HER2/neu and Ki-67 as Prognostic Indicators in Mucoepidermoid Carcinoma of Salivary Glands
Bibliographic record
Abstract
INTRODUCTION: Mucoepidermoid carcinoma is the most common salivary gland malignancy, representing up to 30% of all cases. Despite attempts to correlate histopathologic grades to clinical outcomes, some histologically "low"-grade lesions continue to behave aggressively despite appropriate treatment. OBJECTIVE: This preliminary study will attempt to evaluate the use of immunohistochemical markers HER2/neu and Ki-67 as prognostic markers of biologic aggressiveness for mucoepidermoid carcinoma of the salivary glands. DESIGN AND METHODS: A retrospective chart review of 42 patients with mucoepidermoid carcinoma of major and minor salivary glands treated between 1970 and 1995 was conducted. A combination of primary resection with or without postoperative irradiation was used. Histologic grading and correlation with outcome analyses are provided. RESULTS: In the current study, positive HER2/neu staining and strong Ki-67 staining occurred in patients with high-grade mucoepidermoid carcinoma, whereas low-grade carcinoma was correlated with negative or weak staining. CONCLUSION: These preliminary results indicate that, overall, the overexpression of both the HER2/neu and the Ki-67 oncoproteins may serve as prognostic markers for poor outcome in salivary gland mucoepidermoid carcinoma.
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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 | 0.003 |
| 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".