Incidence and survival outcomes in patients with upper urinary tract urothelial carcinoma diagnosed with variant histology and treated with nephroureterectomy
Bibliographic record
Abstract
OBJECTIVE: To evaluate the incidence and survival outcomes of histological variants of upper tract urothelial carcinoma (UTUC) treated with radical nephroureterectomy (RNU). MATERIALS AND METHODS: We retrospectively analysed data from 1610 patients treated with RNU for clinically non-metastatic UTUC between 1990 and 2016 in several centres participating in the UTUC Collaboration. Histological variants were classified as micropapillary, squamous, sarcomatoid and other, including other rare variants (<10 cases for each). Multivariable competing risk analyses were conducted to assess the effect of variant histology on overall recurrence and cancer-specific mortality (CSM). RESULTS: Overall, 1460 patients (91%) had pure urothelial carcinoma (PUC), whereas 150 (9%) were diagnosed with a variant histology, including 89 (5.0%), 41 (2.0%), 10 (1.0%) and 10 (1.0%) cases of micropapillary, squamous, sarcomatoid and other tumours, respectively. Variant histology was associated with the presence of adverse pathological features compared with PUC, including non-organ-confined disease (59% vs 38%; P < 0.001), lymph node invasion (28% vs 24%; P = 0.02), high-grade disease (88% vs 71%; P < 0.001), tumour necrosis (28% vs 16%; P = 0.001) and positive surgical margins (15% vs 8%; P = 0.01). In competing risk analysis, micropapillary variant was the only factor associated with worse recurrence (sub-hazard ratio [SHR] 2.27, 95% confidence interval [CI] 1.25-4.79; P = 0.02) whereas sarcomatoid variant was associated with worse CSM (SHR 16.8, 95% CI 6.86-41.17; P < 0.001). CONCLUSION: We found that one out of 10 patients with UTUC treated with RNU had variant histology. Only micropapillary and sarcomatoid variants were associated with poorer oncological outcomes after adjusting for available confounding factors.
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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 | 0.000 | 0.001 |
| 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".