643 STAGE SPECIFIC POPULATION-BASED TRENDS OF RPLND USE
Bibliographic record
Abstract
You have accessJournal of UrologyPenis/Testis/Urethra: Benign & Malignant Disease II1 Apr 2010643 STAGE SPECIFIC POPULATION-BASED TRENDS OF RPLND USE Daniel Liberman, Lars Badaus, Giovanni Lughezzani, Maxine Sun, Rodolphe Thuret, Wassim Kassouf, Hugues Widmer, Francesco Montorsi, Shahrokh F. Shariat, Paul Perrotte, and Pierre I. Karakiewicz Daniel LibermanDaniel Liberman More articles by this author , Lars BadausLars Badaus More articles by this author , Giovanni LughezzaniGiovanni Lughezzani More articles by this author , Maxine SunMaxine Sun More articles by this author , Rodolphe ThuretRodolphe Thuret More articles by this author , Wassim KassoufWassim Kassouf More articles by this author , Hugues WidmerHugues Widmer More articles by this author , Francesco MontorsiFrancesco Montorsi More articles by this author , Shahrokh F. ShariatShahrokh F. Shariat More articles by this author , Paul PerrottePaul Perrotte More articles by this author , and Pierre I. KarakiewiczPierre I. Karakiewicz More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1017AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES No data are available regarding the use of retroperitoneal lymph node dissection (RPLND) across all stages of nonseminomatous germ cell testicular tumors (NSGCTT) in the community. We examined the rates of RPLND use in this patient subset in a large population-based cohort. METHODS Between 1988 and 2006, 9633 patients with NSGCTT were treated with or without an RPLND within 17 Surveillance, Epidemiology and End Results (SEER) registries. Analyses focused on annual trends (1988-1992, 1993-1997, 1998-2002, 2003-2006) and univariable and multivariable logistic regression models, stratified according to disease stage. Analyses were adjusted for patient age, race (white, black, other), socio-economic status (low vs. high) and SEER region. RESULTS Overall 2620 (27.2%) of 9633 NSGCTT patients underwent an RPLND (1988-1992: 34.7%, 1993-1997: 29.5%, 1998-2002: 27.6%, 2003-2006: 22.2%; X2 trend p<0.001). In patients with stage I NSGCTT, the overall rate of RPLND was 22.4% (1988-1992: 18.4%, 1993-1997: 23.5%, 1998-2002: 32.4%, 2003-2006: 25.7%; X2 trend p<0.001). In patients with stage II NSGCTT the rate of RPLND was 50.1% (1988-1992: 20.9%, 1993-1997: 18.5%, 1998-2002: 31.8%, 2003-2006: 28.8%; X2 trend p=0.003). Finally in patients with stage III NSGCTT the overall rate of RPLND was 13.1% (1988-1992: 15.0%, 1993-1997: 19.0%, 1998-2002: 32.3%, 2003-2006: 33.6%; X2 trend p=0.983). In multivariable logistic regression models that focused on stage I patients, year of surgery (p<0.001) and SEER registry (p<0.001) represented independent predictors of RPLND. In patients with stage II, year of surgery (p=0.01) remained an independent predictor of RPLND. CONCLUSIONS Population based trends indicate a decreasing rate of RPLND use. This decrease is most apparent in stage I patients where a 55.1% drop was recorded. It may be attributable to wider use of surveillance and/or chemotherapy. Less pronounced decrease was also recorded in stage II patients (19.1% drop) and is attributable to the wider use of chemotherapy as monotherapy. The RPLND rates did not change for stage III patients. Montreal, Canada© 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e252 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.MetricsAuthor Information Daniel Liberman More articles by this author Lars Badaus More articles by this author Giovanni Lughezzani More articles by this author Maxine Sun More articles by this author Rodolphe Thuret More articles by this author Wassim Kassouf More articles by this author Hugues Widmer More articles by this author Francesco Montorsi More articles by this author Shahrokh F. Shariat More articles by this author Paul Perrotte More articles by this author Pierre I. Karakiewicz 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".