Simultaneous radical cystectomy and nephroureterectomy in the treatment of panurothelial carcinoma: a systematic review and single-arm meta-analysis
Bibliographic record
Abstract
Background Panurothelial carcinoma is a rare and aggressive malignancy that requires effective treatment strategies to enhance patient outcomes. Methods We conducted a systematic search of English publications in databases including PubMed, Embase, Cochrane Library, and Web of Science up to May 2023. The quality of the literature was assessed using the Newcastle-Ottawa Scale (NOS) and the Methodological Quality and Synthesis of Case Series and Case Reports tool. Data statistics and analysis were performed using Stata 15.1 software (StataSE, USA). Results Six studies involving 339 patients were included in the analysis. Meta-analysis revealed that Simultaneous Radical Cystectomy and Nephroureterectomy had 2-year and 5-year overall survival rates of 68% (95% CI 60%-76%, I2 = 12.4%, P < 0.001) and 44% (95% CI 36%-53%, I2 = 0, P < 0.001), respectively. The 2-year and 5-year progression-free survival rates were 91% (95% CI 86%-95%, I2 = 95%, P < 0.001) and 65% (95% CI 58%-73%, I2 = 91.5%, P < 0.001), respectively. The 2-year and 5-year cancer-specific survival rates were 73% (95% CI 66%-81%, I2 = 16.7%, P < 0.001) and 57% (95% CI 49%-66%, I2 = 0, P < 0.001), respectively. Additionally, the incidence of minor complications was 19% (95% CI 15%-23%, P < 0.01), major complications was 49% (95% CI 34%-63%, P < 0.01), and the intraoperative blood transfusion rate was 53% (95% CI 44%-61%, P < 0.01). Conclusions Simultaneous radical cystectomy and nephroureterectomy represent feasible approaches for the treatment of Panurothelial carcinoma. Nonetheless, a comprehensive assessment of the surgical risks and benefits is imperative, and larger-scale prospective cohort studies are required to validate therapeutic efficacy. Systematic review registration https://www.crd.york.ac.uk/PROSPERO , identifier CRD42023426401.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.038 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".