Epidemiology and Biostatistics Publications
Canadian Oncogenic Human Papillomavirus Cervical Infection Prevalence: Systematic Review and Meta-analysis
BMC Infectious Diseases
URL with Digital Object Identifier
BACKGROUND: Oncogenic human papillomavirus (HPV) infection prevalence is required to determine optimal vaccination strategies. We systematically reviewed the prevalence of oncogenic cervical HPV infection among Canadian females prior to immunization.
METHODS: We included studies reporting DNA-confirmed oncogenic HPV prevalence estimates among Canadian females identified through searching electronic databases (e.g., MEDLINE) and public health websites. Two independent reviewers screened literature results, abstracted data and appraised study quality. Prevalence estimates were meta-analyzed among routine screening populations, HPV-positive, and by cytology/histology results.
RESULTS: Thirty studies plus 21 companion reports were included after screening 837 citations and 120 full-text articles. Many of the studies did not address non-response bias (74%) or use a representative sampling strategy (53%).Age-specific prevalence was highest among females aged < 20 years and slowly declined with increasing age. Across all populations, the highest prevalence estimates from the meta-analyses were observed for HPV types 16 (routine screening populations, 8 studies: 8.6% [95% confidence interval 6.5-10.7%]; HPV-infected, 9 studies: 43.5% [28.7-58.2%]; confirmed cervical cancer, 3 studies: 48.8% [34.0-63.6%]) and 18 (routine screening populations, 8 studies: 3.3% [1.5-5.1%]; HPV-infected, 9 studies: 13.6% [6.1-21.1%], confirmed cervical cancer, 4 studies: 17.1% [6.4-27.9%].
CONCLUSION: Our results support vaccinating females < 20 years of age, along with targeted vaccination of some groups (e.g., under-screened populations). The highest prevalence occurred among HPV types 16 and 18, contributing a combined cervical cancer prevalence of 65.9%. Further cancer protection is expected from cross-protection of non-vaccine HPV types. Poor study quality and heterogeneity suggests that high-quality studies are needed.