Liver Biochemical Flare with Immune Checkpoint Therapy in Metastatic Merkel Cell Carcinoma: A Liver Biopsy is Always Necessary
Bibliographic record
Abstract
Merkel cell carcinoma (MCC) is a rare, aggressive neuroendocrine carcinoma of the skin. Treatment for locoregional MCC includes local excision with regional lymphadenectomy, followed by adjuvant radiotherapy. Immune checkpoint inhibitors (ICI) have emerged as a breakthrough treatment of metastatic MCC. Nevertheless, T-cell immune response is triggered against self-antigens resulting in immune-mediated toxicities, including ICI-mediated hepatotoxicity. We report a case of recurrent metastatic MCC treated with avelumab, a PD-L1 inhibitor, with subsequent significant liver biochemical flare. The initial clinical diagnosis was ICI-mediated hepatotoxicity. Workup to rule out competing causes of liver injury came back negative. Hence, avelumab was discontinued, and the patient was initiated on steroid therapy with stepwise escalation. Owing to clinical and laboratory deterioration, it was then decided to perform a percutaneous liver biopsy to document steroid-refractory ICI-mediated hepatotoxicity and/or rule out other causes of potential liver injury. The liver biopsy showed MCC tumor cells almost entirely infiltrating the hepatic parenchyma, confirmed by immunohistochemistry. At that point, steroid therapy was discontinued, and the patient was transitioned into palliative care. In conclusion, patients with apparent ICI-related hepatotoxicity should always be considered for a liver biopsy to exclude massive infiltrative malignancy as the true cause of liver dysfunction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".