Open vs. robot-assisted radical cystectomy with extracorporeal or intracorporeal urinary diversion for bladder cancer: A pairwise meta-analysis of outcomes and a network meta-analysis of complications by urinary diversion approach
Bibliographic record
Abstract
INTRODUCTION: There are no meta-analyses of randomized controlled trials (RCTs) comparing open radical cystectomy (OR C) with robot-assisted radical cystectomy (RARC), inclusive of both intracorporeal (iRARC) and extracorporeal (hybrid RARC, hRARC) urinary reconstruction. METHODS: MEDL INE, Embase, Scopus, the International Clinical Trials Registry Platform and ClinicalTrials.gov registries were searched in May 2022. Outcomes of interest included recurrence- or progression-free survival (RFS/PFS), margin status and lymph node yield, mean estimated blood loss (EBL) and operating room time (ORT ), hospital length of stay (LOS ), 90-day complications and readmissions, and quality of life (QoL). Pairwise meta-analyses and network meta-analyses were performed using random-effects models and Bayesian hierarchical random-effects models, respectively. RESULTS: We found no significant differences between RARC and OR C for oncological and most perioperative outcomes: RFS/PFS (hazard ratio [HR ] 0.91, 95% confidence interval [CI] 0.67-1.23); positive surgical margins (odds ratio [OR ] 1.05, 95% CI 0.60-1.85); lymph node yield (mean difference [MD ] -0.63, 95% CI -2.63-1.37); LOS (MD -0.22, 95% CI -1.10-0.65); overall complications (OR 0.81, 95% CI 0.61-1.07); major complications (OR 0.94, 95% CI 0.69-1.30); readmissions (OR 0.90, 95% CI 0.60-1.35); and QoL (standardized MD -0.02, 95% CI -0.17-0.14). We found significantly lower EBL for RARC compared to OR C (MD -312.61, 95% CI -447 to -178.22) at the expense of significantly prolonged ORT (MD 82.34 minutes, 95% CI 44.82-119.86). Network meta-analysis did not find significant differences in complications between hRARC and iRARC. CONCLUSIONS: This meta-analysis confirms the equivalence of RARC and OR C with respect to oncological outcomes.
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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 | 0.018 | 0.029 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.074 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".