Comparing the safety and efficacy of ruxolitinib in patients with Dynamic International Prognostic Scoring System low‐, intermediate‐1‐, intermediate‐2‐, and high‐risk myelofibrosis in JUMP, a Phase 3b, expanded‐access study
Bibliographic record
Abstract
Ruxolitinib, a potent Janus kinase 1/2 inhibitor, has demonstrated durable improvements in patients with myelofibrosis. In this analysis of the Phase 3b JUMP study, which included patients aged ≥18 years with a diagnosis of primary or secondary myelofibrosis, we assessed the safety and efficacy of ruxolitinib in patients stratified by Dynamic International Prognostic Scoring System (DIPSS) risk categories. Baseline characteristic data were available to assess DIPSS status for 1844 of the 2233 enrolled patients; 60, 835, 755, and 194 in the low-, intermediate (Int)-1-, Int-2-, and high-risk groups, respectively. Ruxolitinib was generally well tolerated across all risk groups, with an adverse-event (AE) profile consistent with previous reports. The most common hematologic AEs were thrombocytopenia and anemia, with highest rates of Grade ≥3 events in high-risk patients. Approximately, 73% of patients experienced ≥50% reductions in palpable spleen length at any point in the ≤24-month treatment period, with highest rates in lower-risk categories (low, 82.1%; Int-1, 79.3%; Int-2, 67.1%; high risk, 61.6%). Median time to spleen length reduction was 5.1 weeks and was shortest in lower-risk patients. Across measures, 40%-57% of patients showed clinically meaningful symptom improvements, which were observed from 4 weeks after treatment initiation and maintained throughout the study. Overall survival (OS) was 92% at Week 72 and 75% at Week 240 (4.6 years). Median OS was longer for Int-2-risk than high-risk patients (253.6 vs. 147.3 weeks), but not evaluable in low-/Int-1-risk patients. By Week 240, progression-free survival (PFS) and leukemia-free survival (LFS) rates were higher in lower-risk patients (PFS: low, 90%; Int-1, 82%; Int-2, 46%; high risk, 15%; LFS: low, 92%; Int-1, 86%; Int-2, 58%; high risk, 19%). Clinical benefit was seen across risk groups, with more rapid improvements in lower risk patients. Overall, this analysis indicates that ruxolitinib benefits lower-risk DIPSS patients in addition to higher risk.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".