DNA methylation as prognostic factors in non-muscle-invasive bladder cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: Early prognostication in non-muscle-invasive bladder cancer (NMIBC) is essential for optimizing therapy and follow-up. Epigenetic mechanisms, particularly DNA methylation, have emerged as promising biomarkers for predicting disease outcome. Materials and Methods: A systematic review and meta-analysis were conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to evaluate the prognostic significance of promoter DNA methylation in NMIBC. Comprehensive searches of PubMed, Web of Science, Embase, MEDLINE, and the Cochrane Library (January 2010-October 2022) identified eligible studies. The Newcastle-Ottawa scale was used for quality assessment, and pooled hazard ratios with 95% confidence intervals were calculated using random-effects models. Results: Eleven studies with 3,065 NMIBC patients were analyzed. Promoter methylation was significantly associated with poor progression-free survival (pooled hazard ratios (HR) = 2.88; 95% CI = 2.03-4.09; p < 0.0001) and recurrence-free survival (pooled HR = 2.65; 95% CI = 1.93-3.63; p < 0.0001). Although overall survival showed pathway-specific variation (pooled HR = 0.96; 95% CI = 0.36-2.60; p = 0.94), methylation of adhesion and apoptosis-related genes exhibited the strongest associations. Subgroup analyses revealed a greater prognostic impact in Asian cohorts (p < 0.0001), suggesting regional differences in epigenetic susceptibility. Conclusion: Promoter DNA methylation constitutes a robust prognostic biomarker for recurrence and progression in NMIBC, with stronger effects in Asian populations. Standardization of validated gene panels, assay thresholds, and cross-regional prospective validation will be essential for clinical translation. Integrating methylation-based classifiers into risk stratification models could improve individualized management and long-term outcomes in NMIBC.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".