Comparison of Guidelines on Non-Muscle Invasive Bladder Cancer (EAU, CUA, AUA, NCCN, NICE)
Bibliographic record
Abstract
BACKGROUND: Non-muscle invasive bladder cancer (NMIBC) represents a considerably diverse patient group and the management of this complex disease is debatable. A number of panels from Europe and North America have convened on the topic and recently released guideline documents. OBJECTIVE: The purpose was to compare and contrast the NMIBC guideline recommendations from the EAU (Europe), CUA (Canada), NCCN (United States), AUA (United States), and NICE (United Kingdom). METHODS: All unabridged guideline documents were reviewed by the authors and comparisons were completed according to major topics in NMIBC. RESULTS: Despite a paucity of high level evidence regarding the majority of management topics in NMIBC, there was general agreement among the various guideline panels. Differences mainly centered on the categories of evidence synthesized and grades of recommendations. Each document offers a unique presentation of the available literature and guideline recommendation. CONCLUSIONS: The guidelines for NMIBC from the EAU, CUA, AUA, NCCN, and NICE provide considerable consensus regarding the management of this often difficult disease. Clinicians are encouraged to familiarize themselves with all of the guidelines in order to determine which style of presentation would be most useful to their current practice.
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 | 0.026 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".