Update on the new 9-valent vaccine for human papillomavirus prevention.
Bibliographic record
Abstract
OBJECTIVE: To provide family physicians with information on the efficacy, safety, public health effects, and cost-effectiveness of the 9-valent human papillomavirus (HPV) vaccine. QUALITY OF EVIDENCE: Relevant publications in PubMed up to May 2015 were reviewed and analyzed. Most evidence cited is level I (randomized controlled trials and meta-analyses) or level II (cross-sectional, case-control, and epidemiologic studies). Government reports and recommendations are also referenced. MAIN MESSAGE: The 9-valent HPV vaccine, which protects against HPV types 6, 11, 16, 18, 31, 33, 45, 52, and 58, is safe and effective and will further reduce the incidence of HPV infection, as well as HPV-related cancers. It can also indirectly protect unvaccinated individuals through herd immunity. With an effective vaccination program, most cervical cancers can be prevented. Analyses show that the cost-effectiveness of the 9-valent HPV vaccine in female patients is comparable to the original quadrivalent HPV vaccine (which protects against HPV types 6, 11, 16, and 18) currently in use. However, the usefulness of vaccinating male patients with the 9-valent HPV vaccine needs further investigation. CONCLUSION: The 9-valent HPV vaccine offers more protection against HPV than the quadrivalent HPV vaccine does and is as safe. Analysis of cost-effectiveness favours its use, at least in adolescent girls. Therefore, physicians should recommend the 9-valent HPV vaccine to patients instead of the quadrivalent 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".