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Record W4247523603 · doi:10.1016/j.juro.2011.02.1873

1840 EXTERNAL VALIDATION OF BLADDER CANCER PREDICTIVE NOMOGRAMS FOR RECURRENCE, CANCER-FREE SURVIVAL, AND OVERALL SURVIVAL FOLLOWING RADICAL CYSTECTOMY

2011· article· en· W4247523603 on OpenAlexaboutno aff
Michael Brooks, Maxine Sun, Pierre I. Karakiewicz, Shahrok F. Shariat, Gilad E. Amiel, Seth P. Lerner, Guilherme Godoy

Bibliographic record

VenueThe Journal of Urology · 2011
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNomogramCystectomyMedicineBladder cancerLymph nodeTransitional cell carcinomaCancerUrologyOncologyInternal medicine

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyBladder Cancer: Invasive1 Apr 20111840 EXTERNAL VALIDATION OF BLADDER CANCER PREDICTIVE NOMOGRAMS FOR RECURRENCE, CANCER-FREE SURVIVAL, AND OVERALL SURVIVAL FOLLOWING RADICAL CYSTECTOMY Michael Brooks, Maxine Sun, Pierre Karakiewicz, Shahrok F. Shariat, Gilad E. Amiel, Seth P. Lerner, and Guilherme Godoy Michael BrooksMichael Brooks Houston, TX , Maxine SunMaxine Sun Montreal, Canada , Pierre KarakiewiczPierre Karakiewicz Montreal, Canada , Shahrok F. ShariatShahrok F. Shariat New York, NY , Gilad E. AmielGilad E. Amiel Houston, TX , Seth P. LernerSeth P. Lerner Houston, TX , and Guilherme GodoyGuilherme Godoy Houston, TX View All Author Informationhttps://doi.org/10.1016/j.juro.2011.02.1873AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Nomograms provide individualized risk predictions for patients as opposed to staging-based group risk predictions. Three previously published nomograms for patients following radical cystectomy (RC) for urothelial carcinoma (http://www.nomogram.org) have demonstrated superior accuracy in outcomes predications compared to AJCC staging. The goal of the present study is to validate the nomograms for prediction of recurrence (J Urol 176:1354, 2006), cancer-specific and overall survival (Clin Ca Res 12:6663, 2006), following RC and pelvic lymph node dissection (PLND) for urothelial carcinoma of the bladder. METHODS Two surgeons from a single institution performed 205 consecutive RC and extended PLND for bladder cancer from January 2003 to September 2009. 31 patients were excluded (12 due to non-transitional cell histology, 3 due to salvage surgery status, and 16 due to lack of sufficient data), leaving 174 patients with evaluable data for analysis. The data elements were those used in the original nomograms, including age, gender, pathological T stage, N stage, tumor grade, presence of carcinoma in situ and lymphovascular invasion, neoadjuvant chemotherapy, adjuvant chemotherapy and adjuvant radiation therapy. Model discrimination was measured using the receiver operating characteristics derived area under the curve (AUC). RESULTS At the time of treatment, median age was 69.1 years (interquartile range [IQR], 60.9, 74.7), 88.5% were male, and median follow-up for patients alive was 24 months (IQR, 11, 49). The majority of patients had muscle invasive disease (pT2, pT3 and pT4 in 16.7%, 29.9% and 10.3%, respectively) and high-grade tumors (78.7%); 24.1% had positive nodes (pN1=5.7% and pN2=18.4%). The patients received neoadjuvant and adjuvant chemotherapy in 9.2% and 31.6%, respectively. At the time of analysis, 44 had died, 29 patients of disease, and 34 patients had recurred; including 30 patients who died of disease, and 4 patients who were currently alive with disease. The AUC at 2, 5 and 8 years for recurrence, cancer-specific and overall survival were 77.6, 80.9, 79.4%, 82.2, 84.0, 84.9%, and 81.2, 82.0, and 82.5%, respectively. Nomograms overestimated predictions of all three endpoints. CONCLUSIONS The nomograms for bladder cancer recurrence, cancer-specific survival, and overall survival following RC and PLND performed well in this series, with accuracy comparable to the original series. These nomograms may be useful tools when counseling patients and for risk stratification in clinical trials. © 2011 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 185Issue 4SApril 2011Page: e738 Advertisement Copyright & Permissions© 2011 by American Urological Association Education and Research, Inc.MetricsAuthor Information Michael Brooks Houston, TX More articles by this author Maxine Sun Montreal, Canada More articles by this author Pierre Karakiewicz Montreal, Canada More articles by this author Shahrok F. Shariat New York, NY More articles by this author Gilad E. Amiel Houston, TX More articles by this author Seth P. Lerner Houston, TX More articles by this author Guilherme Godoy Houston, TX More articles by this author Expand All Advertisement 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)0.023
metaresearch head score (Gemma)0.057
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.057
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.042
GPT teacher head0.310
Teacher spread0.268 · 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".

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Citations3
Published2011
Admission routes1
Has abstractyes

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