MP12-14 VARIATIONS IN QUALITY METRICS FOR LOCALIZED PROSTATE CANCER IN AN INTERNATIONAL COHORT
Bibliographic record
Abstract
You have accessJournal of UrologyHealth Services Research: Practice Patterns, Quality of Life and Shared Decision Making I (MP12)1 May 2024MP12-14 VARIATIONS IN QUALITY METRICS FOR LOCALIZED PROSTATE CANCER IN AN INTERNATIONAL COHORT Adam B. Weiner, Anissa V. Nguyen, Robert E. Reiter, Mark S. Litwin, and True North Global Registry Adam B. WeinerAdam B. Weiner , Anissa V. NguyenAnissa V. Nguyen , Robert E. ReiterRobert E. Reiter , Mark S. LitwinMark S. Litwin , and True North Global Registry View All Author Informationhttps://doi.org/10.1097/01.JU.0001009376.16371.fb.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Quality of care provided to patients with prostate cancer (PCa) can be improved by following evidence-based recommendations. No extant data report international variation of quality indicators for localized PCa. Elimination of variation can improve compliance with quality indicators and hence quality of care. METHODS: We included men with local-regional PCa at sites in one of 11 countries within the Movember True North Global Registry (2013-2022). We assessed four primary outcomes indicating high-quality care: 1) Use of active surveillance (AS) for NCCN low-risk PCa; 2) treatment within 12 months of diagnosis for unfavorable-risk (NCCN unfavorable intermediate and high risk) PCa; 3) no use of staging imaging (bone scan, CT, or PET) for imaging favorable-risk PCa; and 4) use of staging imaging for unfavorable-risk PCa. Primary outcomes were tested by international region using Chi-Square analyses by combining the most recent three years of data, adjusting for multiple tests with Bonferroni correction (p=0.05/4=0.0125). RESULTS: Of those with low-risk disease (n=5,112), 45.1% (2,303) elected AS. Rates of AS for these patients (2020-2022) were the highest in Australia/New Zealand (85%) and 14% in Central Europe (Figure 1). Of those with unfavorable-risk disease (n=14,419), 86.6% (36,451) had treatment within 1 year 0.4% (62) brachytherapy, 17.9% (2,578) external beam radiotherapy, and 81.7% (11,779) prostatectomy. Active treatment rates for unfavorable-risk disease were highest in Central Europe (98%) compared to 64% in the US. Rates of no imaging for favorable-risk disease ranged from 92% in Canada to 30% in Italy while rates of imaging for unfavorable-risk disease ranged from 83% in Hong Kong to 39% in the United States (all Chi-Square p<0.0125). CONCLUSIONS: We describe variation in quality metrics for localized PCa in a single international cohort. While quality metrics may vary based on regional cultural and healthcare structures, these benchmarks can promote processes aimed at optimizing care. Ultimately, promoting quality care for men with PCa will require local advocacy for evidence-based practices. Download PPT Source of Funding: The Simon-Strauss Foundation, Prostate Cancer Foundation, Dr. Allen and Charlotte Ginsburg Fellowship in Precision Genomic Medicine, and Movember Foundation © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e206 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Adam B. Weiner More articles by this author Anissa V. Nguyen More articles by this author Robert E. Reiter More articles by this author Mark S. Litwin More articles by this author True North Global Registry 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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.014 | 0.002 |
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".