Abstract A28: Risk model for clinical management of HPV-infected women

Background: The natural history of human papillomavirus (HPV) and the steps leading to cervical cancer are well-known; the steps include infection with one of the 13 carcinogenic HPV genotypes, viral persistence, progression to precancer, and invasion. Cervical screening programs target treatable cervical precancer to prevent cancer mortality and morbidity. HPV infections are very common and only those causing precancer pose a risk of cancer. In addition to HPV genotype, multiple established co-factors can be combined to predict with unparalleled accuracy and precision the broad range of risks for the critical transition from common HPV infection to uncommon cervical precancer. Thus, there are three types of factors predicting risk of precancer: viral (e.g., HPV genotype and viral load), host (e.g., age, race/ethnicity) and behavioral (e.g., oral contraceptive use, smoking, BMI, co-infection with other sexually transmitted agents). We are building a risk prediction model for clinical use that reflects the determinants of HPV natural history. The absolute-risk based model will consider the three possible HPV outcomes: HPV progression, else HPV “clearance” (immune suppression) signifying low risk of subsequent precancer from that infection, else persistence of HPV infection without either progression or clearance (i.e., still unresolved outcome). To estimate these competing risks for all the factors, cofactors and their combinations requires very large cohorts of HPV-infected women. Methods: Our analysis makes use of data from a uniquely large cohort study of HPV-infected women, specifically, the 35,000 HPV-positive women, 30 years or older, from the NCI-Kaiser Permanente Northern California Persistence and Progression cohort study. The median time of follow-up is 3 years (maximum >7 years). Risk predictors already recorded include: woman's age, HPV infection status, HPV genotype, viral load, concurrent cervical cytology result, and the range of behavioral cofactors. We will present at the meeting the steps leading to the final model: 1) univariate, then multivariate, absolute risks of progression, clearance, or persistence for each HPV genotype; 2) the same risks accounting for time to event and loss-to-followup; and 3) the novel statistic mean risk stratification (MRS), which measures how well the model predicts the crucial dichotomous outcome (progression vs. not). MRS identifies which combination of variables, by virtue of frequency of positive results a