The Genitourinary Pathology Society Update on Classification and Grading of Flat and Papillary Urothelial Neoplasia With New Reporting Recommendations and Approach to Lesions With Mixed and Early Patterns of Neoplasia
Bibliographic record
Abstract
The Genitourinary Pathology Society (GUPS) undertook a critical review of the recent advances in bladder neoplasia with a focus on issues relevant to the practicing surgical pathologist for the understanding and effective reporting of bladder cancer, emphasizing particularly on the newly accumulated evidence post-2016 World Health Organization (WHO) classification. The work is presented in 2 manuscripts. Here, in the first, we revisit the nomenclature and classification system used for grading flat and papillary urothelial lesions centering on clinical relevance, and on dilemmas related to application in routine reporting. As patients of noninvasive bladder cancer frequently undergo cystoscopy and biopsy in their typically prolonged clinical course and for surveillance of disease, we discuss morphologies presented in these scenarios which may not have readily applicable diagnostic terms in the WHO classification. The topic of inverted patterns in urothelial neoplasia, particularly when prominent or exclusive, and beyond inverted papilloma has not been addressed formally in the WHO classification. Herein we provide a through review and suggest guidelines for when and how to report such lesions. In promulgating these GUPS recommendations, we aim to provide clarity on the clinical application of these not so uncommon diagnostically challenging situations encountered in routine practice, while also importantly advocating consistent terminology which would inform future work.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".