Cyclooxygenase-2 (COX-2) up-regulation is a prognostic marker for poor clinical outcome of upper tract urothelial cancer.
Bibliographic record
Abstract
BACKGROUND: There are no reliable biomarkers for diagnosis, prediction of outcome or treatment effect monitoring for upper tract urothelial carcinoma (UTUC), which is a uniquely prevalent cancer in Taiwan. In the present study, 128 primary UTUC specimens of various grades and primary tumor status were examined for the expression of cyclooxygenase-2 (COX-2) in tumor and stroma tissues aiming to clarify the association of COX-2 expression with clinical outcomes in Taiwanese patients with UTUC. MATERIALS AND METHODS: Immunohistochemistry was implemented to investigate COX-2 expression levels in 128 paired tumor and stroma specimens. The association of COX-2 expression with tumor progression and prognosis was analyzed. RESULTS: Our data demonstrated that positive COX-2 expression was more frequent in stromal cells (57.0%), than in tumor sites (53.1%), and the up-regulation of COX-2 was strongly associated with higher cancer-specific death and cancer recurrence rates. In COX-2-negative cases, no similar correlation was found. CONCLUSION: COX-2 expression was up-regulated in both stromal and tumor cells of more than half of the studied UTUC patients and the positive expression of COX-2 in stromal cells may be a potential predictive and prognostic biomarker for UTUC, especially for cancer-specific death and recurrence.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".