Chapter 18: Statistical issues in the design and analysis of studies of human papillomavirus and cervical neoplasia.
Appropriately sophisticated statistical approaches are crucial for addressing the increasingly complex set of critical questions that follow from the recognition that human papillomavirus (HPV) is a necessary causal factor for cervical cancer. Cervical cancer researchers have defined the major stages of cervical carcinogenesis, with HPV infection as the necessary cause. Focus of etiologic studies is shifting from establishing causality to determining risk factors for HPV persistence and neoplastic progression using serially collected biomarkers. Prevention-oriented epidemiology and trials of new screening strategies and vaccines will rely on surrogate endpoints because we cannot let women develop cancer when it can be prevented. Future epidemiologic and prevention studies of HPV infection and cervical carcinogenesis will exploit subtle pathologic distinctions and will employ improved measurements of complex molecular biologic phenomena. The anticipated statistical issues are highlighted in this discussion.
Wacholder
Sholom
S
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health/DHHS, EPS 8046, Bethesda, MD 20892-7244, USA. wacholder@nih.gov
D016022:Case-Control Studies; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D015340:Epidemiologic Research Design; D005260:Female; D006801:Humans; D008403:Mass Screening; D015588:Observer Variation; D027383:Papillomaviridae; D030361:Papillomavirus Infections / Q000150:complications*; D015203:Reproducibility of Results; D014412:Tumor Virus Infections / Q000150:complications*; D002583:Uterine Cervical Neoplasms / Q000821:virology*; D002578:Uterine Cervical Dysplasia / Q000821:virology