Lower urinary tract transitional cell carcinoma in cats: Clinical findings, treatments, and outcomes in 118 cases
Bibliographic record
Abstract
BACKGROUND: Lower urinary tract transitional cell carcinoma (TCC) is an important but rarely described disease of cats. OBJECTIVES: To report the clinical characteristics, treatments, and outcomes in a cohort of cats with lower urinary tract TCC and to test identified variables for prognostic relevance. ANIMALS: One-hundred eighteen client-owned cats with lower urinary tract carcinoma. METHODS: Medical records were retrospectively reviewed to obtain information regarding clinical characteristics, treatments, and outcomes. Recorded variables were analyzed statistically. RESULTS: Median age of affected cats was 15 years (range, 5.0-20.8 years) and median duration of clinical signs was 30 days (range, 0-730 days). The trigone was the most common tumor location (32/118; 27.1%) as assessed by ultrasound examination, cystoscopy, or both. Treatment was carried out in 73 of 118 (61.9%) cats. Metastatic disease was documented in 25 of 118 (21.2%) cats. Median progression-free survival and survival time for all cats were 113 days (95% confidence interval [CI], 69-153) and 155 days (95% CI, 110-222), respectively. Survival increased significantly (P < .001) when comparing cats across the ordered treatment groups: no treatment, treatment without partial cystectomy, and treatment with partial cystectomy. Partial cystectomy (hazard ratio [HR], 0.31; 95% CI, 0.17-0.87) and treatment with nonsteroidal anti-inflammatory drugs (HR, 0.55; 95% CI, 0.33-0.93) were significantly associated with longer survival times. CONCLUSIONS AND CLINICAL IMPORTANCE: The results support treatment using partial cystectomy and NSAIDs in cats with TCC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".