The Impact of Quadrivalent Human Papillomavirus (HPV; Types 6, 11, 16, and 18) L1 Virus‐Like Particle Vaccine on Infection and Disease Due to Oncogenic Nonvaccine HPV Types in Sexually Active Women Aged 16–26 Years
Bibliographic record
Abstract
BACKGROUND: We evaluated the impact of a quadrivalent human papillomavirus (HPV) vaccine on infection and cervical disease related to 10 nonvaccine HPV types (31, 33, 35, 39, 45, 51, 52, 56, 58, and 59) associated with >20% of cervical cancers. The population evaluated included HPV-naive women and women with preexisting HPV infection and/or HPV-related disease at enrollment. METHODS: Phase 3 efficacy studies enrolled 17,622 women aged 16-26 years. Subjects underwent cervicovaginal sampling and Pap testing on day 1 and then at 6-12-month intervals for up to 4 years. HPV typing was performed on samples from enrollment and follow-up visits, including samples obtained for diagnosis or treatment of HPV-related disease. All subjects who received 1 dose and returned for follow-up were included. RESULTS: Vaccination reduced the rate of HPV-31/33/45/52/58 infection by 17.7% (95% confidence interval [CI], 5.1% to 28.7%) and of cervical intraepithelial neoplasia (CIN) 1-3 or adenocarcinoma in situ (AIS) by 18.8% (95% CI, 7.4% to 28.9%). Vaccination also reduced the rate of HPV-31/58/59-related CIN1-3/AIS by 26.0% (95% CI, 6.7% to 41.4%), 28.1% (95% CI, 5.3% to 45.6%), and 37.6% (95% CI, 6.0% to 59.1%), respectively. Although a modest reduction in HPV-31/33/45/52/58-related CIN2 or worse was observed, the estimated reduction was not statistically significant. CONCLUSIONS: These cross-protection results complement the vaccine's prophylactic efficacy against disease associated with HPV-6, -11, -16, and -18. Long-term monitoring of vaccinated populations are needed to fully ascertain the population-based impact and public health significance of these findings. TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT00092521 , NCT00092534 , and NCT00092482.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".