Effectiveness of school‐based and high‐risk human papillomavirus vaccination programs against cervical dysplasia in Manitoba, Canada
Bibliographic record
Abstract
The effectiveness of a vaccination program is influenced by its design and implementation details and by the target population characteristics. Using routinely collected population-based individual-level data, we assessed the effectiveness (against cervical dysplasia) of Manitoba's quadrivalent human papillomavirus (qHPV) routine school-based vaccination program and a short-lived campaign that targeted women at high-risk of developing cervical cancer. Females ≥9 years old who received the qHPV vaccine in Manitoba (Canada) between September 1, 2006, and March 31, 2013 (N = 31,442) were matched on age and area of residence to up to three unvaccinated females. Cox proportional hazards models were used to estimate qHPV VE against high-grade (HSILs) and low-grade squamous intraepithelial lesions (LSILs) and atypical squamous cells of undetermined significance (ASCUS). Among 14-17-year-old participants who had Pap cytology after enrollment, the adjusted qHPV VE estimates were 30% (17-58%) and 36% (21-48%) against the detection of HSILs and LSILs, respectively. There was, however, no evidence of program effectiveness among females vaccinated at ≥18 years of age and among those with a history of abnormal cytology, who were mostly vaccinated as part of the high-risk program. Estimates of VE for females vaccinated in the school-based program are consistent with the expected benefits from qHPV vaccination. No similar benefits were detected among women vaccinated at an older age, and those with abnormal cytology, who were targeted by the high-risk program. Further efforts should be targeted at achieving higher vaccine coverage among preadolescents, prior to the initiation of sexual activity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".