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Record W2101982119 · doi:10.1016/j.juro.2012.02.2563

Cost-Effectiveness of Fluorescent Cystoscopy for Noninvasive Papillary Tumors

2012· article· en· W2101982119 on OpenAlexaffabout
Yves Fradet, Yair Lotan

Bibliographic record

VenueThe Journal of Urology · 2012
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsCystoscopyBladder cancerMedicineCystectomyUrologyCancerTransitional cell carcinomaPathologyUrinary systemInternal medicine

Abstract

fetched live from OpenAlex

No AccessJournal of UrologyOpposing View1 May 2012Cost-Effectiveness of Fluorescent Cystoscopy for Noninvasive Papillary Tumors Yves Fradet and Yair Lotan Yves FradetYves Fradet More articles by this author and Yair LotanYair Lotan More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2012.02.2563AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail References 1 : Variability in the recurrence rate at first follow-up cystoscopy after TUR in stage Ta T1 transitional cell carcinoma of the bladder: a combined analysis of seven EORTC studies. Eur Urol2002; 41: 523. Google Scholar 2 : Metabolic characterization of tumor cell-specific protoporphyrin IX accumulation after exposure to 5-aminolevulinic acid in human colonic cells. Photochem Photobiol2002; 76: 518. Google Scholar 3 : The role of hexaminolevulinate fluorescence cystoscopy in bladder cancer. Nat Clin Pract Urol2007; 4: 542. Google Scholar 4 : Hexyl aminolevulinate fluorescence cystoscopy: new diagnostic tool for photodiagnosis of superficial bladder cancer—a multicenter study. J Urol2003; 170: 226. Link, Google Scholar 5 : A phase III, multicenter comparison of hexaminolevulinate fluorescence cystoscopy and white light cystoscopy for the detection of superficial papillary lesions in patients with bladder cancer. J Urol2007; 178: 62. Link, Google Scholar 6 : Improved detection and treatment of bladder cancer using hexaminolevulinate imaging: a prospective, phase III multicenter study. J Urol2005; 174: 862. Link, Google Scholar 7 : Hexaminolevulinate guided fluorescence cystoscopy reduces recurrence in patients with nonmuscle invasive bladder cancer. J Urol2010; 184: 1907. Link, Google Scholar 8 : Neoadjuvant chemotherapy plus cystectomy compared with cystectomy alone for locally advanced bladder cancer. N Engl J Med2003; 349: 859. Google Scholar 9 : Routine use of photodynamic diagnosis of bladder cancer: practical and economic issues. Eur Urol, suppl.2008; 7: 536. Google Scholar 10 : Treatment changes and long-term recurrence rates after hexaminolevulinate (HAL) fluorescence cystoscopy: does it really make a difference in patients with non-muscle-invasive bladder cancer (NMIBC)?. BJU Int2012; 109: 549. Google Scholar 11 : Should we screen for bladder cancer in a high-risk population?: A cost per life-year saved analysis. Cancer2006; 107: 982. Google Scholar 12 : Transurethral resection of non-muscle-invasive bladder transitional cell cancers with or without 5-aminolevulinic acid under visible and fluorescent light: results of a prospective, randomised, multicentre study. Eur Urol2010; 57: 293. Google Scholar 13 : Detection and clinical outcome of urinary bladder cancer with 5-aminolevulinic acid-induced fluorescence cystoscopy: a multicenter randomized, double-blind, placebo-controlled trial. Cancer2011; 117: 938. Google Scholar 14 : Clinically relevant reduction in risk of recurrence of superficial bladder cancer using 5-aminolevulinic acid-induced fluorescence diagnosis: 8-year results of prospective randomized study. Urology2007; 69: 675. Google Scholar 15 : 5-Aminolaevulinic acid-induced fluorescence cystoscopy during transurethral resection reduces the risk of recurrence in stage Ta/T1 bladder cancer. BJU Int2005; 96: 798. Google Scholar Centre Hospitalier Universitaire de Quebec, Quebec, CanadaDepartment of Urology, University of Texas Southwestern Medical Center, Dallas, Texas© 2012 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 187Issue 5May 2012Page: 1537-1539 Advertisement Copyright & Permissions© 2012 by American Urological Association Education and Research, Inc.Metrics Author Information Yves Fradet More articles by this author Yair Lotan More articles by this author Expand All Advertisement PDF downloadLoading ...

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.044
GPT teacher head0.336
Teacher spread0.293 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2012
Admission routes2
Has abstractyes

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