Effect of chemotherapy on cancer specific mortality in female locally advanced urethral cancer
Bibliographic record
Abstract
OBJECTIVE: To quantify the effect of chemotherapy (CHT) in locally advanced female primary urethral cancer (fPUC). METHODS: In the Surveillance, Epidemiology and Ends Results (SEER) database (2000-2021), we identified 295 fPUC patients with locally advanced stage treated with local therapy (surgery or radiation or both) with or without CHT. Multivariable Cox regression models addressed cancer specific mortality free survival (CSM). Sample power analyses were computed. RESULTS: Of 295 fPUC patients, 141 (48%) underwent CHT. CHT rates increased from 40 to 61% (Δ22%) over the study span (2000-2021). Five-year CSM rates of CHT exposed vs. CHT-naïve patients were 58 vs. 43% (Δ15%). In multivariable Cox regression models (age and histology adjusted) CHT independently predicted lower CSM (HR = 0.67, p = 0.027). In squamous cell carcinoma (SCC) subgroup, CHT also independently predicted lower CSM (HR = 0.64, p = 0.01). In urothelial carcinoma (HR = 0.63, p = 0.2) and adenocarcinoma (HR = 0.7, p = 0.7) independent predictor status could not be demonstrated. Small sample sizes in urothelial carcinoma subgroup (UC) and adenocarcinoma subgroup (ADK) undermined the power of the analyses to as low as 48% in UC and 46% in ADK, respectively, versus ideal 80% power. CONCLUSION: In fPUC patients, CHT independently predicts lower CSM. This effect is generalizable to SCC patients. The same relationship between CHT status and CSM is also operational in UC and ADK subgroups, but limited power undermined confirmation of its' statistical significance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".