Epstein-Barr Virus, High-Risk Human Papillomavirus and Abnormal Cervical Cytology in a Prospective Cohort of African Female Sex Workers
Bibliographic record
Abstract
BACKGROUND: High-oncogenic-risk human papillomavirus (hrHPV) is necessary, although insufficient, to promote cervical cancer. Like HPV, Epstein-Barr virus (EBV) is a common pathogen with the capacity to promote epithelial neoplasms. We examined the association between cervical EBV, hrHPV, and cytology in female sex workers in Nairobi, Kenya. METHODS: Women (n = 332) with known cervical cytology and hrHPV mRNA results were evaluated for cervical EBV DNA by conventional polymerase chain reaction. Prevalence ratios (PRs) were calculated to assess the relationships between EBV, hrHPV, and cervical cytology. Prospective analyses used risk ratios and time-to-event analyses to determine the association of EBV with hrHPV clearance and with abnormal cytology outcomes. RESULTS: Baseline prevalence of hrHPV and EBV was 29% and 19%, respectively. Higher EBV prevalence was found among women with older age, HIV, hrHPV, abnormal cytology, Mycoplasma genitalium infection, smoking habits, younger age at sexual debut, and less frequent condom use. At baseline, women with EBV had a higher prevalence of hrHPV infection than did EBV-negative women (52% vs. 24%; HIV-adjusted PR [95% confidence interval], 1.8 [1.3-2.6]). Epstein-Barr virus-positive women had a higher prevalence than did EBV-negative women of high-grade precancer (15% vs. 2%) and abnormal cytology (37% vs. 15%), although HIV- and hrHPV-adjusted associations were not significant (high-grade precancer: PR, 2.0 [0.7-5.9]; abnormal cytology: PR, 1.4 [0.9-2.2]). In prospective analyses, a marginal association was observed between baseline EBV detection and delayed hrHPV clearance. CONCLUSIONS: Our data support a possible role for EBV as a high-risk marker or cofactor for HPV-mediated cervical cancer development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".