Aptima HPV Assay versus Hybrid Capture® 2 HPV test for primary cervical cancer screening in the HPV FOCAL trial
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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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".