ROLE OF HUMAN PAPILLOMAVIRUS IN CERVICAL NEOPLASIA

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The purpose of this case control study is to investigate the role Human Papillomavirus (HPV) DNA types 6, 11, 16, 18, and 31 play in the development of cervical intraepithelial neoplasia (CIN) levels II and III, controlling for known and suspected risk factors, HPV DNA types 16, 18, and 31 have been found to be associated with CIN II and III, while HPV DNA types 6 and 11 are found more frequently in CIN I. This research project hypothesizes that women with CIN II and III are more likely to have HPV DNA types 16, 18, and 31 compared to women with normal cervical smears. Since HPV usually requires an associated carcinogenic agent for malignant transformation in animal tumor models, the role of past genital herpes infection, smoking, and hormonal contraceptives will be evaluated as possible co-carcinogens. The North Carolina Memorial Hospital (NCMH) Neoplasia Clinic will serve as the source of 100 incident cases of CIN II and III as classified by the NCMH cytology laboratory. Biopsy confirmation of CIN II or III will also be a requirement for case status. 200 NCMH Family Medicine Clinic patients receiving routine Pap smears, classified as normal by the NCMH cytology laboratory, will serve as the controls. An additional cervical scraping will be taken from each case and control for HPV DNA typing. All cases and controls will be interviewed by telephone to collect information on potential confounders including: age, race, education, age at first intercourse, number of sexual partners, tobacco use, history of sexually transmitted diseases, and contraceptive methods used. Stratified analysis and unconditional logistic regression will be used to investigate the relationship between HPV DNA types and cervical neoplasia status, while controlling for risk factors. The possibility of interactions between HPV DNA types and the hypothesized co-carcinogenic agents (past genital herpes infection, smoking status, and hormonal contraceptives used) will be evaluated using unconditional logistic regression.