Meta-analysis of Human Papillomavirus Infection Concordance
Open Access
- 1 November 2010
- journal article
- research article
- Published by American Association for Cancer Research (AACR) in Cancer Epidemiology, Biomarkers & Prevention
- Vol. 19 (11) , 2916-2931
- https://doi.org/10.1158/1055-9965.epi-10-0576
Abstract
Background: Estimates of human papillomavirus (HPV) concordance among sexual partners are important for various public health activities, from counseling individual patients to predicting the effect of HPV vaccination. Methods: We systematically searched the PubMed and EMBASE databases for studies of HPV concordance among heterosexual couples published through 2008 in English. Two coders independently abstracted data using standardized forms. We integrated concordance data using random-effects meta-analysis. Results: Thirty studies (33 study populations) that met inclusion criteria reported concordance data for 2,972 couples. Most studies were cross-sectional cohort studies conducted in Europe or Asia that used DNA hybridization to test for HPV, sometimes in conjunction with PCR. Overall, 25.5% (95% confidence interval, 17.2-36.1%) of couples were infected with 1 or more of the same HPV types. Among couples with both members HPV-positive, 63.2% (95% confidence interval, 49.1-75.3%) were infected with 1 or more of the same viral types. Positive concordance was higher for female partners of men with HPV infections than for male partners of women with HPV infections. Positive concordance was also higher for studies using PCR and for the few studies that recruited men with HPV-related disease. Conclusions: Sexual partners of HPV-infected individuals had high rates of HPV infection, suggesting a need for increased attention to this group. Impact: Our refined estimates of HPV concordance can inform clinical encounters and public health planning. Future HPV concordance studies should use more rigorous research designs, characterize their participants in greater detail, and study more meaningful populations. Cancer Epidemiol Biomarkers Prev; 19(11); 2916–31. ©2010 AACR.Keywords
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