Epidemiology of sexually transmitted human papillomavirus infection in young females and their sequential male partners
Bibliographic record
Abstract
Background: The etiologic role of human papillomavirus (HPV) infections in cervical cancer is well established.Secondary cervical cancer prevention requires a detailed understanding of vaginal HPV infection natural history.Characterizing HPV transmission from previous sexual relationships to subsequent sex partners may have implications for primary HPV-related cancer prevention.Objectives: Manuscript 1 examines detection and clearance rates for vaginal HPV infections among females in new heterosexual relationships.Manuscript 2 characterizes type-specific HPV positivity between sequential male partners of the same female.Methods: Genital HPV genotyping and sexual behaviour data were collected on recently-paired Montréal couples in the HPV Infection and Transmission among Couples through Heterosexual activity (HITCH) prospective cohort study.Females provided vaginal samples at 0-, 4-, 8-, 12-, 18-and 24-months, while males provided scrotal and penile samples at 0-and 4-months.Data from 501 women (aged 18-24) were analyzed in Manuscript 1; time-to-event statistics for detection and clearance of HPV infections were calculated at the woman-and HPV-levels using Kaplan-Meier analysis and rates.Data from 42 female-linked sequential partnerships (42 male 1-42 female-42 male 2) were used in Manuscript 2; 1,512 detectable HPV infections were analyzed.Observed/expected ratios for infection concordance between males 1 and 2 were calculated.Using mixed-effects regression, odds ratios (ORs) for male 2 testing positive for the same HPV type as male 1 were estimated.95% confidence intervals are provided in parentheses.Analyses were performed for any HPV type and by subgenera of the Alphapapillomavirus genus.Subgenus 1 includes low oncogenic risk HPV types, subgenus 2 high oncogenic risk types, and subgenus 3 commensal types. II Results:In Manuscript 1, by 24 months, one or more incident HPV infections were detected in 40.4% (33.4-48.4) of women.Incident subgenera 1, 2 and 3 infections cleared at comparable rates per 1000 infection-months: 43.4 (33.6-56.4),47.1 (39.9-55.5)and 46.6 (37.7-57.7),respectively.In Manuscript 2, detection of the same HPV type in males 1 and 2 occurred 2.6 (1.9-3.5)times more often than chance.The OR for male 2 positivity was 4.2 (2.5-7.0).Adjusting for the number of times the linking female partner tested positive for the same HPV type attenuated the relationship between male 1 and 2 positivity.Discussion: In Manuscript 1, HPV-level analyses did not clearly indicate that oncogenic subgenus 2 infections take longer to clear than low oncogenic-risk subgenera 1 and 3 infections.In Manuscript 2, type-specific HPV positivity in males 1 and 2 was not independent.OR estimates suggested mediation by the number of times the female tested positive; infections were likely transmitted to male 2 via the female.Conclusions: Type-specific estimates of HPV infection natural history can provide biologically informed parameters for cervical screening.HPV positivity in male 1-female partnerships predicted positivity in male 2 when the linking female partner was persistently positive.Vaccinating males may therefore prevent HPV infection in unvaccinated ordinal sexual connections.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".