Radical cystectomy for clinical T4b urothelial carcinoma: An Ontario, single-center experience
Bibliographic record
Abstract
INTRODUCTION: Guidelines surrounding the management of T4b muscle-invasive bladder cancer (MIBC) with radical cystectomy (RC) are limited and lack clarity. Our objective was to analyze our single-center experience to provide additional insight into the role of RC. METHODS: We performed a retrospective data analysis using clinical, radiological, and pathological information for all patients managed by RC for cT4b MIBC at the Thunder Bay Regional Health Sciences Centre (July 2015 to July 2020). Patients that had MIBC as their first diagnosis were termed the de novo group and patients that were initially diagnosed as having non-MIBC were termed the progressive group. RESULTS: Nineteen consecutive patients (16 males and three females), with a median age of 68 years, managed by two urologists over the last five years, met study criteria. Eleven (58%) of the patients had de novo MIBC while eight (42%) presented with progressive disease. All patients had dysuria as a presenting symptom. Only one (5%) patient received neoadjuvant chemotherapy. There were low rates of perioperative transfusion (11%), bowel resections (5%), postoperative transfusions (0%), ileus (32%), urine leak (16%), and wound dehiscence (5%). Fourteen patients (74%) had positive lymph nodes. All patients had adjuvant chemotherapy. The one-year recurrence rate in these patients was 53%, with 32% of recurrence being distant metastasis. The one-year survival rate was 95%. CONCLUSIONS: Patients in the de novo and progressive arms of our cohort had similar rates of surgical complications and disease recurrence. We found operative morbidity and disease control to be reasonable, suggesting RC can be considered more often in the management of T4b MIBC patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".