Prevalence and risk factors for HPV seropositivity and anogenital DNA positivity among men who have sex with men: a repeated cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: This study aimed to assess associations of potential risk factors with human papillomavirus (HPV) seropositivity among men who have sex with men (MSM) and compare these to risk factors for anal and penile (HPV) deoxyribonucleic acid (DNA)-positivity in the same study population. METHODS: Seropositivity and anal and penile HPV DNA-positivity were determined for seven high-risk HPV genotypes for MSM aged 16-24 years participating in Papillomavirus Surveillance among STI clinic Youngsters in the Netherlands (PASSYON) 2009-2021. Logistic regression models were conducted to assess risk factors for seropositivity, anal and penile HPV DNA-positivity. RESULTS: Overall, 1019 MSM were included. HPV-16 and -18 were most common for serology, and anal and penile HPV DNA-positivity. Although no clear similarities were observed for most risk factors for HPV seropositivity and anal or penile DNA positivity, receptive anal intercourse (RAI) was the strongest associated risk factor for both seropositivity ('RAI ever' adjusted odds ratio [aOR] 3.50, 95% confidence interval [CI] 1.56-7.88; 'RAI previous 6 months' aOR 2.17, 95% CI 1.44-3.26) and anal DNA-positivity ('RAI previous 6 months' aOR 1.67, 95% CI 1.09-2.56). CONCLUSIONS: Our study is suggestive of site-specific immune response after HPV infection; RAI might lead to anal HPV infections and consequently to seroconversion. Finally, as the two genotypes that are most oncogenic and preventable by all HPV vaccines were most common, our results underline the importance of gender-neutral vaccination.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".