Radiotherapy with radical cystectomy for bladder cancer: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Muscle-invasive bladder cancer (MIBC) is associated with high recurrence and mortality rates. The role of radiotherapy as an adjunct to radical cystectomy is not well-defined. We sought to evaluate the efficacy and safety of radiotherapy preoperatively or postoperatively for patients with MIBC receiving cystectomy compared to cystectomy alone. The primary outcome was overall survival. The secondary outcome was adverse effects. METHODS: MEDLINE, EMBASE, and CENTRAL were searched on August 30, 2016 for randomized controlled trials (RCTs) of patients undergoing cystectomy for bladder cancer. A control group receiving cystectomy alone and an intervention group with radiotherapy and cystectomy were required. The Jadad score was used to assess for bias. Fifteen studies representing 10 RCTs met eligibility criteria. RESULTS: A total of 996 patients were randomized in seven trials included in a meta-analysis of neoadjuvant radiotherapy. Insufficient data were available to complete a pooled analysis for adjuvant radiotherapy. There was a non-statistically significant improvement in overall survival for patients who received neo-adjuvant radiotherapy and cystectomy. At three years and five years, the odds ratios were 1.23 (95% confidence interval [CI] 0.72-2.09) and 1.26 (95% CI 0.76-2.09), respectively, in favour of neoadjuvant radiotherapy. Subgroup analyses including higher doses of radiotherapy showed greater effect on survival. CONCLUSIONS: These data suggest that radiotherapy prior to cystectomy may improve overall survival. This review was limited by old studies, heterogeneous patient populations, and radiotherapy treatment techniques that may not meet current standards. There is a need for current RCTs to further evaluate this effect.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".