648 TUMOR GRADE IMPROVES THE ABILITY OF THE PROGNOSTIC ABILITY OF AJCC STAGES IN PATIENTS WITH PENILE CARCINOMA
Bibliographic record
Abstract
You have accessJournal of UrologyPenis/Testis/Urethra: Benign & Malignant Disease II1 Apr 2010648 TUMOR GRADE IMPROVES THE ABILITY OF THE PROGNOSTIC ABILITY OF AJCC STAGES IN PATIENTS WITH PENILE CARCINOMA Rodolphe Thuret, Claudio Jeldres, Lars Budäus, Giovanni Lughezzani, Daniel Liberman, Maxine Sun, Jean-Jacques Patard, Sharokh F. Shariat, Markus Graefen, Francesco Montorsi, Paul Perrotte, and Pierre Karakiewicz Rodolphe ThuretRodolphe Thuret Montpellier, France, Metropolitan More articles by this author , Claudio JeldresClaudio Jeldres Montreal, Canada More articles by this author , Lars BudäusLars Budäus Hamburg, Germany More articles by this author , Giovanni LughezzaniGiovanni Lughezzani Milano, Italy More articles by this author , Daniel LibermanDaniel Liberman Montreal, Canada More articles by this author , Maxine SunMaxine Sun Montreal, Canada More articles by this author , Jean-Jacques PatardJean-Jacques Patard Rennes, France, Metropolitan More articles by this author , Sharokh F. ShariatSharokh F. Shariat Montreal, Canada More articles by this author , Markus GraefenMarkus Graefen Hamburg, Germany More articles by this author , Francesco MontorsiFrancesco Montorsi Milano, Italy More articles by this author , Paul PerrottePaul Perrotte Montreal, Canada More articles by this author , and Pierre KarakiewiczPierre Karakiewicz Montreal, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1022AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The AJCC or TNM staging of penile carcinoma represents a standard and is widely used in clinical practice. We examined the ability of tumor grade that currently is not considered in the AJCC or TNM staging, to improve the prognostic ability of these two established staging schemes. METHODS We relied on a population of 1577 penile carcinoma patients stages T1-4 N0-3 M0 who underwent an excision biopsy or partial or radical penectomy with or without a lymph node dissection. Separated Cox regression models were fitted for AJCC stages I to III (stage 0 not considered), T and N stages, as well as for T and N stages with tumor grade (grades I vs. II vs. III-IV). Harrell's concordance index was quantified for each of the three tested schemes. RESULTS Overall, 194 patients died of penile carcinomas and the 5-year cancer-specific mortality rate was 16.1% (95% CI=14.0 to 18.4%). The accuracy of AJCC staging in the prediction of cancer-specific mortality-free survival was 68.3% versus 70.0% for TN-based prediction (Mantel-Haenszel test, p<0.001) versus 72.0% for T and N and grade-based prediction (Mantel-Haenszel test, p<0.001). CONCLUSIONS The AJCC staging stratifies non-metastatic penile cancer patients into three distinct categories versus 16 categories for the combination of T1-4 and N0-3 stages versus 48 categories for the combination of T1-4, N0-3 and Grade 1-3 stage and grade combination. The prognostic accuracy of the AJCC staging schemes was the lowest versus an intermediate value for the TN-based scheme versus the highest for the TN and grade-based scheme. The superior prognostic ability of the TN and grade-based scheme suggests that grade should be routinely considered when the T and N stages are used for prediction of prognosis. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e254 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Rodolphe Thuret Montpellier, France, Metropolitan More articles by this author Claudio Jeldres Montreal, Canada More articles by this author Lars Budäus Hamburg, Germany More articles by this author Giovanni Lughezzani Milano, Italy More articles by this author Daniel Liberman Montreal, Canada More articles by this author Maxine Sun Montreal, Canada More articles by this author Jean-Jacques Patard Rennes, France, Metropolitan More articles by this author Sharokh F. Shariat Montreal, Canada More articles by this author Markus Graefen Hamburg, Germany More articles by this author Francesco Montorsi Milano, Italy More articles by this author Paul Perrotte Montreal, Canada More articles by this author Pierre 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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".