Focal Hepatocellular Carcinoma in Pancreas
Bibliographic record
Abstract
A 67-year-old man was found to have a pancreatic head mass on abdominal ultrasound. He had compensated liver cirrhosis due to hepatitis C. The fine-needle aspiration (FNA) biopsy of the mass reported an adenocarcinoma of the pancreas, while the subsequent histopathology report of the supraclavicular lymph node showed features of hepatocellular carcinoma (HCC). A second read and additional stains on the FNA specimen confirmed a hepatoid (hepatocellular) carcinoma of the pancreas. He received atezolizumab and bevacizumab and had a good response. Tumors with features of HCC outside of the liver rarely occur and even more rarely in pancreas, with less than 50 cases reported so far. Pure HCC-like morphology is the most common histological form among four subtypes and has a relatively better prognosis. Surgical resection is considered the treatment of choice if amenable and variable outcomes are reported with different chemotherapies. Challenges exist in the diagnosis and the management of this rare and intriguing entity, and the potential misdiagnosis can have grave consequences as the management is completely different for a pancreatic adenocarcinoma and hepatoid carcinoma. We report a case with a challenging diagnosis of metastatic pancreatic hepatoid carcinoma which was treated as unresectable HCC with immunotherapy and the patient had a good response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".