Low prevalence of vaccine-type HPV infections in young women following the implementation of a school-based and catch-up vaccination in Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: In Quebec, Canada, a school-based HPV vaccination for girls has been offered since 2008. The vaccine used in the program targets HPV16/18, responsible for ∼70% of cervical cancers and HPV6/11, responsible for the majority of anogenital warts. The objective of this study was to assess the prevalence of HPV in vaccinated and unvaccinated women. METHODS: Women aged 17-29 years were eligible to participate. Participants' age, vaccination status and diverse risk factors were assessed by a computer-assisted questionnaire. Biological specimens were obtained by self-sampling. HPV genotyping was performed by Linear Array. RESULTS: A total of 2,118 women were recruited. 2,042 completed the questionnaire and 1,937 provided a vaginal sample. Vaccination coverage varied from 83.5% in women aged 17-19 to 19.1% in those aged 23-29. The overall prevalence of HPV in sexually active women was 39.4% (95%CI: 37.0-41.7) and 56.7% of infected women had multiple type infections. The prevalence of vaccine HPV types varied by age and vaccination status except for women aged 23-29 for whom similar results were observed. Vaccine HPV types were detected in 0.3%, 1.4% and 10.5% of vaccinated women aged 17-19, 20-23, and 23-29 (p<0.05), respectively. HPV16 or HPV18 were detected in 10 women having received at least one dose of vaccine. Nine of these women were already sexually active at the time of vaccination. CONCLUSION: Infections with HPV types included in the vaccine are rare in women aged less than 23 years and are virtually absent in those who received at least one dose of vaccine before sexual debut.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".