MP71-20 BENEFITS AND COSTS OF ALTERNATIVE GUIDELINES FOR SURVEILLANCE OF HIGH-RISK NON-MUSCLE INVASIVE BLADDER CANCER (NMIBC)
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Non-invasive IV (MP71)1 May 2024MP71-20 BENEFITS AND COSTS OF ALTERNATIVE GUIDELINES FOR SURVEILLANCE OF HIGH-RISK NON-MUSCLE INVASIVE BLADDER CANCER (NMIBC) Zhuo T. Su, Katherine Mahon, Michael Rezaee, Sunil Patel, Jeffrey Townsend, and Max Kates Zhuo T. SuZhuo T. Su , Katherine MahonKatherine Mahon , Michael RezaeeMichael Rezaee , Sunil PatelSunil Patel , Jeffrey TownsendJeffrey Townsend , and Max KatesMax Kates View All Author Informationhttps://doi.org/10.1097/01.JU.0001009548.76580.ba.20AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Limited evidence exists to inform optimal strategies for surveillance of NMIBC. We used simulations to compare the benefits and costs of major guidelines for surveillance of high-risk NMIBC. METHODS: A Monte-Carlo simulation was created to model the 10-year outcomes and costs of 5 guidelines for surveillance of 10,000 patients diagnosed with carcinoma in situ (CIS), high-grade (HG) Ta or T1 NMIBC at age 70 years: the American Urological Association (AUA), National Comprehensive Cancer Network (NCCN), European Association of Urology (EAU), Canadian Urological Association (CUA), and National Institute for Health and Care Excellence (NICE). We evaluated separately the most intense (denoted as AUAi and CUAi) and relaxed (AUAr and CUAr) surveillance regimens within the range of surveillance frequencies allowed by the AUA and CUA guidelines. RESULTS: For HGT1, absolute differences in 10-year cumulative incidence (CI) of muscle invasive bladder cancer (MIBC) were ≤0.4% across guidelines (Table 1). Differences across guidelines were minimal in cancer-specific survival (CSS) and overall survival (OS). For CIS and HgTa, greater absolute differences in MIBC CI were seen across guidelines (CIS: ≤0.8%; HgTa: ≤1.3%) and within guidelines (CIS: 0.6% for both AUA and CUA; HgTa: 0.9% for AUA, 0.6% for CUA). For both CIS and HGTa, absolute differences across guidelines were ≤0.5% in CSS and ≤0.2% in OS. In cost-effectiveness analysis, the surveillance regimens all achieved similar health utilities; the less stringent ones such as CUAr and NICE led to cost savings (Table 2). Under conventional cost-effectiveness thresholds, CUAr was the most cost-effective option for HGT1 and CIS, and NICE for HGTa. CONCLUSIONS: Oncological outcomes were highly similar across guidelines for surveillance of HGT1. Small to moderate differences were noted across and within guidelines for surveillance of CIS and HgTa. More stringent surveillance regimens did not achieve enough health utility benefits to be found cost-effective versus less stringent regimens. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e1169 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Zhuo T. Su More articles by this author Katherine Mahon More articles by this author Michael Rezaee More articles by this author Sunil Patel More articles by this author Jeffrey Townsend More articles by this author Max Kates 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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".