Immunohistochemical Analysis of Cyclooxygenase-2 in Non-Melanocytic Skin Cancer: Correlation With Morphological Subtype and Histologic Grade
Bibliographic record
Abstract
BACKGROUND: Basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs) are known as non-melanoma skin cancers (NMSCs), and they account for approximately 90% of all skin cancers. Cyclooxygenase-2 (COX-2) is expressed in NMSC and in premalignant cutaneous lesions (actinic keratosis). METHODS: Immunohistochemistry was performed with COX-2 antibodies in skin biopsies (paraffin tissue archival blocks) from 28 cases with SCC and 33 cases with BCC. RESULTS: COX-2 was immunostained in a total of 61 cases. There was no staining or weakly positive staining in 73.8% of the cases (45 cases), and there was moderate or strong positive staining in 26.3% of the cases (16 cases). COX-2 was expressed in 42.4% of the BCC cases and in 57.1% of the SCC cases. There was a significant relationship between positive COX-2 staining and SCC (P = 0.016). CONCLUSIONS: In this study, SCCs were significantly correlated with the expression of COX-2. In addition, COX-2 was more frequently expressed in SCC than in BCC. The largest diameters of the SCC were significantly correlated with the expression of COX-2. There were no significant associations between COX-2 staining and clinicopathologic features such as the ulceration of the tumor, its anatomic localization, patient gender, the histologic grade of the SCC and the morphological subtype of the BCC.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".