Radical cystectomy for bladder urothelial carcinoma with aggressive variant histology
Bibliographic record
Abstract
PURPOSE: The aim of this study is to report our experience in managing bladder cancer in patients with variant pathology. METHODS: Retrospective data collection for all patients managed by radical cystectomy over the last 3 years for a variant pathol-ogy was completed. We specifically included micropapillary and nested variants. RESULTS: Ten patients were identified, with eight having micropapillary carcinoma (MPC) and two having nested vari-ants. Nine patients were male. The median age was 75. The two patients with nested variant were 56 and 62 years old, respec-tively, whereas all patients with MPC were over the age of 70. Upon cystectomy of all micropapillary cases, three patients (37.5%) had positive lymph node invasion and the final patholo-gy was T2 (two patients), T3 (two patients), and T4 (four patients). Barring a grade III complication Clavien-Dindo classi-fication due to wound dehiscence that necessitated secondary surgical closure, there were no specific perioperative complica-tions. Given the urethral invasion, cystourethrectomy was per-formed on the female patient. Within a median 13-month fol-low-up, three patients developed local recurrence, including two urethral and one new lateral pelvic mass. CONCLUSIONS: Considering the muscle invasive nature of micropapillary and nested bladder cancer, aggressive surgical management should not be postponed. Moreover, due to notable prevalence of concurrent and/or recurrent urethral involvement, initial urethrectomy or early and frequent postoperative ure-throscopy should be provided. Patients with variant histology bladder cancer may benefit from early radical cystectomy when compared to bladder sparing protocols and prostate sparing cystectomy treatment options.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".