Interobserver reproducibility of a hybrid three‐tier grading system of papillary nonmuscle invasive urothelial carcinoma: an international Uropathology study
Bibliographic record
Abstract
AIMS: A hybrid-three tier system with low grade (LG), high grade- G2 (HG-G2), high grade- G3 (HG-G3) has been proposed in recognition of, and to help address, the clinical heterogeneity within high grade WHO 2004/2022. We assessed interobserver reproducibility amongst international uropathologists using this three-tier approach. METHODS AND RESULTS: Papillary Ta nonmuscle invasive bladder cancer (NMIBC) specimens (n = 30) were selected and graded by two uropathologists and assessed using WHO 2004/2022 and WHO 1973 and categorized as LG (n = 15), HG-G2 (n = 8), HG-G3 (n = 7), and photographed at 10× and 20× magnification. Images were circulated via Survey Monkey to invited uropathologists who determined: (1) that image was LG or HG, and (2) if HG, assigned to G2 or G3. Model-based kappa measure of association was used to assess interrater agreement. Eighteen uropathologists:(eight North American, eight European, two other) assessed 60 images with 1076 gradings for analysis. The kappa value amongst Europeans versus North Americans was 0.663 versus 0.647 for 10× images and 0.682 versus 0.623 for 20× images. At 10×, agreement for LG, HG-G2, and HG-G3 was 74.6%, 63.6%, and 92.0%, and at 20× was 64.3%, 63.9%, and 95.2% respectively. CONCLUSION: Three-tier grading of papillary Ta NMIBC had substantial interobserver agreement amongst international uropathologists. The recognition of the HG-G3 case reached the highest concordance. North American uropathologists had comparable kappa scores (substantial agreement) to Europeans, despite being unaccustomed to separating HG cases into G2 and G3, demonstrating three-tier grading could be "quickly" adopted by genitourinary experts if endorsed and required by the relevant bodies in their jurisdiction of practice.
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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 | 0.022 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".