Pembrolizumab-Induced Hepatitis and Pancreatitis in a Patient With Stage IV Non-Small Cell Lung Cancer
Bibliographic record
Abstract
Immune checkpoint inhibitors are a novel approach to treat cancers. Firstly used for treatment of malignant melanomas with promising results, they were later expanded to treat other cancers including non-small cell lung cancers (NSCLC) expressing PD-L1. We present a case of a 66-year-old male who was admitted to the hospital for generalized gastrointestinal complaints consisting of abdominal pain, nausea, vomiting, and loose stools occurring five times daily. Labs were significant for acute transaminitis with hyperbilirubinemia and elevated lipase. All workup for infectious and noninfectious causes was negative. The patient was started pembrolizumab 15 days before admission and his previous labs had all been normal before the initiation of treatment. He was treated with high dose of steroids with initial improvement and discharged on oral steroids taper. He subsequently presented again with worsening liver function tests (LFTs) results and was restarted on a higher dose but unable to tolerate it due to steroid-induced psychosis and left the hospital against medical advice. Presented the third time with persistent elevation of LFTs and worsening hyperbilirubinemia, this time he was started on different class of steroid with atypical antipsychotic but left again a few days later seeking care at a tertiary care institute. This case highlights one of the severe side effects of the immune checkpoint inhibitors which is acute hepatitis that can sometimes lead to acute liver failure. Prompt treatment with steroids is indicated for these patients; and those who are refractory or intolerant to steroids can be treated with a multimodal approach using topical steroids, N-acetylcysteine (NAC), ursodeoxycholic acid and immune suppressant drugs. J Med Cases. 2018;9(9):320-322 doi: https://doi.org/10.14740/jmc3131w
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".