Exposure–response relationship of fedratinib in patients with intermediate‐2 or high‐risk myelofibrosis
Bibliographic record
Abstract
Abstract Aims Fedratinib is a potent, oral, Janus kinase inhibitor for the treatment of myelofibrosis (MF). This report describes exposure–response (E–R) analyses of fedratinib based on pooled data from phase 2/3 studies in patients with intermediate‐2 or high‐risk MF, with or without prior ruxolitinib exposure. Methods Pharmacokinetic (PK) exposures were derived from the population PK analysis. Efficacy endpoints included spleen volume reduction ≥35% (SVR35) and total symptom score reduction ≥50% (TSS response). Safety endpoints included grade ≥3 anaemia or thrombocytopenia, any‐grade nausea/vomiting and diarrhoea. The E–R models were developed using logistic regression analyses. Results Fedratinib exposure was positively associated with SVR35 (odds ratio [OR], 38.2; 95% confidence interval [CI], 12.4–118; P < 0.001) and TSS response (OR, 20.8; 95% CI, 6.27–69.2; P < 0.001), after adjusting for covariates. Baseline spleen volume was inversely associated with SVR35 (P = 0.029). Prior ruxolitinib exposure was not associated with SVR35 (P = 0.090) or TSS response (P = 0.326). Although numerically higher incidence of adverse events was observed in patients with higher fedratinib exposure, there was no statistically significant association between fedratinib exposure and any safety related endpoints. Prior ruxolitinib exposure was associated with experiencing grade ≥3 thrombocytopenia (P = 0.004). Lower baseline haemoglobin level (<10 g/dL) and platelet count (<100 × 109/L) were associated with experiencing grade ≥3 anaemia (P < 0.001) and thrombocytopenia (P < 0.001), respectively. Antiemetic prophylaxis was associated with lower rates of nausea/vomiting (P < 0.001). Conclusions Fedratinib exposure was positively associated with spleen volume reduction and TSS responses, without having significant impact on safety. Fedratinib 400 mg once daily is an appropriate dose for patients with MF regardless of ruxolitinib exposure.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".