Evaluation of the natural history of cancer of the cervix, implications for prevention. The Cancer Risk Management Model (CRMM) – Human papillomavirus and cervical components. (June 2015) - Miller, Anthony B.; Gribble, Steve; Nadeau, Claude; Asakawa, Keiko; Flanagan, William M.; Wolfson, Michael; Coldman, Andrew; Evans, William K.; Fitzgerald, Natalie; Lockwood, Gina; Popadiuk, Cathy
Highlights: Effects of modeling HPV infection. Implications of varying rates of vaccination penetrance. Vaccination policies for girls or girls and boys. Abstract: The Cancer Risk Management Model (CRMM) initiative of the Canadian Partnership Against Cancer offers policy makers a tool for making decisions regarding prevention and screening for their particular landscape. The cervical cancer component of CRMM is complex because the development of cervical cancer depends on HPV infection and has to take account of the fact that individuals must come in contact with one another for HPV to spread. Two tightly coupled models were built, one for the infectious spread of HPV (CRMM-HPV), and the other for the pathway from infection to disease onset, progression, screening, treatment, and mortality (CRMM-Cervical). This paper provides an overview of methods and functionality for CRMM components which simulate vaccination, screening, HPV incidence, disease progression, and cancer incidence. CRMM-HPV is a continuous-time, interacting-agent, Monte-Carlo microsimulation model that simulates sexual networks and HPV transmission. Six HPV groups (6, 11, 16, 18, other non-carcinogenic, other carcinogenic) and two vaccination types (bivalent, quadrivalent) were modeled. Input parameters include demography, sexual debut, partnership formation/separation and virus transmission, clearance, natural immunity. CRMM-HPV provides a 100-year projection of impacts of vaccinations on HPV infections. Results were scaled to reflect the Canadian population aged 10+ in 2011. Various vaccination scenarios can be compared by altering vaccination program design (target age, sex, program years, participation rate, vaccine type), vaccine efficacy, duration of protection and previous vaccination status. These parameters enable users to explore impacts of various scenarios such as targeting various age groups, adding boys, and booster and catch-up programs.