PD09-10 TEMPORAL TRENDS IN MANAGEMENT AND OUTCOMES OF TESTICULAR CANCER: A POPULATION-BASED STUDY
Bibliographic record
Abstract
You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Practice Patterns, Quality of Life and Shared Decision Making II1 Apr 2017PD09-10 TEMPORAL TRENDS IN MANAGEMENT AND OUTCOMES OF TESTICULAR CANCER: A POPULATION-BASED STUDY Michael Leveridge, D Robert Siemens, Kelly Brennan, Jason Izard, Safiya Karim, and Christopher Booth Michael LeveridgeMichael Leveridge More articles by this author , D Robert SiemensD Robert Siemens More articles by this author , Kelly BrennanKelly Brennan More articles by this author , Jason IzardJason Izard More articles by this author , Safiya KarimSafiya Karim More articles by this author , and Christopher BoothChristopher Booth More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.560AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Treatment guidelines for early-stage testicular cancer have increasingly recommended de-escalation of therapy. We sought to describe changes in routine clinical practice and whether this has compromised survival in the general population. METHODS The Ontario Cancer Registry was linked to electronic records of treatment to identify all patients diagnosed with testicular cancer and treated with orchiectomy in Ontario during 2000-2010. Treatment after orchiectomy was classified as radiotherapy (RT), retroperitoneal lymph node dissection (RPLND), chemotherapy, or none. Stage of disease at diagnosis was not available. Cancer-specific (CSS) and overall survival (OS) were measured from date of orchiectomy. The chi-squared test was used to evaluate temporal trends in practice patterns; the log-rank trend test was used to evaluate whether outcomes changed over time. RESULTS Orchiectomy pathology reports were available for 86% (2821/3281) of all cases in Ontario; the study population included 1580 and 1105 cases of seminoma and non-seminoma (NSGCT); other histologies were excluded. Median age was 34 years. Among patients with seminoma there was a significant increase in the proportion of patients with no active treatment after orchiectomy (from 33% to 66%, p<0.001). Use of RT decreased over time (57% to 18%, p<0.001) and use of chemotherapy remained stable (from 16% to 17%, p=0.344). Post-orchiectomy practice patterns remained relatively stable among patients with NSGCT: no treatment 29% to 41% (p=0.221); chemotherapy 69% to 55% (p=0.203); RPLND 27% to 26% (p=0.308). Among the 296 patients undergoing RPLND, 61% were performed in the post-chemotherapy setting; this proportion remained stable over time (p=0.423). OS for the entire cohort at 5 and 10 years was 96% and 94%. CSS at 5 and 10 years was 97% and 97%. There was no significant change in OS or CSS for seminoma (98% and 99% respectively) or NSGCT (96% and 96%) over the study period. CONCLUSIONS Since 2000 there has been de-escalation of treatment among men with seminoma, with surveillance alone predominating in recent years. Practice patterns for NSGCT have remained stable since 2000. Outcomes achieved in the general population are very good and have not decreased over time with de-escalation of therapy. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e197-e198 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Michael Leveridge More articles by this author D Robert Siemens More articles by this author Kelly Brennan More articles by this author Jason Izard More articles by this author Safiya Karim More articles by this author Christopher Booth 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".