Reduced-Intensity Hematopoietic Cell Transplantation for Patients with Primary Myelofibrosis: A Cohort Analysis from the Center for International Blood and Marrow Transplant Research
Bibliographic record
Abstract
We evaluated outcomes and associated prognostic factors in 233 patients undergoing allogeneic hematopoietic cell transplantation (HCT) for primary myelofibrosis (MF) using reduced-intensity conditioning (RIC). The median age at RIC HCT was 55 yr. Donors were a matched sibling donor (MSD) in 34% of RIC HCTs, an HLA well-matched unrelated donor (URD) in 45%, and a partially matched/mismatched URD in 21%. Risk stratification according to the Dynamic International Prognostic Scoring System (DIPSS) was 12% low, 49% intermediate-1, 37% intermediate-2, and 1% high. The probability of survival at 5 yr was 47% (95% confidence interval [CI], 40% to 53%). In a multivariate analysis, donor type was the sole independent factor associated with survival. Adjusted probabilities of survival at 5-yr were 56% (95% CI, 44% to 67%) for MSD, 48% (95% CI, 37% to 58%) for well-matched URD, and 34% (95% CI, 21% to 47%) for partially matched/mismatched URD (P = .002). The relative risk (RR) for NRM was 3.92 (P = .006) for well-matched URD and 9.37 (P < .0001) for partially matched/mismatched URD. Trends toward increased NRM (RR, 1.7; P = .07) and inferior survival (RR, 1.37; P = .10) were observed in DIPSS intermediate-2/high-risk patients compared with DIPSS low/intermediate-1 risk patients. Our data indicate that RIC HCT is a potentially curative option for patients with MF, and that donor type is the most important factor influencing survival in these patients.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".