MétaCan
Menu
Back to cohort
Record W2258126254 · doi:10.3233/blc-150034

Comparison of Guidelines on Non-Muscle Invasive Bladder Cancer (EAU, CUA, AUA, NCCN, NICE)

2016· review· en· W2258126254 on OpenAlexaffabout
Nicholas Power, Jonathan I. Izawa

Bibliographic record

VenueBladder Cancer · 2016
Typereview
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsGuidelineNiceMedicinePresentation (obstetrics)Bladder cancerFamily medicineCancerIntensive care medicinePathologyInternal medicineComputer scienceSurgery

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.163
GPT teacher head0.474
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations93
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBladder CancerSame topicBladder and Urothelial Cancer TreatmentsFrench-language works237,207