Efficacy of Metastasectomy for Metastatic Bladder Cancer: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Objectives It has been proposed that metastasectomy may cure some patients with a single metastasis. Hence, we considered it necessary to clarify the role of metastasectomy for metastatic bladder cancer (BCa). Methods We conducted a systematic review of published reports on the efficacy of metastasectomy for different sites of BCa metastasis. We searched English articles published before 7 June 2025 in three electronic databases: PubMed, Embase, and Cochrane Library. We then extracted authors, year of publication, country in which the study was conducted, study institution, study design, survival analysis, months of follow‐up, size of study cohort, treatment, hazard ratios (HR) with 95% confidence interval (CI), and source of HR. The Newcastle–Ottawa Scale was used to analyze the risk and quality of included studies. All procedures were performed according to the PRISMA guidelines. A meta‐analysis was performed on studies with sufficient survival data to analyze. Overall survival was analyzed to clarify the efficacy of metastasectomy for metastatic BCa. Results Our meta‐analysis identified 8 of 7877 articles published from 1992 to 2024 that met our criteria. These articles encompassed 15 139 patients in all, which showed that patients who underwent metastasectomy had better overall survivals (OS) than did those who only had non‐surgical treatment (HR = 0.46, 95% CI 0.27–0.79, I 2 = 64.3%). Additionally, we found a positive association between OS and metastasectomy in patients with brain metastases (HR = 0.49, 95% CI 0.34–0.70, I 2 = 49.7%). Conclusions We found a positive association between metastasectomy and OS in patients with metastatic BCa, especially those with brain metastases. Metastasectomy should be considered an adequate approach in BCa, when feasible. Trial Registration PROSPERO number: CRD42021234305
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".