Case Series of Cancer Patients Treated With Galunisertib, a Transforming Growth Factor-Beta Receptor I Kinase Inhibitor in a First-in-Human Dose Study
Bibliographic record
Abstract
Galunisertib (LY2157299 monohydrate) is a first-in-class small molecule inhibitor (SMI) of the transforming growth factor-beta (TGF-beta) signaling pathway. Some adverse events were associated with galunisertib during the first-in-human dose (FHD) study. Among these adverse events (n = 11) were four cases of infection, two cases of thromboembolic events and two cases of thrombocytopenia. In one of the patients with thromboembolic events, an autopsy was also performed to examine possible changes of the aorta. No significant histopathologic changes were observed. Single cases of grade 2 diarrhea (only associated with drug intake), stroke (after resection for relapsed glioma), and pre-existing co-primary tumor (possible colorectal cancer) were observed. Because TGF-beta plays an important role in tissue homeostasis and in immune response regulation, the present case series may serve as a future reference for adverse events observed in subsequent clinical trials with galunisertib. J Med Cases. 2014;5(11):603-609 doi: http://dx.doi.org/10.14740/jmc1966w
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".