Survival and clinicopathological significance of B7-H3 in bladder cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: B7-H3 has been implicated in clinical pathological features and prognosis across various cancer types, suggesting its potential as a cancer biomarker. Nevertheless, consensus remains elusive regarding its clinical-pathological and prognostic significance in bladder cancer. To address this gap, we conducted a systematic review and meta-analysis. METHODS: We systematically searched PubMed, Embase, Web of Science, Cochrane, and CNKI databases from their inception up to October 6, 2022. We evaluated the literature's quality using the Newcastle-Ottawa Scale. We performed meta-analysis using Review Manager 5.3 and STATA 12.0, synthesizing data and calculating odds ratios (ORs) or hazard ratios (HRs) with corresponding 95% confidence intervals (CIs). RESULTS: After applying eligibility criteria and conducting assessments, we included data from 8 studies, encompassing 1622 bladder cancer patients. Bladder tumor tissues exhibited significantly elevated B7-H3 protein expression compared to normal bladder tissues. Elevated B7-H3 expression was notably associated with patient age, tumor infiltration, and recurrence in bladder cancer. However, no significant correlations were observed with other clinical characteristics. Our pooled HR analysis indicated no significant association between B7-H3 expression and overall survival in bladder cancer patients. CONCLUSION: Our meta-analysis unveils the complex role of B7-H3 in bladder cancer progression. It appears to be directly involved in tumor infiltration and recurrence but cannot definitively serve as a prognostic biomarker for bladder cancer. To validate these findings, further well-designed studies, encompassing larger sample sizes and diverse racial backgrounds, are warranted. PROSPERO REGISTRATION: No. CRD42022364688.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.036 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".