p53 expression in patients with advanced urothelial cancer of the urinary bladder
Bibliographic record
Abstract
OBJECTIVE: To test whether assessing p53 expression could improve the ability to predict disease recurrence and disease-specific survival in a multi-institutional cohort of patients with advanced urothelial carcinoma of the urinary bladder (UCB). PATIENTS AND METHODS: The study comprised 692 patients with pT3-4 N0 or pTany N+ UCB treated with radical cystectomy and lymphadenectomy. The predictive accuracy (PA) was quantified using the 200 bootstrap-corrected concordance index. The base model comprised age, gender, stage, grade, lymphovascular invasion, number of lymph nodes removed, number of lymph nodes positive, concomitant carcinoma in situ, and adjuvant chemotherapy. RESULTS: p53 expression was altered in 341 (49.3%) patients. In multivariable analyses, p53 expression was independently associated with disease recurrence (hazard ratio, 1.66; P < 0.001) and cancer-specific mortality (hazard ratio 1.65, P < 0.001). Overall, adding p53 did not significantly improve the PA of the base model (recurrence +0.7%, P = 0.085, and cancer-specific mortality +1.2%, P = 0.050). In the subgroups of pT3N0 (280) and pT4N0 (83) patients, p53 slightly improved the PA of the base model by a statistically significant degree (recurrence +1.7% and +3.6%, respectively; cancer-specific mortality +1.9% and +3.5%, respectively; all P < 0.001). In 329 patients with pTany N+ disease p53 status did not improve the PA of the base model. CONCLUSION: While assessing p53 expression has limited utility in patients with lymph node-positive UCB, it marginally improves prognostication in patients with advanced non-metastatic UCB. Integration of p53 into a panel of biomarkers might be necessary to capture a more accurate picture of the biological potential of advanced UCB.
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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) | 0.000 | 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".