Comparison of outcomes of HCT in blast phase of <i>BCR-ABL1</i>− MPN with de novo AML and with AML following MDS
Bibliographic record
Abstract
Comparative outcomes of allogeneic hematopoietic cell transplantation (HCT) for BCR-ABL1- myeloproliferative neoplasms (MPNs) in blast phase (MPN-BP) vs de novo acute myeloid leukemia (AML), and AML with prior myelodysplastic syndromes (MDSs; post-MDS AML), are unknown. Using the Center for International Blood and Marrow Transplant Research (CIBMTR) database, we compared HCT outcomes in 177 MPN-BP patients with 4749 patients with de novo AML, and 1104 patients with post-MDS AML, using multivariate regression analysis in 2 separate comparisons. In a multivariate Cox model, no difference in overall survival (OS) or relapse was observed in patients with MPN-BP vs de novo AML with active leukemia at HCT. Patients with MPN-BP in remission had inferior OS in comparison with de novo AML in remission (hazard ratio [HR], 1.40 [95% confidence interval [CI], 1.12-1.76]) due to higher relapse rate (HR, 2.18 [95% CI, 1.69-2.80]). MPN-BP patients had inferior OS (HR, 1.19 [95% CI, 1.00-1.43]) and increased relapse (HR, 1.60 [95% CI, 1.31-1.96]) compared with post-MDS AML. Poor-risk cytogenetics were associated with increased relapse in both comparisons. Peripheral blood grafts were associated with decreased relapse in MPN-BP and post-MDS AML (HR, 0.70 [95% CI, 0.57-0.86]). Nonrelapse mortality (NRM) was similar between MPN-BP vs de novo AML, and MPN-BP vs post-MDS AML. Total-body irradiation-based myeloablative conditioning was associated with higher NRM in both comparisons. Survival of MPN-BP after HCT is inferior to de novo AML in remission and post-MDS AML due to increased relapse. Relapse-prevention strategies are required to optimize HCT outcomes in MPN-BP.
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 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 | 0.000 |
| 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".