Benefit of Early Ruxolitinib Initiation Regardless of Fibrosis Grade in Patients with Primary Myelofibrosis: A Post Hoc Analysis of the Single-Arm Phase 3b JUMP Study
Bibliographic record
Abstract
Bone marrow fibrosis (BMF) is an adverse prognostic factor for myelofibrosis (MF). The single-arm, open-label, phase 3b JUMP trial (NCT01493414) assessed the safety and efficacy of the JAK1/JAK2 inhibitor ruxolitinib in patients with symptomatic MF. This post hoc analysis investigated the impact of BMF grade on response and outcomes in patients with primary MF (PMF) from the JUMP study. BMF was assessed by biopsy and graded from 0 to 3; grades 0-1 were considered low-grade fibrosis (LGF) and grades 2-3 were considered high-grade fibrosis (HGF). Patients with LGF (n = 268) had lower rates of cytopenias at baseline but showed comparable disease burden vs. patients with HGF (n = 852). The proportion of patients achieving a spleen response was greater in the LGF group vs. the HGF group at Week 24 and at any time during the study, while overall survival estimates were improved in patients with LGF vs. patients with HGF. Early initiation of ruxolitinib therapy (within 2 years of diagnosis) was associated with increased response rates in all patients. These results highlight the efficacy of ruxolitinib in symptomatic patients with PMF, with the greatest clinical improvements observed in patients with LGF and in patients who received early treatment.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".