1831 THE PROGNOSTIC ABILITY OF VARIOUS NODAL CODING SCHEMES IN BLADDER CANCER PATIENTS TREATED WITH RADICAL CYSTECTOMY: RESULTS FROM THE SURVEILLANCE, EPIDEMIOLOGY, AND END RESULTS DATABASE
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Invasive/Metastatic Disease III1 Apr 20101831 THE PROGNOSTIC ABILITY OF VARIOUS NODAL CODING SCHEMES IN BLADDER CANCER PATIENTS TREATED WITH RADICAL CYSTECTOMY: RESULTS FROM THE SURVEILLANCE, EPIDEMIOLOGY, AND END RESULTS DATABASE Giovanni Lughezzani, Claudio Jeldres, Shahrokh F. Shariat, Lars Budaus, Maxine Sun, Daniel Liberman, Rodolphe Thuret, Mattia Sangalli, Seth P. Lerner, Paul Perrotte, Francesco Montorsi, and Pierre I. Karakiewicz Giovanni LughezzaniGiovanni Lughezzani Milano, Italy More articles by this author , Claudio JeldresClaudio Jeldres Montreal, Canada More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat Montreal, Canada More articles by this author , Lars BudausLars Budaus Hamburg, Germany More articles by this author , Maxine SunMaxine Sun Montreal, Canada More articles by this author , Daniel LibermanDaniel Liberman Montreal, Canada More articles by this author , Rodolphe ThuretRodolphe Thuret Montpellier, France More articles by this author , Mattia SangalliMattia Sangalli Milano, Italy More articles by this author , Seth P. LernerSeth P. Lerner Houston, TX More articles by this author , Paul PerrottePaul Perrotte Montreal, Canada More articles by this author , Francesco MontorsiFrancesco Montorsi Milano, Italy More articles by this author , and Pierre I. KarakiewiczPierre I. Karakiewicz Montreal, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1769AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Several coding schemes have been proposed to best define the prognostic value of nodal status at radical cystectomy, namely lymph node density, number of positive nodes, number of removed nodes, and pathologic N-substages of the TNM classification. We compared the prognostic ability of these definitions for the prediction of cancer-specific mortality (CSM). METHODS Between 1988 and 2006, 7624 assessable patients underwent radical cystectomy and pelvic lymphadenectomy within 17 Surveillance, Epidemiology, and End Results registries. Univariable and multivariable Cox regression analyses addressed the prognostic impact of different nodal status coding schemes on CSM after surgery. Covariates consisted of age, gender, pT stage and tumor grade. Harrell's concordance index quantified accuracy and 200 bootstrap resamples were used to correct for overfit bias. RESULTS In multivariable analyses addressing CSM after surgery, nodal stage, regardless of its coding, achieved the independent predictor status (p<0.001). Lymph node density represented the most informative predictor of CSM in the entire cohort (gain in predictive accuracy: 2.6%), followed by pN-substages (gain in predictive accuracy: 2.5%) and by the lymph-node density categorized in <20% and >20% (gain in predictive accuracy: 2.3%). However, the differences in predictive accuracy between the three coding schemes were not statistically significant. CONCLUSIONS Although several nodal coding schemes may appear conceptually attractive, from a prognostic perspective the pathologic N-substages perform well and represent a nodal coding scheme that all clinicians are familiar with. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e711 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Giovanni Lughezzani Milano, Italy More articles by this author Claudio Jeldres Montreal, Canada More articles by this author Shahrokh F. Shariat Montreal, Canada More articles by this author Lars Budaus Hamburg, Germany More articles by this author Maxine Sun Montreal, Canada More articles by this author Daniel Liberman Montreal, Canada More articles by this author Rodolphe Thuret Montpellier, France More articles by this author Mattia Sangalli Milano, Italy More articles by this author Seth P. Lerner Houston, TX More articles by this author Paul Perrotte Montreal, Canada More articles by this author Francesco Montorsi Milano, Italy More articles by this author Pierre I. Karakiewicz Montreal, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".