Aetiology and Evaluation of Men with Urethral Stricture and the Current Role of Urethroplasty in the Treatment of Anterior Urethral Strictures
Bibliographic record
Abstract
Introduction: The use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) has been associated with improved bladder cancer outcomes. The objective of this study was to perform a systematic review of the literature and investigate the effects of these medications on survival from our own retrospective database. Methods: A systematic literature search of PubMed and the Cochrane database was conducted and 34 relevant articles identified. No randomised control trials were identified. After exclusion, five observational studies were included in our analysis. Since there was a paucity of data, we then performed a retrospective cohort study using clinical data from our electronic medical record. All patients who underwent radical cystectomy, with or without adjuvant chemotherapy, at a single tertiary care centre in Ontario, Canada between 2001 and 2016 were identified. Results: Our literature review found that ACEI or ARB use in upper urinary tract and lower urinary tract non-muscle invasive bladder cancer was associated with increased 5-year recurrence-free, cancer-specific, and overall survival. Our own analysis identified 464 patients who underwent radical cystectomy for muscle-invasive bladder cancer during the study period. Ninety-nine individuals received ACEI or ARB treatment during this time. Cox-proportion hazards modelling suggested that the use of ACEI or ARB was not significantly associated with a survival benefit. Conclusions: We are unable to support or oppose the use of ACEI or ARB as adjuvant treatment in bladder cancer due to the heterogeneity and quality of published data. Our own study data do not support the use of these medications as adjuvant therapy for muscle-invasive bladder cancer. A randomised control trial in this area of research is required.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".