Evidence for cross-protection but not type-replacement over the 11 years after human papillomavirus vaccine introduction
Bibliographic record
Abstract
Examination of cross-protection and type replacement after human papillomavirus (HPV) vaccine introduction is essential to guide vaccination recommendations and policies. The aims of this study were to examine trends in non-vaccine-type HPV: 1) genetically related to vaccine types (to assess for cross-protection) and 2) genetically unrelated to vaccine types (to assess for type replacement), among young women 13-26 years of age during the 11 years after HPV vaccine introduction. Participants were recruited from a hospital-based teen health center and a community health department for four cross-sectional surveillance studies between 2006 and 2017. Participants completed a survey that assessed sociodemographic characteristics and behaviors, and cervicovaginal swabs were collected and tested for 36 HPV genotypes. We determined changes in proportions of non-vaccine-type HPV prevalence and conducted logistic regression to determine the odds of infection across the surveillance studies, propensity-score adjusted to control for selection bias. Analyses were stratified by vaccination status. Among vaccinated women who received only the 4-valent vaccine (n = 1,540), the adjusted prevalence of HPV types genetically related to HPV16 decreased significantly by 45.8% (adjusted odds ratio [AOR] = 0.48, 95% confidence interval [CI] = 0.31-0.74) from 2006-2017, demonstrating evidence of cross-protection. The adjusted prevalence of HPV types genetically related to HPV18 did not change significantly (14.2% decrease, AOR = 0.83, 95% CI = 0.56-1.21). The adjusted prevalence of HPV types genetically unrelated to vaccine types did not change significantly (4.2% increase, AOR = 1.09, CI = 0.80-1.48), demonstrating no evidence of type replacement. Further studies are needed to monitor for cross-protection and possible type replacement after introduction of the 9-valent HPV vaccine.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".