Does Total Body Irradiation Conditioning Improve Outcomes of Myeloablative Human Leukocyte Antigen–Identical Sibling Transplantations for Chronic Lymphocytic Leukemia?
Bibliographic record
Abstract
An allogeneic hematopoietic cell transplantation from an HLA-identical donor after high-dose (myeloablative) pretransplantation conditioning is an effective therapy for some people with chronic lymphocytic leukemia (CLL). Because CLL is a highly radiosensitive cancer, we hypothesized that total body irradiation (TBI) conditioning regimens may be associated with better outcomes than those without TBI. To answer this, we analyzed data from 180 subjects with CLL receiving myeloablative doses of TBI (n = 126) or not (n = 54), who received transplants from an HLA-identical sibling donor between 1995 and 2007 and reported to the Center for International Blood & Marrow Transplant Research. At 5 years, treatment-related mortality was 48% (95% confidence interval [CI], 39% to 57%) versus 50% (95% CI, 36% to 64%); P = NS. Relapse rates were 17% (95% CI, 11% to 25%) versus 22% (95% CI, 11% to 35%); P = NS. Five-year progression-free survival and overall survival were 34% (95% CI, 26% to 43%) versus 28% (95% CI, 15% to 42%); P = NS and 42% (95% CI, 33% to 51%) versus 33% (95% CI, 19% to 48%); P = NS, respectively. The single most common cause of death in both cohorts was recurrent/progressive CLL. No variable tested in the multivariate analysis was found to significantly affect these outcomes, including having failed fludarabine. Within the limitations of this study, we found no difference in HLA-identical sibling transplantation outcomes between myeloablative TBI and chemotherapy pretransplantation conditioning in persons with CLL.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".