Outcomes of Human Leukocyte Antigen–Matched Sibling Donor Hematopoietic Cell Transplantation in Chronic Lymphocytic Leukemia: Myeloablative Versus Reduced-Intensity Conditioning Regimens
Bibliographic record
Abstract
Allogeneic hematopoietic cell transplantation (HCT) can cure some chronic lymphocytic leukemia (CLL) subjects. This study compared outcomes of myeloablative (MA) and reduced-intensity conditioning (RIC) transplants from HLA-matched sibling donors (MSD) for CLL. From 1995 to 2007, information regarding 297 CLL subjects was reported to the Center of International Blood and Marrow Transplant Research; of these, 163 underwent MA and 134 underwent RIC MSD HCT. The MA subjects underwent transplantation less often after 2000 and less commonly received antithymocyte globulin (4% versus 13%, P = .004) or prior antibody therapy (14% versus 53%; P < .001). RIC was associated with a greater likelihood of platelet recovery and less grade 2 to 4 acute graft-versus-host disease compared with MA conditioning. One- and 5-year treatment-related mortality (TRM) were 24% (95% confidence intervals [CI], 16% to 33%) versus 37% (95% CI, 30% to 45%; P = .023), and 40% (95% CI, 29% to 51%) versus 54% (95% CI, 46% to 62%; P = .036), respectively, and the relapse/progression rates at 1 and 5 years were 21% (95% CI, 14% to 29%) versus 10% (95% CI, 6% to 15%; P = .020), and 35% (95% CI, 26% to 46%) versus 17% (95% CI, 12% to 24%; P = .003), respectively. MA conditioning was associated with better progression-free (PFS) (relative risk, .60; 95% CI, .37 to .97; P = .038) and 3-year survival in transplantations before 2001, but for subsequent years, RIC was associated with better PFS and survival (relative risk, 1.49 [95% CI, .92 to 2.42]; P = .10; and relative risk, 1.86 [95% CI, 1.11 to 3.13]; P = .019). Pretransplantation disease status was the most important predictor of relapse (P = .003) and PFS (P = .0007) for both forms of transplantation conditioning. MA and RIC MSD transplantations are effective for CLL. Future strategies to decrease TRM and reduce relapses are warranted.
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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".