JOURNAL ARTICLE
META-ANALYSIS
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
SYSTEMATIC REVIEW
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HIV-positive women have higher risk of human papilloma virus infection, precancerous lesions, and cervical cancer.

AIDS 2018 March 28
OBJECTIVE: HIV-positive women have higher human papillomavirus (HPV) prevalence and cervical cancer incidence than HIV-negative women, partly because of HIV's modifying effect on HPV pathogenesis. We synthesized the literature on the impact of HIV on HPV natural history.

DESIGN: Systematic review and meta-analysis.

METHODS: We searched the literature for studies evaluating HPV acquisition and persistence or precancer progression by HIV status. Data on HPV natural history by HIV status, CD4 cell counts, viral load, and antiretroviral therapy (ART) were summarized using fixed effect models.

RESULTS: Overall, 38 of 1845 abstracts identified met inclusion criteria. HIV-positive women had higher HPV acquisition [relative risk (RRpooled) 2.64, 95% confidence interval (CI) 2.04-3.42] and lower HPV clearance (hazard ratiopooled 0.72, 95% CI 0.62-0.84) than HIV-negative women. HPV acquisition was higher with declining CD4 cell count and was lower in those virally suppressed on ART. HIV was associated with higher incidence of low-grade squamous intraepithelial lesions (LSIL; RRpooled 3.73, 95% CI 2.62-5.32) and high-grade squamous intraepithelial lesions (HSIL; hazard ratiopooled 1.32, 95% CI 1.10-1.58), largely because of increased HPV persistence. ART lowered progression from normal cytology to LSIL (hazard ratiopooled 0.65, 95% CI 0.52-0.82), but not HSIL. Cervical cancer incidence was associated with HIV positivity (RR 4.1, 95% CI 2.3-6.6), but not with ART.

CONCLUSION: HIV-positive women have higher risk of acquiring HPV, with risk inversely associated with CD4 cell count. ART lowered HPV acquisition, increased clearance, and reduced precancer progression, likely via immune reconstitution. Although some of our results are limited by small number of studies, our study can inform screening guidelines and mathematical modeling for cervical cancer prevention.

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