Higher Cancer Mortality in Rural Upper Urinary Tract Urothelial Carcinoma Patients
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to investigate differences in the stage at presentation and cancer-specific mortality (CSM) between rural area (RA) and urban area (UA) residence status in nonmetastatic upper urinary tract urothelial carcinoma (UTUC) patients. METHODS: Newly diagnosed T1-3N0M0 UTUC patients with available residence status were abstracted from the Surveillance, Epidemiology, and End Results database (2004-2016). Propensity score (PS) matching (1 RA vs. 3 UA) accounted for age (interval ≤2 years), T stage (exact matching: T1, T2, and T3), and tumor grade (exact matching: high grade, low grade/unknown). Cumulative incidence plots and multivariable competing risk regression models focused on CSM, after adjustment for other-cause mortality. RESULTS: Of 6,012 patients, 125 (2.1%) resided in RAs and 5,887 (97.9%) in UAs. RA patients were younger than UA patients (median age 72 vs. 75 years, p = 0.03). No differences were recorded in tumor location, T stage, tumor grade, or surgical treatment between RA and UA patients. After 1:3 PS matching, 125 RA patients and 375 UA patients were assessable. At 5 years of follow-up, CSM rates were 26.7 versus 15.7% according to RA versus UA, respectively. After additional multivariable adjustment for age, sex, tumor location, and surgical treatment, RA remained an independent predictor of higher CSM (hazard ratio 1.75, p = 0.02). CONCLUSIONS: Despite no differences in cancer characteristics, UTUC patients in RA are at higher risk of CSM than their UA counterparts. This suggests suboptimal care delivery and compliance as possible causes. Complex and/or rare disease should be centralized to expert centers, which are often in UAs.
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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 | 0.001 |
| 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) | 0.002 | 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".