Prognostic importance of lymphovascular invasion in urothelial carcinoma of the renal pelvis
Bibliographic record
Abstract
BACKGROUND: The current study was conducted to assess the impact of lymphovascular invasion on the survival of patients with urothelial carcinoma of the renal pelvis. METHODS: Patients with urothelial carcinoma of the renal pelvis who underwent radical nephroureterectomy from 2010 through 2015 were identified in the National Cancer Data Base. Patients were characterized according to demographic and clinical factors, including pathologic tumor stage and lymphovascular invasion. Associations with overall survival were assessed through proportional hazards regression analysis. RESULTS: A total of 4177 patients were identified; 1576 had lymphovascular invasion. Patients with T3 disease and lymphovascular invasion had 5-year survival that was significantly worse than that of patients with T3 disease without lymphovascular invasion (34.7% vs 52.6; P < .001 by the log-rank test), and approached that of patients with T4 disease without lymphovascular invasion (34.7% vs 26.5%; P = .002). On multivariate analysis controlling for age, comorbidities, grade, lymph node status, surgical margin status, race, sex, and chemotherapy administration, patients with T3 disease and lymphovascular invasion also were found to have significantly worse survival compared with patients with T3 disease without lymphovascular invasion (hazard ratio, 1.7; 95% confidence interval, 1.4-1.91). CONCLUSIONS: Lymphovascular invasion status is a key prognostic marker that can stratify the risk of patients with pT3 upper tract urothelial carcinoma further. Patients with this pathologic feature should be carefully considered for clinical trials exploring existing and novel therapies. Cancer 2018;124:2507-14. © 2018 American Cancer Society.
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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 | 0.002 |
| 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".