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Meta-Analysis
. 2015 Oct 6:5:14667.
doi: 10.1038/srep14667.

Worldwide Prevalence of Human Papillomavirus and Relative Risk of Prostate Cancer: A Meta-analysis

Lin Yang  1   2 , Shuanghua Xie  1 , Xiaoshuang Feng  1 , Yuheng Chen  1 , Tongzhang Zheng  3 , Min Dai  1 , Cindy Ke Zhou  4 , Zhibin Hu  5 , Ni Li  1 , Dong Hang  5
Affiliations
Meta-Analysis

Worldwide Prevalence of Human Papillomavirus and Relative Risk of Prostate Cancer: A Meta-analysis

Lin Yang et al. Sci Rep. .

Abstract

Despite the increasing number of studies conducted recently to evaluate the association between HPV infections and the risk of prostate cancer, the results remain inconclusive. Furthermore, the prevalence and distribution of overall and individual HPV types worldwide in prostate cancer has not been reported until now. Therefore, we estimated the prevalence of HPV in prostate cancer by pooling data of 46 studies with 4919 prostate cancer cases, taking into account the heterogeneity of major related parameters, including study region, specimen type, HPV DNA source, detection method, publication calendar period and Gleason score. Moreover, we tested the association of HPV infections with prostate cancer risks by a meta-analysis of 26 tissue-based case-control studies. We found that the prevalence of HPV infection was 18.93% (95% CI = 17.84-20.05%) in prostate cancer cases, and most of which were high-risk HPV types (17.73%, 95% CI = 16.52-18.99%). The prevalence varied by region, PCR primers used, publication calendar period and Gleason score. Our study also showed a significantly increased risk of prostate cancer with the positivity of overall HPV detected in prostate tissues (OR = 1.79, 95% CI = 1.29-2.49) and revealed the geographic variation of association strength (P < 0.001). In conclusion, HPV infections may contribute to the risk of prostate cancer.

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Figures

Figure 1
Figure 1. Prevalence of Individual HPV Types in Tissues and Sera.
Figure 2
Figure 2. Odds Ratios of Prostate Cancer Cases Associated with HPV in Tissues (Cases vs. Controls), by Random-effect Model.
See this image and copyright information in PMC

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