p53 status correlates with the risk of progression in stage T1 bladder cancer: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Published studies have yielded inconsistent results on the relationship between p53 status and the progression of stage T1 non-muscle invasive bladder cancer (NMIBC). Therefore, we performed a meta-analysis to evaluate the prognostic value of p53 in T1 NMIBC. METHODS: We systematically searched for relevant literatures in MEDLINE, EMBASE, and Web of Science. Data were pooled together from individual studies, and meta-analysis was performed. Study quality was assessed using the Newcastle-Ottawa Scale. Pooled risk ratios (RRs) and 95% CI were calculated to estimate the effect sizes. Moreover, subgroup analyses were carried out. RESULTS: A total of 12 studies comprising 712 patients were subjected to the final analysis. p53 overexpression was significantly associated with higher progression rate of T1 NMIBC (RR 2.32, 95% CI 1.59-3.38). Moderate heterogeneity was observed across the studies (I(2) = 39%, P < 0.0001). In a subgroup analysis stratified by stage, p53 overexpression was a predictor of progression in T1 grade 3 NMIBC (RR 2.71, 95% CI 1.31-5.64). In addition, in a subgroup analysis stratified by intravesical therapy, p53 overexpression was a predictor of progression in T1 NMIBC received Bacillus Calmette-Guérin intravesical therapy (RR 3.35, 95% CI 1.89-5.93). Furthermore, after excluding the study that possibly contributed to the heterogeneity by the sensitivity analysis, the association p53 overexpression was significantly correlated with progression of T1 NMIBC (RR 2.74, 95% CI 2.05-3.65) without evidence of heterogeneity (I(2) = 0 %, P < 0.0001). CONCLUSIONS: This meta-analysis suggested that p53 overexpression may be associated with progression of T1 NMIBC patients. Because of the heterogeneity and other limitations, further studies with rigid criteria and large populations are still warranted to confirm our findings.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.068 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".