Comparison between 1973 and 2004/2016 WHO grading systems in patients with Ta urothelial carcinoma of urinary bladder
Bibliographic record
Abstract
AIMS: To compare the 1973 WHO and the 2004/2016 WHO grading systems in patients with urothelial carcinoma of urinary bladder (UCUB), since no consensus has been made which classification should supersede the other and since both are recommended in clinical practice. METHODS: Newly diagnosed patients with Ta UCUB treated with transurethral resection of bladder tumour were abstracted from the Surveillance, Epidemiology and End Results database (2010-2016). Kaplan-Meier plots and multivariable Cox regression models (CRMs) tested cancer-specific mortality (CSM), according to 1973 WHO (G1 vs G2 vs G3) and to 2004/2016 WHO (low-grade vs high-grade) grading systems. RESULTS: Of 35 986 patients, according to 1973 WHO grading system, 8165 (22.7%) were G1, 17 136 (47.6%) were G2 and 10 685 (29.7%) were G3. According to 2004/2016 WHO grading system, 24 961 (69.4%) were low-grade versus 11 025 (30.6%) high-grade. In multivariable CRMs, G3 (HR: 2.05, p<0.001), relative to G1, and high-grade(HR: 2.13, p<0.001), relative to low-grade, predicted higher CSM. Conversely, G2 (p=0.8) was not an independent predictor. The multivariable models without consideration of either grading system were 74% accurate in predicting 5-year CSM. After addition of 1973 WHO or 2004/2016 WHO grade, the accuracy increased to 76% and 77%, respectively. CONCLUSIONS: From a statistical standpoint, it appears that the 2004/2016 WHO grading system holds a small, although measurable advantage over the 1973 WHO grading system. Other considerations, such as intraobserver and interobserver variability may represent an additional matric to consider in deciding which grading system is better.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".