HPV for cervical cancer screening (HPV FOCAL): Complete Round 1 results of a randomized trial comparing HPV‐based primary screening to liquid‐based cytology for cervical cancer
Bibliographic record
Abstract
Complete Round 1 data (baseline and 12-month follow-up) for HPV FOCAL, a randomized trial establishing the efficacy of HPV DNA testing with cytology triage as a primary screen for cervical cancer are presented. Women were randomized to one of three arms: Control arm - Baseline liquid-based cytology (LBC) with ASCUS results triaged with HPV testing; Intervention and Safety arms - Baseline HPV with LBC triage for HPV positives. Results are presented for 15,744 women allocated to the HPV (intervention and safety combined) and 9,408 to the control arms. For all age cohorts, the CIN3+ detection rate was higher in the HPV (7.5/1,000; 95%CI: 6.2, 8.9) compared to the control arm (4.6/1,000; 95%CI: 3.4, 6.2). The CIN2+ detection rates were also significantly higher in the HPV (16.5/1,000; 95%CI: 14.6, 18.6) vs. the control arm (10.1/1,000; 95%CI: 8.3, 12.4). In women ≥35 years, the overall detection rates for CIN2+ and CIN3+ were higher in the HPV vs. the control arm (CIN2+:10.0/1,000 vs. 5.2/1,000; CIN3+: 4.2/1,000 vs. 2.2/1,000 respectively, with a statistically significant difference for CIN2+). HPV testing detected significantly more CIN2+ in women 25-29 compared to LBC (63.7/1,000; 95%CI: 51.9, 78.0 vs. 32.4/1,000; 95%CI: 22.3, 46.8). HPV testing resulted in significantly higher colposcopy referral rates for all age cohorts (HPV: 58.9/1,000; 95%CI: 55.4, 62.7 vs. CONTROL: 30.9/1,000; 95%CI: 27.6, 34.6). At completion of Round 1 HPV-based cervical cancer screening in a population-based program resulted in greater CIN2+ detection of across all age cohorts compared to LBC screening.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".