Bias Due to Correlation Between Times-at-Risk for Infection in Epidemiologic Studies Measuring Biological Interactions Between Sexually Transmitted Infections: A Case Study Using Human Papillomavirus Type Interactions

Abstract

The clustering of human papillomavirus (HPV) infections in some individuals is often interpreted as the result of common risk factors rather than biological interactions between different types of HPV. The intraindividual correlation between times-at-risk for all HPV infections is not generally considered in the analysis of epidemiologic studies. We used a deterministic transmission model to simulate cross-sectional and prospective epidemiologic studies measuring associations between 2 HPV types. When we assumed no interactions, the model predicted that studies would estimate odds ratios and incidence rate ratios greater than 1 between HPV types even after complete adjustment for sexual behavior. We demonstrated that this residual association is due to correlation between the times-at-risk for different HPV types, where individuals become concurrently at risk for all of their partners' HPV types when they enter a partnership and are not at risk when they are single. This correlation can be controlled in prospective studies by restricting analyses to susceptible individuals with an infected sexual partner. The bias in the measured associations was largest in low-sexual-activity populations, cross-sectional studies, and studies which evaluated infection with a first HPV type as the exposure. These results suggest that current epidemiologic evidence does not preclude the existence of competitive biological interactions between HPV types.

Evidence of synergistic relationships between HIV and Human Papillomavirus (HPV): systematic reviews and meta‐analyses of longitudinal studies of HPV acquisition and clearance by HIV status, and of HIV acquisition by HPV status

“…Furthermore, we found some evidence in review 2 that adjustment for key confounding variables including sexual behaviour actually strengthened the associations. That said, even with adjusted estimates the presence of residual confounding cannot totally be excluded, especially by partner and/or partnership characteristics (influencing the likelihood of exposure to HPV and HIV) or previous HPV infections (which may protect or predispose to HPV infection) .…”

“…There were some indications from the few studies available that HPV acquisition and persistence increased as CD4 level declined (review 1). There was also some evidence of a dose-response between number of HPV types and HIV acquisition risk (review 2), which may reflect increased biological HIV susceptibility with increasing number of HPV infections, though could also be a marker of shared risk behaviour [71] or some immunological susceptibility.…”

“…Furthermore, we found some evidence in review 2 that adjustment for key confounding variables including sexual behaviour actually strengthened the associations. That said, even with adjusted estimates the presence of residual confounding cannot totally be excluded, especially by partner and/or partnership characteristics (influencing the likelihood of exposure to HPV and HIV) or previous HPV infections (which may protect or predispose to HPV infection) [71]. Conversely, mathematical modelling to assess potential biases in STI and HIV interaction estimates for different study designs has suggested that whilst statistical adjustment can help reduce overestimation due to confounding, the magnitude of association could also be underestimated in the presence of misclassification of exposure [78,79].…”

“…The interactions between HIV and HPV could be analogous to the interactions between HIV and HSV-2 in terms of some similarity of biological mechanisms. In future, better evidence of these interactions could be obtained from discordant couple studies and/or studies with more frequent STI and HIV testing, using the best HIV tests with the shortest window period, and by adequately measuring potential sexual risk factors among participants and their partners [71].…”

Evaluation of HPV type‐replacement in unvaccinated and vaccinated adolescent females—Post‐hoc analysis of a community‐randomized clinical trial (II)

“…26,27 Thus, we used it but only as a sensitivity analysis to achieve more insight into a priori hypothesized prevalence rate ratio differences. Furthermore, clustering of multiple HPV infections is one of the most sensitive ways of looking for changes in the population biology of HPV types although subject to bias based on behavioral differences (risk-taking factors) and possible correlation of the occurrence of HPV types.…”