Hepatobiliary Adverse Events Associated With the <scp>KRAS p.G12C</scp> Inhibitor Sotorasib
Bibliographic record
Abstract
PURPOSE: The p.G12C mutation in KRAS is commonly found in many cancers and was previously untreatable until drugs like sotorasib were developed. However, up to 15% of patients treated with sotorasib have experienced hepatobiliary adverse events. To investigate whether these side effects are more common among sotorasib users, a pharmacovigilance study is necessary. METHODS: This study used the FDA adverse event reporting system (FAERS) database, a publicly available repository of reported drug adverse events, and AERSMine, an open-access pharmacovigilance tool, to investigate these adverse events. RESULTS: A total of 428 hepatobiliary adverse events were linked to sotorasib. Hepatic cytolysis had the highest reported relative risk at 26.541 and a safety signal of 4.726. Elevated liver and biliary enzymes such as AST, ALT, ALP, and GGT were commonly observed, but with lower reported relative risk and safety signal values, which supports previous real-world reports. CONCLUSIONS: These findings highlight the hepatobiliary risks associated with sotorasib and underscore the importance of closely monitoring liver function in patients who are using the medication. This is particularly crucial for patients with hepatobiliary cancers, as disease progression and adverse events could be misinterpreted.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".