Efficacy and Safety of Momelotinib in Myelofibrosis: A Systematic Review and Meta-Analysis With a Focus on Anemia Outcomes
Bibliographic record
Abstract
Background: ) mutations. Nearly 50% of PMF patients experience anemia (hemoglobin (Hb) < 10 g/dL), often worsened by JAK inhibitors like ruxolitinib and fedratinib. Momelotinib, an oral ACVR1, JAK1, and JAK2 inhibitor, improves anemia, symptoms, and splenomegaly, likely through hepcidin regulation. This review evaluates its efficacy and safety, with a focus on anemia. Methods: A systematic review and meta-analysis were conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, including randomized controlled trials (RCTs) and clinical studies assessing momelotinib's efficacy and safety. Primary outcomes included spleen volume reduction (≥ 35%) and anemia response (transfusion independence). Secondary endpoints included symptom burden reduction and safety. Results: Six studies, including three RCTs, met inclusion criteria. Meta-analysis showed momelotinib was noninferior to ruxolitinib in spleen volume reduction but superior in anemia benefits, increasing transfusion independence (odds ratio (OR): 2.09; 95% confidence interval (CI): 1.53 - 2.85) and reducing transfusion dependence (OR: 0.62; 95% CI: 0.45 - 0.84). Symptom burden reduction was comparable to other JAK inhibitors. Common adverse events included dizziness (OR: 1.70; 95% CI: 1.05 - 2.74) and nausea (OR: 3.07; 95% CI: 1.82 - 5.18), with no significant increase in serious adverse events. Conclusions: Momelotinib improved anemia-related outcomes and quality of life in MF without increased adverse events. However, heterogeneity in control groups limited direct efficacy comparisons. Larger studies are needed to confirm its effectiveness and safety.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.038 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".