Can biological markers predict recurrence and progression of superficial bladder cancer?
Bibliographic record
Abstract
Biological markers that are predictive of recurrence and progression of superficial bladder tumors must provide additional information to that provided by multiplicity, size and grade. Field anomalies in normal appearing urothelium of patients with papillary superficial transitional cell carcinoma have been associated with tumor antigens and chromosome 9 deletions. Also, primary tumors with chromosome 9 deletions are associated with a higher risk of recurrence. Abnormal expression of p53, p21 and Ki-67 cell cycle markers have little predictive value for recurrence. However, p53 overexpression or mutation and decreased expression of p27 are associated with cancer progression and survival. New markers, such as mutations in the fibroblast growth factor receptor 3 gene (found in 30% of tumors), anomalies of the PTEN gene and vascular endothelial growth factor expression, may have potential and require further evaluation. Molecular fingerprints of superficial tumors with distinct clinical behavior are being rapidly unravelled. Large-scale clinical studies are urgently needed to provide supportive evidence for their incorporation in clinical management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".