); disease-free survival (DFS) Bu 45% versus TBI 48% (P = .35); and overall survival (OS) Bu 57% versus TBI 53% (P = .35). In multivariate analysis, Bu patients had higher risk of relapse (relative risk, 1.46; 95% confidence interval, 1.15 to 1.85; P = .002) compared with TBI patients. Despite the higher relapse, Bu-containing conditioning led to similar OS and DFS following HCT for ALL.
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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 | 0.000 | 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 | 0.001 |
| 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".