Prognostic significance of substage and WHO classification systems in T1 urothelial carcinoma of the bladder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it