Ribociclib-Induced Hepatitis: A Case Report of Possible Autoimmune Hepatotoxicity
Bibliographic record
Abstract
Background: Hormone receptor-positive breast cancer is the most common subtype, accounting for approximately two-thirds of all breast cancer cases. In the metastatic setting, first-line treatment is comprised of endocrine therapy and a cyclin-dependent kinase 4 and 6 inhibitor. Ribociclib is the most used agent and has the highest risk of hepatotoxicity among the three currently available cyclin-dependent kinase 4 and 6 inhibitors. Case Presentation: We present a case of a 59-year-old postmenopausal female with metastatic hormone receptor-positive breast cancer who started treatment with fulvestrant and ribociclib after progression on anastrozole. After the third cycle, she developed grade 3 transaminitis. Ribociclib was held, and after no improvement in 28 days, she was treated with a 6-day course of prednisone 1 mg/kg, with significant improvement in her liver enzymes. Rechallenge with a lower dose of ribociclib (200 mg) was attempted; however, she again developed grade 3 transaminitis. This again required treatment with a short course of corticosteroids. Following normalization of her liver enzymes, she was rechallenged with abemaciclib with no recurrent hepatotoxicity. Conclusion: Ribociclib hepatotoxicity can be successfully treated with withdrawal of the medication and a short course of corticosteroids if liver enzymes do not improve following a 28-day withdrawal, highlighting a potential immune-mediated mechanism. Additionally, rechallenge with another cyclin-dependent kinase 4 and 6 inhibitor is a safe and effective strategy that should be considered.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".