North American study and meta-analysis evaluating performance of Bladder EpiCheck <sup>®</sup> , a FDA cleared test, in non-muscle invasive bladder cancer recurrence
Bibliographic record
Abstract
Background: Bladder EpiCheck (BE) is a novel methylation-based PCR urine test for the detection of non-muscle invasive bladder cancer (NMIBC) recurrences. Objective: We present the results of a North American study evaluating BE and meta-analysis of literature. Methods: A prospective, blinded, multicenter study was conducted in North America. Voided urine was collected from NMIBC patients prior to cystoscopic surveillance. BE testing was performed centrally. For the meta-analysis, a PUBMED search was performed to identify all published peer-reviewed clinical studies of BE for NMIBC surveillance. Results: In this study, 674 patients were enrolled of which 449 were included. Overall sensitivity was 67% (95%CI 58%-74%), specificity was 84% (80%-88%), PPV was 65% (57%-73%) and NPV was 85% (81%-89%). For high-grade (HG) recurrence, sensitivity was 77% (65%-85%) and NPV was 95% (92%-97%).In patients with negative cystoscopy and cytology at the first study visit, risk of subsequent recurrence in 12 months was 5.3 (2.7-10.3) times higher in patients with positive BE vs. negative BE (p < 0.0001). In patients with negative cystoscopy and equivocal cytology, BE was positive in 75-89% of those with later HG recurrence, with PPV of 42% (15%-72%)-63% (38%-84%).The meta-analysis included 7 studies and 1564 patients. Overall sensitivity was 82% (66-92%), HG sensitivity was 91% (82-95%), specificity was 85% (80-88%), PPV was 60% (55-64%) and HG NPV was 98% (97-99%). Conclusions: The consistently strong performance of BE indicate that a positive test could improve timely disease recurrence detection and a negative test could rule-out HG disease. Furthermore, the low rate of false positive results, potentially minimizes unnecessary downstream procedures and patient anxiety.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.032 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".