Consistency of Spleen and Symptom Reduction Regardless of Cytopenia in Patients With Myelofibrosis Treated With Pacritinib
Bibliographic record
Abstract
BACKGROUND: Pacritinib is a JAK2/IRAK1/ACVR1 inhibitor that is approved in the United States for the treatment of patients with myelofibrosis who have a platelet count < 50 × 109/L. Phase 3 clinical studies of pacritinib included patients across a wide range of baseline platelet and hemoglobin levels. PATIENTS AND METHODS: In order to assess the impact of baseline blood counts on pacritinib efficacy, an analysis of efficacy outcomes by baseline platelet and hemoglobin levels was performed using data pooled from 2 Phase 3 studies of pacritinib in patients with MF (PERSIST-1 and PERSIST-2). RESULTS: Of 276 patients evaluable for spleen response, spleen volume reduction occurred consistently across platelet subgroups (< 100 × 109/L or ≥ 100 × 109/L) and hemoglobin subgroups (< 8 g/dL, ≥ 8 to < 10 g/dL, or > 10 g/dL), with no diminution in treatment effect in patients with severe thrombocytopenia or anemia. Among 159 patients evaluable for symptoms response, improvement in total symptom score (TTS) was similar across platelet subgroups. A ≥ 50% improvement of TSS occurred more frequently in patients with baseline hemoglobin < 8 g/dL compared with those with baseline hemoglobin ≥ 8 to < 10 g/dL or > 10 g/dL. Patients with baseline hemoglobin < 8 g/dL also experienced improved hemoglobin sustained over 24 weeks, whereas subgroups with less severe anemia had stable hemoglobin levels over time. Symptom improvement as assessed using the Patient Global Impression of Change instrument was generally consistent across platelet and hemoglobin subgroups. CONCLUSION: Pacritinib demonstrates consistent efficacy in patients with MF regardless of baseline platelet and hemoglobin counts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".