Fedratinib: a pharmacotherapeutic option for JAK-inhibitor naïve and exposed patients with myelofibrosis
Bibliographic record
Abstract
INTRODUCTION: Ruxolitinib is the most commonly used JAK-inhibitor (JAKi) for the management of symptoms related to splenomegaly and cytokine-mediated inflammation in patients with myelofibrosis (MF), but is limited by variable durability of response with most patients experiencing failure after 2-3 years. Long-term data on other approved JAKi, fedratinib and pacritinib, are not available due to the clinical hold put on pivotal trials for toxicity concerns. AREAS COVERED: Following the initial hold for concern of Wernicke's encephalopathy, fedratinib was approved by the Food and Drug Administration (FDA) in 2019 for MF. We review the data available from early, and late phase critical trials, outline a role for fedratinib in the current treatment landscape of MF, and highlight the knowledge gaps in optimizing use of fedratinib. EXPERT OPINION: The JAKARTA and JAKARTA2 trials established efficacy in spleen volume response (SVR) and symptom reduction in JAKi-naïve and ruxolitinib-exposed MF patients, respectively. Further trials, FREEDOM and FREEDOM2, are in progress to understand long-term effects of fedratinib; and include strategies to mitigate gastrointestinal toxicity, monitor thiamine levels and surveil for encephalopathy. We use fedratinib for symptomatic MF following ruxolitinib failure in patients without significant cytopenias; with practical strategies for monitoring and managing potential toxicity.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 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".