Long‐term outcomes and cost savings of office fulguration of papillary Ta low‐grade bladder cancer
Bibliographic record
Abstract
OBJECTIVES: To assess whether office-based fulguration (OF) under local anaesthesia for small, recurrent, pathological Ta low-grade (LG) non-muscle-invasive bladder cancer (NMIBC) is an effective alternative to transurethral resection of bladder tumour (TURBT), avoiding the costs and risks of procedure, and anesthesia. PATIENTS AND METHODS: Of 521 patients with primary TaLG NMIBC, this retrospective study included 270 patients who underwent OF during follow-up for recurrent, small, papillary LG-appearing tumours at a university centre (University Health Network, University of Toronto, Canada). We assessed the cumulative incidence of cancer-specific mortality (CSM) and disease progression (to MIBC or metastases), as well as possible direct cost savings. RESULTS: In the 270 patients with recurrent TaLG NMIBC treated with OF, the mean (sd) age was 64.9 (13.3) years, 70.8% were men, and 60.3% had single tumours. The mean (sd, range) number of OF procedures per patient was 3.1 (3.2, 1-22). The median (interquartile range) follow-up was 10.1 (5.8-16.2) years. Patients also underwent a mean (sd) of 3.6 (3.0) TURBTs during follow-up in case of numerous or bulkier recurrence. In all, 44.4% of patients never received intravesical therapy. The 10-year incidence of CSM and progression were 0% and 3.1% (95% confidence interval 0.8-5.4%), respectively. Direct cost savings in Ontario were estimated at $6994.14 (Canadian dollars) per patient over the study follow-up. CONCLUSIONS: This study supports that properly selected patients with recurrent, apparent TaLG NMIBC can be safely managed with OF under local anaesthesia with occasional TURBT for larger or numerous recurrent tumours, without compromising long-term oncological outcomes. This approach could generate substantial cost-saving to healthcare systems, is patient-friendly, and could be adopted more widely.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".