A Simulation Study of Using Composite Outcomes from HPV Genotyping Assay Results to Monitor Human Papillomavirus Infections

• Activity Number: 353
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Carol Lin*+
• Companies: CDC
• Keywords: sensitivity ; specificity ; composite prevalence ; genotyping assay ; simulation ; HPV infections

Abstract

More than 120 types of HPV have been identified according to DNA genome. Researchers have classified and grouped the various HPV types by their association with a variety of clinical conditions (i.e., cervical cancer, warts), phylogenetic position, and types related to vaccines to form composite measures. Composite prevalence estimates based on various genotyping assay results have been calculated to assess the burden of HPV infections and monitoring HPV vaccine effectiveness. While prevention and intervention strategies can be made based on these prevalence estimates, research on how well these estimates measure the true underlying infection burden is limited. We perform a Monte Carlo simulation study to evaluate the composite prevalence estimates calculated based on panels of genotyping assay results in monitoring HPV infections when the true underlying infection rates change or assays with different sensitivities and specificities are used. The results suggest that when the true underlying type-specific infection rates are relatively low, composite prevalence estimates over-estimate the infection burden and could under-estimate vaccine effectiveness. In addition, the impac