The Impact of Previous Ureteroscopic Tumor Ablation on Oncologic Outcomes After Radical Nephrouretectomy for Upper Urinary Tract Urothelial Carcinoma
Bibliographic record
Abstract
Abstract We investigated whether a history of endoscopic tumor ablation impacts oncologic outcomes after radical nephroureterectomy (RNU) for upper urinary tract urothelial carcinoma (UTUC). Using a multi-institutional database that contained patients who were treated with RNU, oncologic outcomes were assessed according to history of ureteroscopic tumor ablation. Disease-free survival (DFS) and cancer-specific survival (CSS) were estimated using the Kaplan-Meier survival analysis. Multivariate Cox regression analyses were performed to determine independent predictors of disease recurrence and cancer-specific mortality after RNU. The study included 1268 patients, 853 men and 415 women, with a mean age of 67.5 years (range 32-94 y) and 52.8 months median follow-up after RNU. A total of 175 (13%) patients underwent RNU after endoscopic tumor ablation and 1093 (87%) patients underwent RNU without a history of endoscopic ablation. The 5-year DFS and CSS rates were 72% and 77% in those with a history of tumor ablation vs 69% and 73% in those without a history of ablation (P = 0.171 and P = 0.365, respectively). In multivariate Cox regression analysis, history of ablation therapy was not associated with disease recurrence or cancer-specific mortality (hazard ratio [HR]: 0.79, P = 0.185 and HR: 0.7, P = 0.078, respectively). Our collaborative international efforts suggest that in selected patients, endoscopic tumor ablation does not adversely affect the recurrence and survival after subsequent RNU for UTUC. Our data support the continued role of ureteroscopic ablation of UTUC in appropriately selected 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".