The relationship between promoter methylation of p16 gene and bladder cancer risk: a meta-analysis.
Bibliographic record
Abstract
PURPOSE: Many scientific evidences suggested that the methylation of p16INK4a (p16) was associated with bladder cancer, but some existing studies have yielded inconclusive results about the relationship between p16 promoter methylation and pathological features or the tumor grade of bladder cancer. This meta-analysis of studies aims to evaluate the clinical and prognostic significance of p16 methylation in bladder carcinogenesis. METHODS: Studies were systemically searched via PubMed and Google Scholar in English up to Sept 2015 and a total of ten appropriate studies (693 cases and 290 controls) with an average NOS score of 6.8 were included. The quality of the appropriate studies was measured by the Newcastle-Ottawa Scale (NOS) assessment. RESULTS: The meta-analysis results revealed that the methylation state of p16 was statistically significantly associated with an increased risk of bladder cancer (OR=6.71, 95% CI=3.79-11.87) compared to control, and there is no statistically significantly association between the p16 methylation and the tumor pTNM staging (OR=0.59, 95% CI=0.22-1.60) or the tumor grade (OR=1.01, 95% CI=0.52-1.94) in p16 methylated patients compared to unmethylated patients. CONCLUSIONS: our meta-analysis indicates that p16 promoter methylation may be a promising biomarker for the diagnosis of bladder cancer and the inactivation of p16 may be an early event in bladder carcinogenesis. More studies with larger numbers of participants worldwide are needed to further identify the obvious association above.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.048 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".