The effect of HIV infection on anal and penile human papillomavirus incidence and clearance
Bibliographic record
Abstract
OBJECTIVES: A large portion of anogenital cancers is caused by high-risk human papillomavirus (hrHPV) infections, which are especially common in HIV-infected men. We aimed to compare the incidence and clearance of anal and penile hrHPV infection between HIV-infected and HIV-negative MSM. DESIGN: Analyses of longitudinal data from a prospective cohort study. METHODS: MSM aged 18 years or older were recruited in Amsterdam, the Netherlands, and followed-up semi-annually for 24 months. At each visit, participants completed risk-factor questionnaires. Anal and penile self-samples were tested for HPV DNA using the SPF10-PCR DEIA/LiPA25 system. Effects on incidence and clearance rates were quantified via Poisson regression, using generalized estimating equations to correct for multiple hrHPV types. RESULTS: Seven hundred and fifty MSM with a median age of 40 years (interquartile 35-48) were included in the analyses, of whom 302 (40%) were HIV-infected. The incidence rates of hrHPV were significantly higher in HIV-infected compared with HIV-negative MSM [adjusted incidence rate ratio (aIRR) 1.6; 95% confidence interval (CI) 1.3-2.1 for anal and aIRR 1.4; 95%CI 1.0-2.1 for penile infection]. The clearance rate of hrHPV was significantly lower for anal [adjusted clearance rate ratio (aCRR) 0.7; 95%CI 0.6-0.9], but not for penile infection (aCRR 1.3; 95%CI 1.0-1.7). HrHPV incidence or clearance did not differ significantly by nadir CD4 cell count. CONCLUSION: Increased anal and penile hrHPV incidence rates and decreased anal hrHPV clearance rates were found in HIV-infected compared with HIV-negative MSM, after adjusting for sexual behavior. Our findings suggest an independent effect of HIV infection on anal hrHPV infections.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".