Updated pathology reporting standards for bladder cancer: biopsies, transurethral resections and radical cystectomies
Bibliographic record
Abstract
AIM: Optimal management of bladder cancer requires an accurate, standardised and timely pathological diagnosis, and close communication between surgeons and pathologists. Here, we provide an update on pathology reporting standards of transurethral resections of the bladder and cystectomies. METHODS: We reviewed recent literature, focusing on developments between 2013 and 2021. RESULTS: Published reporting standards developed by pathology organizations have improved diagnosis and treatment. Tumor sub-staging and subtyping has gained increased attention. Lymph nodes continue to be an area of debate, and their staging has seen minor modifications. Several tasks, particularly regarding specimen preparation ("grossing"), are not yet standardized and offer opportunity for improvement. Molecular classification is rapidly evolving, but currently has only limited impact on management. CONCLUSION: Pathological reporting of bladder cancer is continuously evolving and remains challenging in some areas. This review provides an overview of recent major developments, with a particular focus on published reporting standards.
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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 | 0.023 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".