A systematic review to establish the frequency of cyclooxygenase-2 expression in normal breast epithelium, ductal carcinoma in situ, microinvasive carcinoma of the breast and invasive breast cancer
Bibliographic record
Abstract
BACKGROUND: Epidemiological studies have suggested a protective effect of cyclooxygenase (COX)-inhibiting non-steroidal anti-inflammatory drugs in breast cancer risk and disease progression. We performed a systematic review to evaluate the frequency of COX-2 expression in normal breast epithelium, ductal carcinoma in situ of breast (DCIS), DCIS-adjoining invasive breast cancer, microinvasive carcinoma of the breast (MICB) and invasive breast cancer. METHODS: Literature searches were carried out on MEDLINE, EMBASE and Web of Science from their commencement until September 2010. Primary studies examining COX-2 expression by immunohistochemistry methodology were included. Meta-analyses were carried out using random effects models for individual study estimates of COX-2 expression and pooled to give an overall estimate. RESULTS: The pooled prevalences (95% confidence intervals) of COX-2 expressions were 53% (44-61) in DCIS studies and 42% (36-49) in the invasive breast cancer studies. There were too few studies involving normal breast epithelium, DCIS-adjoining invasive breast cancer and MICB to conduct meta-analyses. CONCLUSION: The findings from our meta-analyses have shown similar COX-2 expression in DCIS and invasive breast cancer. This may suggest the involvement of COX-2 in early carcinogenesis. Further studies of COX-2 expression in DCIS are required to investigate the use of COX-2 as a potential drug target for prevention of disease progression in DCIS.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.013 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".