Prevention and control of HPV and HPV-related cancers in France: the evolving landscape and the way forward – a meeting report
Bibliographic record
Abstract
Misinformation regarding HPV vaccine safety and benefits has resulted in low coverage within the eligible French population. HPV vaccination is safe and efficacious in preventing HPV infections in adolescents. However, reaching optimal coverage in countries such as France is challenging due to misinformation, among other factors. Moreover, disparities exist in cervical cancer screening programs. To support the government health promotion policy aimed at improving prevention and control of HPV-related cancers in France, the Human Papillomavirus Prevention and Control Board (HPV-PCB), in collaboration with local experts, held a meeting in Annecy, France (December 2021).HPV-PCB is an independent, multidisciplinary board of international experts that disseminates relevant information on HPV to a broad array of stakeholders and provides guidance on strategic, technical and policy issues in the implementation of HPV control programs.After a one-and-a-half-day meeting, participants concluded that multi-pronged strategies are required to expand vaccination coverage and screening. Vaccine acceptance could be improved by: 1) strenghtening existing trust in clinicians by continuous training of current and upcoming/pre-service healthcare professionals (HCPs), 2) improving health literacy among adolescents and the public through school and social media platforms, and 3) providing full reimbursement of the gender-neutral HPV vaccine, as a strong signal that this vaccination is essential.The discussions on HPV infections control focused on the need to: 1) encourage HCPs to facilitate patient data collection to support performance assessment of the national cervical cancer screening program, 2) advance the transition from cytology to HPV-based screening, 3) improve cancer prevention training and awareness for all HCPs involved in screening, including midwives, 4) identifying patient barriers to invitation acceptance, and 5) promoting urine or vaginal self-sampling screening techniques to improve acceptability, while establishing appropriate follow-up strategies for HPV-positive women. This report covers some critical findings, key challenges, and future steps to improve the status of HPV prevention and control measures in the country.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".