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ABSTRACT: Background
To evaluate the pattern of co-infection of human papillomavirus (HPV) types in both sexes in Sweden.Methods
Cell samples from genital swabs, first-void urine, and genital swabs immersed in first-void urine were collected in the present cross-sectional High Throughput HPV Monitoring study. Overall, 31,717 samples from women and 9,949 from men (mean age 25) were tested for 16 HPV types using mass spectrometry. Multilevel logistic regression was used to estimate the expected number of multiple infections with specific HPV types, adjusted for age, type of sample, and accounting for correlations between HPV types due to unobserved risk factors using sample-level random effects. Bonferroni correction was used to allow for multiple comparisons (120).Results
Observed-to-expected ratio for any multiple infections was slightly above unity in both sexes, but, for most 2-type combinations, there was no evidence of significant departure from expected numbers. HPV6/18 was found more often and HPV51/68 and 6/68 less often than expected. However, HPV68 tended to be generally underrepresented in co-infections, suggesting a sub-optimal performance of our testing method for this HPV type.Conclusions
We found no evidence for positive or negative clustering between HPV types included in the current prophylactic vaccines and other untargeted oncogenic types, in either sex.
SUBMITTER: Vaccarella S
PROVIDER: S-EPMC3747214 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
Vaccarella Salvatore S Söderlund-Strand Anna A Franceschi Silvia S Plummer Martyn M Dillner Joakim J
PloS one 20130819 8
<h4>Background</h4>To evaluate the pattern of co-infection of human papillomavirus (HPV) types in both sexes in Sweden.<h4>Methods</h4>Cell samples from genital swabs, first-void urine, and genital swabs immersed in first-void urine were collected in the present cross-sectional High Throughput HPV Monitoring study. Overall, 31,717 samples from women and 9,949 from men (mean age 25) were tested for 16 HPV types using mass spectrometry. Multilevel logistic regression was used to estimate the expec ...[more]