Grading of Urothelial Carcinoma and The New “World Health Organisation Classification of Tumours of the Urinary System and Male Genital Organs 2016”
Bibliographic record
Abstract
CONTEXT: In the management of urothelial carcinoma, determination of the pathological grade aims at stratifying tumours into different prognostic groups to allow evaluation of treatment results, and optimise patient management. This article reviews the principles behind different grading systems for urothelial bladder carcinoma discussing their reproducibility and prognostic value. OBJECTIVE: This paper aims to show the evolution of the World Health Organisation (WHO) grading system, discussing their reproducibility and prognostic value, and evaluating which classification system best predicts disease recurrence and progression. The most optimal classification system is robust, reproducible, and transparent with comprehensive data on interobserver and intraobserver variability. The WHO published an updated tumour classification in 2016, which presents a step forward, but its performance will need validation in clinical studies. EVIDENCE ACQUISITION: Medline and EMBASE were searched using the key terms WHO 1973, WHO/International Society of Urological Pathology 1998, WHO 2004, WHO 2016, histology, reproducibility, and prognostic value, in the time frame 1973 to May 2016. The references list of relevant papers was also consulted, resulting in the selection of 48 papers. EVIDENCE SYNTHESIS: There are still inherent limitations in all available tumour classification systems. The WHO 1973 presents considerable ambiguity for classification of the G2 tumour group and grading of the G1/2 and G2/3 groups. The 2004 WHO classification introduced the concept of low-grade and high-grade tumours, as well as the papillary urothelial neoplasm of low malignant potential category which is retained in the 2016 classification. Furthermore, while molecular markers are available that have been shown to contribute to a more accurate histological grading of urothelial carcinomas, thereby improving selection of treatment for a given patient, these are not (yet) part of standard clinical practice. CONCLUSIONS: The prognosis of patients diagnosed with urothelial carcinoma greatly depends on correct histological grading of the tumour. There is still limited data regarding intraobserver and interobserver variability differences between the WHO 1973 and 2004 classification systems. Additionally, reproducibility remains a concern: histological differences between the various types of tumour may be subtle and there is still no consensus amongst pathologists. The recent WHO 2016 classification presents a further improvement on the 2004 classification, but until further data becomes available, the European Association of Urology currently recommends the use of both WHO 1973 and WHO 2004/2016 classifications. PATIENT SUMMARY: Bladder cancer, when treated in time, has a good prognosis. However, selection of the most optimal treatment is largely dependent on the information your doctor will receive from the pathologist following evaluation of the tissue resected from the bladder. It is therefore important that the classification system that the pathologist uses to grade the tissue is transparent and clear for both urologists and pathologists. A reliable classification system will ensure that aggressive tumours are not misinterpreted, and less aggressive cancer is not overtreated.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".