Prognostic significance of substage and WHO classification systems in T1 urothelial carcinoma of the bladder
Bibliographic record
Abstract
PURPOSE OF REVIEW: Treatment of T1 urothelial bladder cancer (T1-BC) is challenging as risk assessment criteria for progression are lacking. Histological grade and T1 substage have been identified as important prognostic factors. Currently, no consensus exists regarding the optimal sub-staging and grading systems for T1-BC. We reviewed recent advances in the various grading and sub-staging systems and their clinical applicability. RECENT FINDINGS: Stratification by muscularis mucosae invasion is the most explored sub-staging system. Its prognostic value was established by 12/23 (52%) available studies. Importantly, muscularis mucosae identification varied substantially among pathologists. Sub-staging based on diameter of invasive carcinoma [T1 microinvasive and T1 extensive-invasive (T1m/e)] proved a more reproducible system with at least equal prognostic value. However, more study is needed to investigate interobserver variation. For nonmuscle-invasive bladder cancer grading, the 1973 and 2004 WHO classifications both provide independent prognostic information. However, remarkably few studies have investigated their applicability in T1-BC only. The available reports suggest that the 1973 WHO classification is superior to WHO 2004. SUMMARY: If multicenter studies confirm the promising results of T1m/e sub-staging, it may be incorporated in the Internation Union Against Cancer TNM classification system for urinary bladder cancer. More studies are warranted to define the optimal classification system for grade in T1-BC.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".