Efficacy and safety of ruxolitinib in patients with myelofibrosis and low platelet count (50 × 10 <sup>9</sup> /L to <100 × 10 <sup>9</sup> /L) at baseline: the final analysis of EXPAND
Bibliographic record
Abstract
Background: Thrombocytopenia is a common feature of myelofibrosis (MF), a myeloproliferative neoplasm driven by dysregulated JAK/STAT signaling; however, pivotal trials assessing the efficacy of ruxolitinib (a JAK1/2 inhibitor) excluded MF patients with low platelet counts (<100 × 10 9 /L). Objectives: Determination of the maximum safe starting dose (MSSD) of ruxolitinib was the primary endpoint, with long-term safety and efficacy as secondary and exploratory endpoints, respectively. Design: EXPAND (NCT01317875) was a phase 1b, open-label, ruxolitinib dose-finding study in patients with MF and low platelet counts (50 to <100 × 10 9 /L). Methods: Patients were stratified according to baseline platelet count into stratum 1 (S1, 75 to <100 × 10 9 /L) or stratum 2 (S2, 50 to <75 × 10 9 /L). Previous analyses established the MSSD at 10 mg twice daily (bid); long-term results are reported here. Results: Of 69 enrolled patients, 38 received ruxolitinib at the MSSD (S1, n = 20; S2, n = 18) and are the focus of this analysis. The incidence of adverse events was consistent with the known safety profile of ruxolitinib, with thrombocytopenia (S1, 50%; S2, 78%) and anemia (S1, 55%; S2, 44%) the most frequently reported adverse events and no new or unexpected safety signals. Substantial clinical benefits were observed for patients in both strata: 50% (10/20) and 67% (12/18) of patients in S1 and S2, respectively, achieved a spleen response (defined as ⩾50% reduction in spleen length from baseline) at any time during the study. Conclusion: The final safety and efficacy results from EXPAND support the use of a 10 mg bid starting dose of ruxolitinib in patients with MF and platelet counts 50 to <100 × 10 9 /L. Registration: ClinicalTrials.gov NCT01317875.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".