Disease detection and resource use in the safety and control arms of the HPV FOCAL cervical cancer screening trial
Bibliographic record
Abstract
BACKGROUND: The HPV FOCAL Trial is a RCT comparing human papilloma virus (HPV) with Liquid Based Cytology (LBC) screening for cervical cancer. Results are presented for the comparison of the Safety and Control arms after two rounds. METHODS: HPV FOCAL included randomisation of women aged 25-65 into the Safety arm, where they were initially screened with HPV and the Control arm, where they received entry screening with LBC, with both arms screened again with LBC at 24 months. RESULTS: There are 6203 (Safety) and 6075 (Control) women included in this analysis. For the Safety vs Control arms, Round 1 screening resulted in increased detection of cervical intraepithelial neoplasia 2 or worse (CIN2+),15.3 vs 10.4 per 1000, RR=1.48 (95%CI=1.08-2.03) and higher colposcopy referral rates, 5.6% vs 3.2%. LBC screening at 24 months resulted in similar colposcopy referral rates, 1.5% vs 1.9%, and decreased CIN2+ detection, 2.0 vs 4.7 per 1000, RR=0.43 (95%CI=0.21-0.88) in the Safety vs Control arms. CIN2+ detection and colposcopy referral rates declined with increasing age in both arms. One round of HPV screening detected similar levels of CIN2+ as two rounds of LBC screening. INTERPRETATION: CIN2+ detection at 2 years was lower in those screened by HPV, indicating an improved 2-year negative predictive value of the HPV test.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".