Can lymphovascular invasion replace the prognostic value of lymph node involvement in patients with upper tract urothelial carcinoma after radical nephroureterectomy?
Bibliographic record
Abstract
INTRODUCTION: This study aimed to evaluate whether lymphovascular invasion (LVI) can replace lymph node (LN) involvement as a prognostic marker in patients who do not undergo lymph node dissection (LND) during surgery in patients with upper tract urothelial carcinoma (UTUC). METHODS: A total of 505 patients who underwent radical nephroureterectomy (RNU) were recruited from four academic centres and divided into four groups: node negative (N0, Group 1); node positive (N+, Group 2); no LND without LVI (NxLVI-, Group 3); and no LND with LVI (NxLVI+, Group 4). RESULTS: Patients in Group 2 had larger tumours, a higher incidence of left-sided involvement, more aggressive T stage and grade, and a higher positive surgical margin rate than patients in other groups. Pathological features (T stage and grade) were poorer in Group 4 than in Groups 1 and 3. Compared to other groups, Group 2 had the worst prognostic outcomes regarding locoregional/distant metastasis-free survival (MFS), cancer-specific survival (CSS), and overall survival (OS). LVI and LN status in Group 4 was not associated with MFS in multivariate analysis. Among Nx diseases, LVI was not an independent predictor of MFS or CCS. The small number of cases in Groups 2 and 4 is a major limitation of this study. CONCLUSIONS: Clinical outcomes according to LVI did not correlate with those outcomes predicted by LN involvement in patients with UTUC. Therefore, LVI may not be used as a substitute for nodal status in patients who do not undergo LND at the time of surgery.
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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 | 0.001 | 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".