International Society of Urological Pathology (ISUP) Consensus Conference on Current Issues in Bladder Cancer. Working Group 1
Bibliographic record
Abstract
Grade is a key prognostic factor in determining progression in nonmuscle invasive papillary urothelial carcinomas. The 2 most common grading methods in use worldwide are the World Health Organization (WHO) 2004 and 1973 schemes. The International Society of Urological Pathology (ISUP) organized the 2022 consensus conference in Basel, Switzerland on current issues in bladder cancer and tasked working group 1 to make recommendations for future iterations of bladder cancer grading. For this purpose, the ISUP developed in collaboration with the European Association of Urology a 10-question survey for their memberships to understand the current use of grading schemes by pathologists and urologists and to ascertain the areas of potential improvements. An additional survey was circulated to the ISUP membership for their opinion on interobserver variability in grading, reporting of urine cytology, and challenges encountered in grade assignment. Comprehensive literature reviews were performed on bladder cancer grading prognosis and interobserver variability along with The Paris System for urine cytology. There are notable differences in practice patterns between North American and European pathologists in terms of used grading scheme and diagnosis of papillary urothelial neoplasm of low malignant potential. Areas of common ground include difficulty in grade assignment, a desire to improve grading criteria, and a move towards subclassifying high-grade urothelial carcinomas. The surveys and in-person voting demonstrated a strong preference to refine current grading into a 3-tier scheme with the division of WHO 2004 high grade into clinically relevant categories. More variable opinions were voiced regarding the use of papillary urothelial carcinoma with low malignant potential.
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.
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 | 0.054 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.016 | 0.012 |
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".