MP54-14 TIME TRENDS IN USE OF RADICAL PROSTATECTOMY BY TUMOR RISK AND LIFE EXPECTANCY IN A NATIONAL VA COHORT FROM 2000 TO 2017
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Localized: Surgical Therapy III (MP54)1 Apr 2019MP54-14 TIME TRENDS IN USE OF RADICAL PROSTATECTOMY BY TUMOR RISK AND LIFE EXPECTANCY IN A NATIONAL VA COHORT FROM 2000 TO 2017 Kristina Vaculik, Michael Luu, Lauren Howard, William Aronson, Martha Terris, Christopher Kane, Christopher Amling, Matthew Cooperberg, Stephen Freedland, and Timothy Daskivich* Kristina VaculikKristina Vaculik More articles by this author , Michael LuuMichael Luu More articles by this author , Lauren HowardLauren Howard More articles by this author , William AronsonWilliam Aronson More articles by this author , Martha TerrisMartha Terris More articles by this author , Christopher KaneChristopher Kane More articles by this author , Christopher AmlingChristopher Amling More articles by this author , Matthew CooperbergMatthew Cooperberg More articles by this author , Stephen FreedlandStephen Freedland More articles by this author , and Timothy Daskivich*Timothy Daskivich* More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000556681.16460.b3AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Current prostate cancer (PC) treatment guidelines endorse active surveillance (AS) for most men with low-risk PC and select men with favorable intermediate-risk PC among those with ≥10-year life expectancy (LE), while recommending observation (or non-surgical management) for those with <10-year LE. We sought to identify time trends in the use of radical prostatectomy (RP) for non-metastatic PC across subgroups of tumor risk and LE. METHODS: We sampled 4,902 men from the Shared Equal Access Regional Cancer Hospital (SEARCH) database treated with radical prostatectomy for non-metastatic PC at 8 Veterans Affairs hospitals between 2000 and 2017. LE was calculated using age and Charlson comorbidity index scores. Stratified linear regression was used to calculate trends in proportion of men treated with RP by D'Amico tumor risk and LE (≥10 vs. <10 years) subgroups. RESULTS: Across all men, from 2000 to 2017, the proportion of low-risk tumors treated with RP decreased from 51% to 8% (43% decrease, 95% CI -50% to -37%, p<0.001), while the proportion of intermediate- and high-risk tumors increased from 32% to 60% (28% increase, 95% CI 24% to 32%, p<0.001) and 17% to 33% (16% increase, 95% CI 9% to 23%, p=0.002), respectively. The proportion of favorable intermediate-risk tumors treated with RP decreased from 67% to 40% over the study period (27% decrease, 95% CI -47% to -6%, p=0.01). Among men older than 65 (n=1,398/4,902 (29%)), the proportion treated with RP did not differ over time between those with <10-year LE (44% to 49%, 5% increase, 95% CI -4% to 14%, p=0.2) and those with ≥10-year LE (56% to 51%, 5% decrease, 95% CI -14% to 4%, p=0.2). There was also no statistically significant difference in proportion treated with RP over time between men with <10 vs. ≥10-year LE within any tumor risk subgroup. However, the proportion treated with RP for favorable intermediate-risk disease appeared to decrease less markedly over time in men with <10-year LE compared with ≥10-year LE (9% decrease vs. 44% decrease, p=0.07). CONCLUSIONS: While VA urologists now are operating infrequently on low-risk tumors, rates of RP among men with limited LE appear to be stable over time. LE should play a greater role in triage and management of men with indolent PC. Source of Funding: NCI K08CA230155 Vancouver, Canada; Los Angeles, CA; Durham, NC; Los Angeles, CA; Augusta, GA; San Diego, CA; Portland, OR; San Francisco, CA; Los Angeles, CA© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e789-e790 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kristina Vaculik More articles by this author Michael Luu More articles by this author Lauren Howard More articles by this author William Aronson More articles by this author Martha Terris More articles by this author Christopher Kane More articles by this author Christopher Amling More articles by this author Matthew Cooperberg More articles by this author Stephen Freedland More articles by this author Timothy Daskivich* More articles by this author Expand All 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.012 | 0.003 |
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.
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".