Acute Hepatitis in a Patient Treated With Ribociclib for Metastatic Breast Carcinoma
Bibliographic record
Abstract
Ribociclib, a cyclin-dependent kinase 4/6 (CDK4/6) inhibitor, is widely used in the treatment of hormone receptor-positive (HR+), human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer. Although hepatotoxicity is a recognized adverse effect, severe cases of ribociclib-induced liver injury with histologic confirmation of submassive hepatic necrosis remain rare. We describe a case of a postmenopausal woman with newly diagnosed stage IV HR+/HER2-negative invasive lobular carcinoma who developed acute hepatocellular injury 8 weeks after initiating ribociclib and anastrozole. The patient presented with fatigue, jaundice, and dark urine, and was found to have markedly elevated transaminases (alanine aminotransferase 1,825 U/L; aspartate aminotransferase 1,536 U/L) and hyperbilirubinemia. A thorough workup excluded viral, autoimmune, and obstructive hepatobiliary causes. Liver biopsy demonstrated confluent centrilobular necrosis without fibrosis or significant inflammation. Causality assessments yielded an R-factor of 20.73, a Roussel Uclaf Causality Assessment Method score of 10 (highly probable), and a Naranjo score of 7 (probable). Ribociclib was discontinued and intravenous N-acetylcysteine (NAC) initiated, leading to gradual normalization of liver enzymes. The patient was maintained on anastrozole alone, with no recurrence of liver injury and stable disease at 13-month follow-up. This case highlights the potential for ribociclib to induce severe hepatocellular injury with histologic evidence of submassive necrosis. Early recognition and structured causality assessment ensures patient safety. In patients with significant hepatotoxicity, discontinuation of ribociclib and non-rechallenge may be prudent. Furthermore, consideration of NAC in management is important in cases demonstrating persistent transaminitis despite ribociclib discontinuation.
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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".