Association between the choice of the conditioning regimen and outcomes of allogeneic hematopoietic cell transplantation for myelofibrosis
Bibliographic record
Abstract
Allogeneic hematopoietic cell transplantation (allo-HCT) remains the only curative treatment for myelofibrosis. However, the optimal conditioning regimen either with reduced-intensity conditioning (RIC) or myeloablative conditioning (MAC) is not well known. Using the Center for International Blood and Marrow Transplant Research database, we identified adults aged ≥18 years with myelofibrosis undergoing allo-HCT between 2008-2019 and analyzed the outcomes separately in the RIC and MAC cohorts based on the conditioning regimens used. Among 872 eligible patients, 493 underwent allo-HCT using RIC (fludarabine/ busulfan n=166, fludarabine/melphalan n=327) and 379 using MAC (fludarabine/busulfan n=247, busulfan/cyclophosphamide n=132). In multivariable analysis with RIC, fludarabine/melphalan was associated with inferior overall survival (hazard ratio [HR]=1.80; 95% confidenec interval [CI]: 1.15-2.81; P=0.009), higher early non-relapse mortality (HR=1.81; 95% CI: 1.12-2.91; P=0.01) and higher acute graft-versus-host disease (GvHD) (grade 2-4 HR=1.45; 95% CI: 1.03-2.03; P=0.03; grade 3-4 HR=2.21; 95%CI: 1.28-3.83; P=0.004) compared to fludarabine/busulfan. In the MAC setting, busulfan/cyclophosphamide was associated with a higher acute GvHD (grade 2-4 HR=2.33; 95% CI: 1.67-3.25; P<0.001; grade 3-4 HR=2.31; 95% CI: 1.52-3.52; P<0.001) and inferior GvHD-free relapse-free survival (GRFS) (HR=1.94; 95% CI: 1.49-2.53; P<0.001) as compared to fludarabine/busulfan. Hence, our study suggests that fludarabine/busulfan is associated with better outcomes in RIC (better overall survival, lower early non-relapse mortality, lower acute GvHD) and MAC (lower acute GvHD and better GRFS) in myelofibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".