Transitional-Cell Carcinoma Recurrence Rate after Nephroureterectomy in Patients Who Undergo Open Excision of Bladder Cuff <i>v</i> Transurethral Incision of the Ureteral Orifice
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The gold standard treatment for upper-tract transitional-cell carcinoma is radical nephroureterectomy, but management of the distal ureter is not standardized. Two treatment options to detach the distal ureter are open cystotomy (OC) and excision of a bladder cuff or transurethral incision of the ureteral orifice (TUIUO). We compared the clinico-pathologic outcomes of these two techniques. PATIENTS AND METHODS: Hospital records were reviewed on all 51 patients who had undergone open or laparoscopic nephroureterectomy at our institution between 1 January 1990 and 30 June 2005. Patient demographics, intraoperative parameters, and pathology data were collected. The mean follow-up was 23.2 months (range 4.5-75 months) and 22.1 months (range 1-50 months) for the OC and TUIUO groups, respectively. There were no significant differences in sex, age at operation, American Society Anesthesiologists risk score, previous transitional-cell tumors, pathologic tumor grade and stage, or metastatic disease status in the two groups. RESULTS: Five patients had an unplanned incomplete ureterectomy. The bladder recurrence rates were similar in the OC group (22.2%; 6/27) and the TUIUO group (26.3%; 5/19). There were no pelvic recurrences in either group. Four of the five patients who had an incomplete ureterectomy had tumor recurrences, three in the form of metastatic disease. CONCLUSION: Management of the distal ureter by TUIUO in appropriate patients offers the same rate of bladder recurrence as OC. Incomplete ureterectomy results in a significantly higher rate of recurrence, often associated with the development of metastatic disease.
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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 | 0.003 |
| 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".