A case study and proposal for publishing directed acyclic graphs: The effectiveness of the quadrivalent HPV vaccine in perinatally HIV exposed girls
Background: Developing a causal graph is an important step in etiologic research planning and can be used to highlight data flaws and irreparable bias and confounding. Recent findings have suggested that the human papillomavirus (HPV) vaccine is less effective in protection against HPV associated disease in a population of girls living with HIV. Development: In order to understand the relationship between HIV status and HPV vaccine effectiveness, it is important to outline the key assumptions of the causal mechanisms before designing a study to investigate the effect of the HPV vaccine in girls living with HIV infection. Application: We present a causal graph to describe our assumptions and proposed approach to explore this relationship. We hope to obtain feedback on our assumptions prior to data analysis and exemplify the process for designing an etiologic study.Conclusion: The approach we lay out in this paper may be useful for other researchers who have an interest in using causal graphs to describe and assess assumptions in their own research prior to undergoing data collection and/or analysis.