Comparative performance of the human papillomavirus test and cytology for primary screening for high‐grade cervical intraepithelial neoplasia at the population level
Bibliographic record
Abstract
The World Health Organization recommends high-risk human papillomavirus (hrHPV)-based screening for women 39 to 49 years, based on the greater accuracy of hrHPV-based screening for cervical cancer detection. Many cervical cancer screening programs have incorporated hrHPV testing and multiple early cervical cancer detection strategies have been evaluated, mostly under controlled conditions. However, there are few evaluations of combined hrHPV and cytology strategies post-implementation at the population level. Our study sought to estimate the relative yield of hrHPV testing compared to cervical cytology, as a primary screening test for cervical intraepithelial neoplasia grade 2+ (CIN2+), used at the population level. We analyzed screening data from Mexico's public cervical cancer prevention program from 2010 to 2015 in women 35 to 64 years. The study population consisted of two cohorts: one from a total of 2 881 962 cytology-based screening tests and another from a total of 2 004 497 hrHPV-based screening tests, which are concurrent in time. We performed a relative yield analysis using Poisson regression models to compare the effectiveness of hrHPV testing for CIN2+ with cervical cytology. A total of 4 886 459 records were analyzed, including 23 999 biopsies; 0.12% (n = 6166) had a CIN2+ histologic diagnosis. hrHPV testing with cytological triage detects twice as many CIN2+ cases as screening using cytology alone.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".