Efficacy and safety of a novel dosing strategy for ruxolitinib in the treatment of patients with myelofibrosis and anemia: the REALISE phase 2 study
Bibliographic record
Abstract
Anemia is a frequent manifestation of myelofibrosis (MF) and there is an unmet need for effective treatments in anemic MF patients. The REALISE phase 2 study (NCT02966353) evaluated the efficacy and safety of a novel ruxolitinib dosing strategy with a reduced starting dose with delayed up-titration in anemic MF patients. Fifty-one patients with primary MF (66.7%), post-essential thrombocythemia MF (21.6%), or post-polycythemia vera MF (11.8%) with palpable splenomegaly and hemoglobin <10 g/dl were included. Median age was 67 (45-88) years, 41.2% were female, and 18% were transfusion-dependent. Patients received 10 mg ruxolitinib b.i.d. for the first 12 weeks, then up-titrations of up to 25 mg b.i.d. were permitted, based on efficacy and platelet counts. Overall, 70% of patients achieved a ≥50% reduction in palpable spleen length at any time during the study. The most frequent adverse events leading to dose interruption/adjustment were thrombocytopenia (17.6%) and anemia (11.8%). Patients who had a dose increase had greater spleen size and higher white blood cell counts at baseline. Median hemoglobin levels remained stable and transfusion requirements did not increase compared with baseline. These results reinforce the notion that it is unnecessary to delay or withhold ruxolitinib because of co-existent or treatment-emergent anemia.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".