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Statistical Methods in Medical Research
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Evaluating the role of human papillomavirus vaccine in cervical cancer prevention

Minhee Kang

Department of Biostatistics, Harvard University School of Public Health, Boston, MA, USA, mkang{at}hsph.harvard.edu

Stephen W Lagakos

Department of Biostatistics, Harvard University School of Public Health, Boston, MA, USA

Persistent genital infection with human papillomavirus (HPV) is a natural candidate as a surrogate marker for cervical cancer because of the strong epidemiologic and molecular evidence that HPV infection is the causative agent for almost all cervical cancers. However, while infection with high-risk types of HPV appears to be necessary for the development of cervical cancer, most infections are controlled by host immune response and do not lead to cancer in the vast majority of infected women. Because diagnostic tests cannot distinguish a persistent infection in the pathogenesis of cervical cancer from a transient infection, it is difficult to describe the disease mechanism as a progressive process based on observations. Therefore, the disease pathogenesis pathway does not fit into the usual surrogate marker framework, raising practical concerns about using HPV infection as a surrogate for a clinical endpoint in vaccine trials. In this paper, we describe the challenges in defining HPV infection as a surrogate endpoint in a HPV vaccine trial that is aimed at reducing cervical cancer rates and examine potential effects of the vaccine. We then outline some issues in the design and analysis of HPV vaccine trials, including the use of operationally defined HPV infection events meant to capture persistent infections. We conclude with a recommendation for a multi-state model that uses HPV infection to help explain the mechanisms of vaccine action rather than validate it as an endpoint substitute.

Statistical Methods in Medical Research, Vol. 13, No. 2, 139-155 (2004)
DOI: 10.1191/0962280204sm358ra


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