Analytical validation and diagnostic performance of the ASCL1/ZNF582 methylation test for detection of high-grade anal intraepithelial neoplasia and anal cancer
Bibliographic record
Abstract
DNA methylation testing on biopsies can detect high-grade anal intraepithelial neoplasia (HGAIN) in need of treatment and anal cancer. This study aimed to analytically validate and determine the diagnostic performance of a newly developed multiplex quantitative methylation-specific PCR, PreCursor-M AnoGYN(RUO), combining ASCL1, ZNF582 and a reference (ACTB) in one assay. Analytical validation was performed on two qPCR devices using predefined quality criteria. Diagnostic performance was determined on a cross-sectional series of 111 anal biopsies covering all stages of anal disease. Differences in methylation levels were assessed using the Kruskal-Wallis test. Area under the curve was determined using logistic regression analysis. Detection rates were calculated at predefined specificities for the cross-sectional and an additional longitudinal series of 23 HGAIN biopsies preceding anal cancer (i.e., progressive HGAIN). For both devices analytical quality criteria were met. ASCL1 and ZNF582 methylation levels increased with increasing severity of disease (p < 6*10−8). Diagnostic performance for AIN3+ was 0.81. All cancers and virtually all progressive HGAIN were detected at 70% and 80% specificity. In conclusion, the ASCL1/ZNF582 methylation test (PreCursor-M AnoGYN(RUO)) was demonstrated to be highly robust and reproducible. Moreover, it had excellent diagnostic accuracy to detect AIN3+ and can potentially be used to guide HGAIN management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".