Adjuvant chemotherapy for high-risk upper tract urothelial carcinoma: Results from the Upper Tract Urothelial Carcinoma Collaboration
Bibliographic record
Abstract
5075 Background: There is relatively little literature regarding the use of adjuvant chemotherapy following radical nephroureterectomy in the management of patients with upper tract urothelial carcinoma (UTUC). Our goal was to determine the incidence of receipt of adjuvant chemotherapy in high-risk patients and the ensuing effect on overall- and cancer-specific survival. Methods: Using an international collaborative database, we identified 1390 patients who underwent nephroureterectomy for non-metastatic UTUC between the years of 1992 and 2006. Of these, 542 (39%) patients were classified as high-risk (pT3N0, pT4N0, and/or lymph node positive). These patients were separated into two groups—those who did and did not receive adjuvant chemotherapy—and were stratified by gender, age group, performance status, tumor grade and stage. Cox proportional hazard modeling and Kaplan-Meier analyses were used to determine overall- and cancer-specific survival amongst the cohorts. Results: Of the high-risk patients, 121 (22%) received adjuvant chemotherapy. Adjuvant chemotherapy was more commonly administered in the context of increased tumor grade and stage (p < 0.001). Median survival in the entire cohort was 24 months (range 0–231 months). There was no significant difference in overall- or cancer-specific survival between those who did and did not receive adjuvant chemotherapy; however age, performance status, tumor grade, and tumor stage were significant predictors of both overall and cancer-specific survival. Conclusions: Adjuvant chemotherapy is infrequently utilized in the treatment of patients with high-risk UTUC after nephroureterectomy. Despite this, it appears that adjuvant chemotherapy confers minimal impact on overall- or cancer-specific survival in this group. No significant financial relationships to disclose.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".