Risk of cervical HPV infection and prevalence of vaccine-type and other high-risk HPV types among sexually active teens and young women (13–26 years) enrolled in the VALHIDATE study
Bibliographic record
Abstract
HPV vaccination is expected to reduce the incidence of cervical cancer. The greatest and the earliest health gains will be ensured by high vaccine coverage among all susceptible people. The high costs and the risk of a reduced cost/effectiveness ratio in sexually active girls still represent the main obstacles for a more widespread use of HPV vaccination in many countries. Data on the rate, risk factors, and HPV types in sexually active women could provide information for the evaluation of vaccination policies extended to broader age cohorts. Sexually active women aged 13-26 years enrolled in an Italian cohort study were screened for cervical HPV infections; HPV-DNA positive samples were genotyped by InnoLipa HPV Genotyping Extra or by RFLP genotype analysis.: Among the 796 women meeting the inclusion criteria, 10.80% (95% CI 8.65-12.96) were HPV-DNA infected. Age>18 years, lifetime sexual partners>1, and history of STIs were associated to higher risk of HPV infection in the multivariable models adjusted for age, lifetime sexual partners, and time of sexual exposure. The global prevalence of the four HPV vaccine-types was 3.02% (95% CI 1.83-4.20) and the cumulative probability of infection from at least one vaccine-type was 12.82% in 26-years-old women and 0.78% in 18-years-old women.: Our data confirm most of the previously reported findings on the risk factors for HPV infections. The low prevalence of the HPV vaccine-types found may be useful for the evaluation of the cost/efficacy and the cost/effectiveness of broader immunization programs beyond the 12-years-old cohort.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".