Management of upper urinary tract urothelial carcinoma
Bibliographic record
Abstract
Upper urinary tract urothelial carcinoma (UTUC) is relatively uncommon. In this article, we review prognostic factors, criteria and indications for treatment with the available modalities using contemporary data. A systematic search on PubMed was performed using the keywords 'upper tract urothelial carcinoma', 'upper tract transitional cell carcinoma', 'nephroureterectomy', 'laparoscopic', 'endoscopic' and 'prognostic factor'. The literature on UTUC is scarce. No prognostic factors have been formally validated in either the diagnosis or treatment of UTUC. The gold-standard management for invasive UTUC is radical nephroureterectomy with a bladder-cuff excision. Laparoscopic and endoscopic approaches represent alternatives in properly selected individuals. Segmental ureterectomy may also be considered. The extent and role of lymph node dissection remains to be validated. Chemotherapy may also be considered in select patients. Additional multi-institutional studies are needed to identify and validate prognostic factors that can predict the outcomes of patients diagnosed with UTUC. Randomized controlled trials are needed to assess the efficacy of the treatment modalities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".