The Prognostic Significance of Metastatic Perivesical Lymph Nodes Identified in Radical Cystectomy Specimens for Transitional Cell Carcinoma of the Bladder
Bibliographic record
Abstract
PURPOSE: We determined the prognostic significance of metastatic perivesical lymph nodes (PVLN) in transitional cell carcinoma of the bladder (TCC). MATERIALS AND METHODS: A retrospective review of 198 consecutive patients who underwent radical cystectomy for clinically organ confined TCC identified 32 patients with PVLN in pathology specimens. Patient characteristics were compared. Overall survival, disease-specific survival (DSS) and disease-free survival were estimated using Kaplan-Meier actuarial methodology. The log-rank test was used to compare the differences between patients with and without metastatic TCC to PVLN. Cox multivariate regression analysis was used to determine whether the effect of metastatic PVLN on survival was independent of pathological stage. RESULTS: Metastatic TCC was found in the PVLN of 14 patients. Median followup and age were 13.5 months and 66.5 years, respectively. Patients with and without metastatic PVLN had similar characteristics and pathological disease staging. The overall survival, DSS and disease-free survival were significantly less for patients with metastatic TCC in PVLN (p = 0.002, p = 0.013 and p <0.001, respectively), and involvement of PVLN and pelvic nodes (p = 0.001, p = 0.010 and p = 0.041, respectively). Metastatic PVLN was an independent predictor of OS and DSS (p = 0.016 and p = 0.025, respectively). CONCLUSIONS: Metastases to PVLN appear to confer a significantly worse prognosis for patients undergoing radical cystectomy. Patients with identifiable metastatic PVLN may benefit from early adjuvant therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".