The Use of Cytokeratin 19 (CK19) Immunohistochemistry in Lesions of the Pancreas, Gastrointestinal Tract, and Liver
Bibliographic record
Abstract
Cytokeratin immunostaining forms the bedrock of the immunohistochemical evaluation of tumors. Cytokeratin 19 (CK19) belongs to a family of keratins, which are normally expressed in the lining of the gastroenteropancreatic and hepatobiliary tracts. CK19 immunohistochemistry has been used successfully in thyroid tumors to recognize papillary carcinomas for some time. However, its use in the pancreas, liver, and gastrointestinal tract (GIT) has only recently come to the fore. The purpose of this review is to look at the use of CK19 immunohistochemistry in tumors occurring at these sites. CK19 has been shown to be an independent prognostic factor for pancreatic neuroendocrine tumors, especially the insulin-negative tumors. CK19 positive tumors are associated with poor outcome irrespective of the established pathologic parameters such as size, mitoses, lymphovascular invasion, and necrosis. It is recommended that CK19 be part of the immunohistochemical panel in the work-up of pancreatic endocrine tumors. CK19 is positive in the most of neuroendocrine tumors occurring in the rest of the GIT, except rectal tumors, which are negative. In the liver, CK19 is of prognostic value in hepatocellular carcinomas and is of use in distinguishing cholangiocarcinoma from hepatocellular carcinomas. It can also be used to highlight native ductules in the liver and helps separate conditions such as focal nodular hyperplasia from hepatic adenoma. The vast majority of adenocarcinomas in the GIT and pancreas are CK19 positive.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".