Bibliographic record
Abstract
Abstract HPV causes multiple cancers in men and women, accounting for ~5% of all cancers worldwide. In 2006 a 4-valent HPV vaccine was licensed for use for cervical cancer prevention in the US and other countries. After completion of a male HPV vaccine efficacy trial, the 4-valent HPV vaccine was also licensed for the prevention of genital warts in 2009 and anal cancer in 2010. Since licensure, several countries have developed policies promoting national dissemination of the vaccine. Australia has led the way with a robust public health program that rapidly reached ~80% of the age eligible female population. With up to six full years of vaccine dissemination to adolescent females countries are now able to report population effectiveness, or the impact of the vaccine to prevent HPV-related diseases. There are three main outcome variables of interest: short-term (HPV infection and genital wart rates), intermediate-term (reduction in incident cervical lesions), and long-term (incidence and mortality from HPV-related cancers). Effectiveness data for short-term outcomes have recently been reported for Australia, New Zealand, Denmark, Sweden, Germany, Belgium, Canada, and the US. Significant declines in genital wart incidence in females have been reported from all countries to date that have evaluated effectiveness. In Australia, where there was early vaccine adoption nationally and high vaccine penetrance, concomitant declines in genital warts among unvaccinated males have also been documented. Intermediate-term endpoints, such as cervical pre-cancerous lesions have also significantly declined in Australia, Denmark, and the US. These results provide early evidence that routine vaccination significantly reduces HPV infection and early disease endpoints attributed to the 4 major disease causing types of HPV among young adult females at the population level. However, to achieve the full promise of eliminating HPV vaccine type-related disease, broad dissemination of the vaccine is required. Several strategies are under consideration to improve population coverage, including dissemination of vaccine to low resource countries through the GAVI program, alternative dose schedules, and two vs. three dose schedules. Ultimately, strong public health and physician recommendations, as well as population acceptability, are needed to eliminate HPV-related disease through a vaccine approach. Citation Format: Anna R. Giuliano. Global impact of HPV vaccination. [abstract]. In: Proceedings of the Twelfth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2013 Oct 27-30; National Harbor, MD. Philadelphia (PA): AACR; Can Prev Res 2013;6(11 Suppl): Abstract nr FO01-01.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.253 | 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 teacher head, 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".