Overview of the European and North American studies on HPV testing in primary cervical cancer screening
Bibliographic record
Abstract
Several studies suggest that HPV testing is more sensitive than cytology in primary cervical screening. These studies had different designs and were reported in different ways. Individual patient data were collected for all European and North American studies in which cytology was routinely performed and HPV testing was included as an additional parallel test. More than 60,000 women were included. The sensitivity and specificity of HPV testing were compared with routine cytology, both overall and for ages <35, 35-49 and 50+. The age-specific prevalence of high risk HPV (hr-HPV) was also analysed. HPV testing was substantially more sensitive in detecting CIN2+ than cytology (96.1% vs. 53.0%) but less specific (90.7% vs. 96.3%). The sensitivity of HPV testing was similar in all studies carried out in different areas of Europe and North America, whereas the sensitivity of cytology was highly variable. HPV sensitivity was uniformly high at all ages, whereas the sensitivity of cytology was substantially better in women over the age of 50 than in younger women (79.3% vs. 59.6%). The specificity of both tests increased with age. Positivity rates for HPV testing in women without high-grade CIN were region dependent. These results support the use of HPV testing as the sole primary screening test, with cytology reserved for women who test HPV positive. Large demonstration projects are needed to fully evaluate this strategy.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.019 | 0.031 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".