Estimating HPV DNA Deposition Between Sexual Partners Using HPV Concordance, Y Chromosome DNA Detection, and Self-reported Sexual Behaviors
Bibliographic record
Abstract
Background: Detection of human papillomavirus (HPV) DNA in genital samples may not always represent true infections but may be depositions from infected sexual partners. We examined whether sexual risk factors and a biomarker (Y chromosome DNA) were associated with genital HPV partner concordance and estimated the fraction of HPV detections potentially attributable to partner deposition. Methods: The HITCH study enrolled young women attending a university or college in Montréal, Canada, and their male partners, from 2005 to 2010. We tested baseline genital samples for Y chromosome DNA and HPV DNA using polymerase chain reaction. Results: Type-specific HPV concordance was 42.4% in partnerships where at least one partner was HPV DNA positive. Y chromosome DNA predicted type-specific HPV concordance in univariate analyses, but in multivariable models the independent predictors of concordance were days since last vaginal sex (26.5% higher concordance 0-1 vs 8-14 days after last vaginal sex) and condom use (22.6% higher concordance in never vs always users). We estimated that 14.1% (95% confidence interval [CI], 6.3-21.9%) of HPV DNA detections in genital samples were attributable to vaginal sex in the past week. Conclusions: A substantial proportion of HPV DNA detections may be depositions due to recent unprotected vaginal sex.
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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 | 0.003 | 0.012 |
| 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 | 0.001 | 0.001 |
| 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 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".