Evaluation of a validated methylation triage signature for human papillomavirus positive women in the HPV FOCAL cervical cancer screening trial
Bibliographic record
Abstract
Human papillomavirus (HPV)-based cervical cancer screening requires triage of HPV positive women to identify those at risk of cervical intraepithelial neoplasia grade 2 (CIN2) or worse. We conducted a blinded case-control study within the HPV FOCAL randomized cervical cancer screening trial of women aged 25-65 to examine whether baseline methylation testing using the S5 classifier provided triage performance similar to an algorithm relying on cytology and HPV genotyping. Groups were randomly selected from women with known HPV/cytology results and pathology outcomes. Group 1: 104 HPV positive (HPV+), abnormal cytology (54 CIN2/3; 50 <CIN2); Group 2: 103 HPV+, normal cytology with HPV persistence at 12 mo. (53 CIN2/3; 50 <CIN2); Group 3: 50 HPV+, normal cytology with HPV clearance at 12 mo. (assumed <CIN2), total n=257. For the combined groups, S5 risk score CIN2/3 relative sensitivity, specificity and positive predictive value (PPV) were compared with other triage approaches. Methylation showed a highly significant increasing trend with disease severity. For CIN3, S5 relative sensitivity and specificity were: 93.2% (95%CI: 81.4-98.0) and 41.8% (35.2-48.8), compared to 86.4% (75.0-95.7) and 49.8% (43.1-56.6) respectively for combined abnormal cytology/HPV16/18 positivity (differences not statistically significant at 5% level); adjusted PPVs were 18.2% (16.2-20.4) and 19.3% (16.6-22.2) respectively. S5 was also positive in baseline specimens from eight cancers detected during or after trial participation. The S5 methylation score had high sensitivity and PPV for CIN3, compatible with US and European thresholds for colposcopy referral. Methylation signatures can identify most HPV positive women at increased risk of cervical cancer from their baseline screening specimens.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".