The EVVA Cohort Study: Anal and Cervical Type-Specific Human Papillomavirus Prevalence, Persistence, and Cytologic Findings in Women Living With HIV
Bibliographic record
Abstract
Background: The risk of anal cancer due to high-risk human papillomavirus (HR-HPV) is higher in women living with human immunodeficiency virus (HIV) than in the general population. We present findings of cervical and anal HPV and cytologic tests at baseline in the EVVA cohort study and HPV persistence data 6 months after baseline. Methods: Semiannual visits included questionnaires, chart reviews, cervical/anal cytologic and cervical/anal HPV testing for 2 years. Genotyping for 36 HPV genotypes was performed using the Roche Linear Array HPV genotyping test. Results: A total of 151 women living with HIV were recruited. At baseline, 75% had anal HPV, 51% had anal HR-HPV, 50% had cervical HPV, and 29% had cervical HR-HPV. Anal HPV-16 and HPV-51 were more frequent in women born in Canada (31% and 29%, respectively, compared with ≤16% for other women). Most anal HR-HPV types detected at 6 months (57%-93%) were persistent from baseline. Findings of anal cytologic tests were abnormal for 37% of women. Conclusions: Anal HPV is highly prevalent in women living with HIV, and type distribution varies by place of birth. High-resolution anoscopy was indicated in more than one third of results. As anal cancer is potentially preventable, these important findings need to be considered when selecting the best approach for anal cancer screening programs.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".