Repeat Transurethral Resection for Non–muscle-invasive Bladder Cancer: An Updated Systematic Review and Meta-analysis in the Contemporary Era
Bibliographic record
Abstract
CONTEXT: Repeat transurethral resection (reTUR) is a guideline-recommended treatment strategy in high-risk non-muscle-invasive bladder cancer (NMIBC) patients treated with transurethral resection of bladder tumor (TURBT); however, the impact of recent procedural/technological developments on reTUR outcomes has not been assessed yet. OBJECTIVE: To assess the outcomes of reTUR for NMIBC in the contemporary era, focusing on whether temporal differences and technical advancement, specifically, photodynamic diagnosis and en bloc resection of bladder tumor (ERBT), affect the outcomes. EVIDENCE ACQUISITION: Multiple databases were queried in February 2023 for studies investigating reTUR outcomes, such as residual tumor and/or upstaging rates, its predictive factors, and oncologic outcomes, including recurrence-free (RFS), progression-free (PFS), cancer-specific (CSS), and overall (OS) survival. We synthesized comparative outcomes adjusting for the effect of possible confounders. EVIDENCE SYNTHESIS: Overall, 81 studies were eligible for the meta-analysis. In T1 patients initially treated with conventional TURBT (cTURBT) in the 2010s, the pooled rates of any residual tumors and upstaging on reTUR were 31.4% (95% confidence interval [CI]: 26.0-37.2%) and 2.8% (95% CI: 2.0-3.8%), respectively. Despite a potential publication bias, these rates were significantly lower than those in patients treated in the 1990-2000s (both p < 0.001). ERBT and visual enhancement-guided cTURBT significantly improved any residual tumor rates on reTUR compared with cTURBT based on both matched-cohort and multivariable analyses. Among studies adjusting for the effect of possible confounders, patients who underwent reTUR had better RFS (hazard ratio [HR]: 0.78, 95% CI: 0.62-0.97) and OS (HR: 0.86, 95% CI: 0.81-0.93) than those who did not, while it did not lead to superior PFS (HR: 0.74, 95% CI: 0.47-1.15) and CSS (HR: 0.94, 95% CI: 0.86-1.03). CONCLUSIONS: reTUR is currently recommended for high-risk NMIBC based on the persistent high rates of residual tumors after primary resection. Improvement of resection quality based on checklist applications and recent technical/procedural advancements hold the promise to omit reTUR. PATIENT SUMMARY: Recent endoscopic/procedural developments improve the outcomes of repeat resection for high-risk non-muscle-invasive bladder cancer. Further investigations are urgently needed to clarify the potential impact of the use of these techniques on the need for repeat transurethral resection in the contemporary era.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".