Contemporary conditional cancer‐specific survival after radical nephroureterectomy in patients with nonmetastatic urothelial carcinoma of upper urinary tract
Bibliographic record
Abstract
Abstract Background and Objectives To examine the effect of conditional survival on 5‐year cancer‐specific survival (CSS) probability after radical nephroureterectomy (RNU) in a contemporary cohort of patients with non‐metastatic urothelial carcinoma of the upper urinary tract (UTUC). Methods Within the Surveillance, Epidemiology and End Results database (2004‐2015), 6826 patients were identified. Conditional 5‐year CSS estimates were assessed after event‐free follow‐up duration. Multivariable Cox regression (MCR) models predicted cancer‐specific mortality (CSM) according to event‐free follow‐up length. Results Overall, 956 (14.0%) were T 1 low grade(LG)N 0 , 1305 (19.1%) T 1 high grade(HG)N 0 , 1215 (17.8%) T 2 N 0 , 2249 (32.9%) T 3 N 0 and 1101 (16.1%) T 4 N 0 /T any N 1‐3 . From baseline, 93.4% to 94.2% in T 1 LGN 0 provided 5‐year CSS and, respectively, 86.2% to 95.3% in T 1 HGN 0 , 77.5% to 87.8% in T 2 N 0 , 63.0% to 91.1% in T 3 N 0 , and 38.8% to 88.2% in T 4 N 0 /T any N 1‐3 . In MCR models, relative to T 1 LGN 0 , T 1 HGN 0 (Hazard ratio [HR] 1.7), T 2 N 0 (HR 3.0), T 3 N 0 (HR: 5.2), and T 4 N 0 /T any N 1‐3 (HR 11.9) were independent predictors of higher CSM. Conditional HRs decreased to levels equivalent to T 1 LGN 0 at 3 years vs 5 years of event‐free survival for T 1 HGN 0 and all other groups, respectively. Conclusions A direct relationship exists between event‐free follow‐up and survival probability after RNU. From a clinical perspective, such survival estimates may have particular importance during preoperative counseling.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".