MP23-18 FACTORS ASSOCIATED WITH LONG-TERM ADHERENCE TO ACTIVE SURVEILLANCE AMONG MEN WITH LOW RISK PROSTATE CANCER: A POPULATION BASED STUDY FROM ONTARIO
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Localized: Active Surveillance I (MP23)1 Apr 2020MP23-18 FACTORS ASSOCIATED WITH LONG-TERM ADHERENCE TO ACTIVE SURVEILLANCE AMONG MEN WITH LOW RISK PROSTATE CANCER: A POPULATION BASED STUDY FROM ONTARIO Narhari Timilshina*, Patrick Richard, Maria Komisarenko, Doug Cheung, Lisa Martin, Shabbir Alibhai, and Antonio Finelli Narhari Timilshina*Narhari Timilshina* More articles by this author , Patrick RichardPatrick Richard More articles by this author , Maria KomisarenkoMaria Komisarenko More articles by this author , Doug CheungDoug Cheung More articles by this author , Lisa MartinLisa Martin More articles by this author , Shabbir AlibhaiShabbir Alibhai More articles by this author , and Antonio FinelliAntonio Finelli More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000856.018AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Active surveillance (AS) has become widely accepted as the standard of care for low-risk prostate cancer (PC) worldwide.. However limited work has examined the population-level uptake and real world adherence. We describe the uptake and long-term adherence to AS, and the factors associated with them using provincial level data on men with low risk PC. METHODS: This was an observational, population-based study using linked administrative databases in Ontario. All men diagnosed with PC between 2008 and 2014 in Ontario, Canada were identified from the Ontario Cancer Registry. The treatment-free survival rate was estimated using cumulative incidence function methods. Factors associated with long-term adherence to AS were evaluated using Cox Proportional Hazard (PH) models. Sensitivity analyses used Fine and Gray models to account for competing risks of progression to metastases or death. RESULTS: Overall 51% of low risk PC patients were initially managed by AS. AS uptake increased substantially from 39.5 % to 63.5% between 2008 and 2014. The median time to discontinuation of AS was 58 months (IQR:23-101). Cumulative AS adherence rates at year 1 and year 5 were 87.1%% and 63.3%, respectively. On multivariable analysis, factors associated with lower AS discontinuation within the median 5-year were increasing age at diagnosis (75+year HR 0.31 95%CI 0.26-0.38 vs. <55), lower physician volume tertile and lower Institution tertile. Higher AS discontinuation was associates with higher PSA at diagnosed and higher prostate volume. CONCLUSIONS: The uptake of AS significantly increased in recent years in Ontario. We found large number of patients continue on As after 5-year at population level for men diagnosed with low risk PC in Canada. Factors affecting continue AS were higher PSA at diagnosis and higher prostate volume. Source of Funding: The Prostate Cancer Canada © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e345-e345 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Narhari Timilshina* More articles by this author Patrick Richard More articles by this author Maria Komisarenko More articles by this author Doug Cheung More articles by this author Lisa Martin More articles by this author Shabbir Alibhai More articles by this author Antonio Finelli 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".