Aptima HPV Assay versus Hybrid Capture® 2 HPV test for primary cervical cancer screening in the HPV FOCAL trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Cervical cancer screening programs are switching from Pap screening to high-risk HPV testing. OBJECTIVES: (HC2) for primary cervical screening. STUDY DESIGN: HPV FOCAL is a randomized trial comparing HC2 to liquid-based cytology (LBC) for screening women aged 25-65. AHPV and HC2 were compared at the baseline screen (n=3473). Genotyping was by the Aptima HPV 16 18/45 Genotype Assay. We assessed HPV genotyping and reflex LBC for colposcopy triage. RESULTS: AHPV/HC2 agreement was 96.5% (kappa 0.76); positive agreement was 77.4%. The AHPV positive rate was 7.2% vs. 8.4% for HC2 (p=0.06). Based on HC2 screening, round 1 CIN2 and CIN3+ rates were 9.2/1000 and 5.2/1000 respectively. Using HC2 as the comparator test, AHPV CIN2+ and CIN3+ relative sensitivities were 0.96 and 1.00 (p=1.00) respectively. High-grade reflex LBC and HPV 16 infection were significantly associated with CIN3+. AHPV specificity was 0.94 vs. 0.93 (p=0.05) for HC2. Compared with triage of HC2+ with abnormal cytology or HPV persistence for 12 months, colposcopy referral would be significantly reduced (38.3/1000 vs. 60.8/1000; p<0.001) if AHPV+ women with abnormal LBC and HPV 16/18/45 were referred at baseline. CIN2+ and CIN3+ detection rates were not significantly different for the two strategies. CONCLUSIONS: AHPV vs. HC2 screening had equivalent CIN2+ and CIN3+ detection. Triage of AHPV+ by abnormal reflex LBC and the presence of HPV 16/18/45 would result in a significantly lower colposcopy referral rate with similar CIN2+ and CIN3+ detection rates as the overall HC2+ referral algorithm.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it