TURALIO <sup>®</sup> Risk Evaluation and Mitigation Strategy Program (tREMS): 3-year retrospective hepatic safety assessment
Bibliographic record
Abstract
Aim: Hepatic safety data assessment from the TURALIO® (pexidartinib) Risk Evaluation and Mitigation Strategy (tREMS) Program. Methods: Retrospective 3-year assessment (August 2019 to June 2022) of hepatic events from the TURALIO® (pexidartinib) Risk Evaluation and Mitigation Strategy Program. Results: A total of 451 patients, 369 prescribers, 2 wholesalers/distributors and 2 pharmacies were enrolled and certified. Twenty-one (4.7%) patients met the criteria for a hepatic adverse event or laboratory abnormality suggestive of serious and potentially fatal liver injury, all with onset within 2 months of therapy. No new hepatic safety signals were identified. Conclusion: Results are consistent with the phase 3 ENLIVEN trial data. Liver enzyme monitoring, combined with early intervention, including dose modification and discontinuation, conducted in patients treated with pexidartinib mitigate the risk of potential hepatotoxicity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".