Prevalent and persistent oncogenic HPV types in a cohort of women living with HIV prior to HPV vaccination
Bibliographic record
Abstract
OBJECTIVE: To describe prevalent and persistent oncogenic human papillomavirus (HPV) types detected in women living with HIV (WLWH) in Canada, including women with cervical dyskaryosis, and to determine predictors of type-specific HPV persistence. METHODS: Women and girls living with HIV, recruited from 14 sites of HIV care across Canada, were included in a sub-analysis of a prospective vaccine immunogenicity cohort study (two HPV DNA results, at least one cervical cytology result pre-vaccination). Demographic and clinical data were collected alongside cervical samples for cytology and HPV DNA typing between November 25, 2008, and May 19, 2015. RESULTS: Pre-vaccination, HPV16 and HPV52 were the most prevalent oncogenic HPV types. Of the 252 women and girls who met the eligibility criteria, 45% were infected with at least one oncogenic HPV type and one-third of participants had a persistent oncogenic infection. HPV16, 45, and 52 were the most frequently persistent types. Seventeen percent of women had persistent infections with oncogenic HPV types not within currently available vaccines (HPV35/39/51/56/59/68/82). Lower CD4 count significantly predicted HPV persistence (P=0.024). Cervical cytology results were normal for 82.9% of participants, atypical squamous cells of undetermined significance for 2.4%, low-grade squamous intraepithelial lesions for 11.5%, and high-grade squamous intraepithelial lesions for 2.8%. CONCLUSION: Unvaccinated WLWH were infected with a wide range of oncogenic HPV types. The findings highlighted the importance of optimal treatment of HIV and continued cervical cancer screening as key steps toward the global elimination of cervical cancer.
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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) | 0.001 | 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".