Accelerating HPV-related cancer elimination – a meeting report
Bibliographic record
Abstract
The human papillomavirus (HPV) Prevention and Control Board organized a meeting to explore effective strategies for accelerating the elimination of HPV-related cancers, starting from WHO's cervical cancer elimination campaign targets-vaccination of 90% of girls by age 15, two HPV screenings with a high-performance test for 70% of women between 35-45 years, and 90% treatment and care of women with cervical disease. Nevertheless, the global HPV vaccination coverage remains low (~ 30%), as does screening coverage, with only 24% (48/139) of programmes utilising recommended high-performance tests (such as HPV testing). The meeting explored various strategies, including the extension of vaccination for women at older ages. While vaccination of HPV-positive individuals has demonstrated safety and immunogenicity, further research is required to confirm the potential protective effects and reduced viral transmission among infected populations. Several innovative approaches were discussed, including the HPV Faster strategy, promoting combined HPV vaccination and screening for women up to age 45. This strategy aims to substantially reduce cervical cancer incidence by decreasing future screening needs among HPV-negative women and intensifying follow-up for those already HPV-positive. A variant of this approach, Sweden's "HPV EVEN Faster," simultaneously vaccinates and screens younger women (ages 23-30), aiming at significantly reducing HPV circulation and effectively reaching underserved populations. Moreover, in resource-limited settings, transitioning to single-dose vaccination emerged as a promising strategy to expand vaccine coverage, as modelled in India, Rwanda, and Brazil. Modelling data reinforced the prioritisation of increasing vaccination coverage and expanding targets in girls up to age 20 as the most efficient strategy to reduce cervical cancers. However, when increasing coverage is challenging, extending vaccination to boys could potentially enhance herd protection. Finally, the discussions underlined that successful "accelerated" HPV elimination strategies must be context-specific, taking into consideration local resources, health system capacities, and socio-economic factors. Political commitment, targeted implementation research, and innovations such as affordable new vaccines and point-of-care tests are key to speed up global progress toward HPV-related cancer elimination.
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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 | 0.001 |
| 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) | 0.001 | 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 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".