Alternative donor transplantation for myelodysplastic syndromes: haploidentical relative and matched unrelated donors
Bibliographic record
Abstract
We compared outcomes in 603 patients with myelodysplastic syndrome (MDS) after HLA-haploidentical relative (n = 176) and HLA-matched unrelated (n = 427) donor hematopoietic cell transplantation (HCT) from 2012 to 2017, using the Center for International Blood and Marrow Transplant Research database. All transplantations used reduced-intensity conditioning regimens. Total-body irradiation plus cyclophosphamide and fludarabine was the predominant regimen for HLA-haploidentical relative donor HCT, and graft-versus-host disease (GVHD) prophylaxis was uniformly posttransplantation cyclophosphamide, calcineurin inhibitor, and mycophenolate. Fludarabine with busulfan or melphalan was the predominant regimen for HLA-matched unrelated donor HCT, and GVHD prophylaxis was calcineurin inhibitor with mycophenolate or methotrexate. Results of multivariate analysis revealed higher relapse (hazard ratio [HR], 1.56; P = .0055; 2-year relapse rate, 48% vs 33%) and lower disease-free survival (DFS) rates after HLA-haploidentical relative donor HCT (HR, 1.29; P = .042; 2-year DFS, 29% vs 36%). However, overall survival (OS) rates did not differ between donor type (HR, 0.94; P = .65; 2-year OS, 46% for HLA-haploidentical and 44% for HLA-matched unrelated donor HCT) because of mortality associated with chronic GVHD. Acute grade 2 to 4 GVHD (HR, 0.44; P < .0001) and chronic GVHD (HR, 0.36; P < .0001) were lower after HLA-haploidentical relative donor HCT. By 2 years, probability of death resulting from chronic GVHD was lower after HLA-haploidentical relative compared with HLA-matched unrelated donor HCT (6% vs 21%), negating any potential survival advantage from better relapse control. Both donor types extend access to transplantation for patients with MDS; strategies for better relapse control are desirable for HLA-haploidentical relative donor HCT, and effective GVHD prophylaxis regimens are needed for unrelated donor HCT.
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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".