Immunohistochemical Expression and Prognostic Value of ER, PR and HER2/neu in Pancreatic and Small Intestinal Neuroendocrine Tumors
Bibliographic record
Abstract
BACKGROUND AND AIMS: There has been limited study of estrogen and progesterone receptor (ER/PR) expression in gastrointestinal neuroendocrine tumors (GINETs) despite emerging evidence of hormone receptor regulation of pancreatic islet cells. Beta cells express PR and progesterone has been implicated in the pathogenesis of gestational diabetes. There is conflicting information regarding HER2/neu protein overexpression in GINETs. Investigation of ER, PR and HER2/neu expression in GINETs is therefore warranted. METHODS: A pathology database search identified 77 patients with primary pancreatic (40) or small intestinal (37) NETs diagnosed from 1991 to 2009. Ki67, ER, PR and HER2/neu were assessed via immunohistochemistry. ER and PR were interpreted as negative (0), 1+ (Allred score 3-7/8) or 2+ (Allred score 8/8), and HER2/neu was assessed according to ASCO/CAP guidelines for breast carcinoma. Clinical correlation and survival outcomes were ascertained by a retrospective clinical chart review. RESULTS: 2+ PR staining was observed more often in pancreatic compared to small intestinal cases (55 vs. 8%; p < 0.001). All small intestinal NETs with 2+ PR were duodenal primaries. Cases with 2+ PR presented significantly less often with nodal or distant metastases compared to cases with 0/1+ PR (13 vs. 61.5%; p < 0.001) and had significantly improved disease-free survival (median 155 vs. 38 months; p = 0.037). Only one case demonstrated 2+ ER staining and all were negative for HER2/neu. CONCLUSION: GINETs with strong (2+) PR expression are associated with pancreatic/duodenal origin, lower stage disease, and more favorable clinical prognosis. Further study is needed to determine the clinical utility of PR expression in GINETs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".