DESCRIPTION (provided by applicant): Several factors are changing the landscape of cervical cancer control, including a better understanding of the natural history of HPV, promising new screening approaches using HPV DNA testing, and the recent licensure of the first prophylactic HPV vaccine targeting the two most common high-risk types of HPV, 16 and 18. We propose to refine our Cervical Cancer Screening Model to be capable of assessing the costs, benefits, and cost-effectiveness of primary prevention (vaccination), secondary prevention (screening), and strategies that combine both. Our specific aims are: (1) to refine a natural history model to function as an open population- based simulation model capable of forecasting incidence, mortality, and costs associated with different cervical cancer control strategies. This model will be calibrated to the United States population using the best available data, including observed patterns in HPV type-specific prevalence, invasive cancer, and temporal variation in factors such as sexual behavior and smoking; (2) to develop a dynamic transmission model of HPV 16 and 18 to estimate the population-level impact of a type-specific vaccination taking into account biological and host factors, vaccine properties, behavioral issues, and herd immunity. We will assess the incremental benefit of vaccinating boys in addition to girls under different scenarios; compare the costs and benefits of policies restricting vaccination to young girls not yet sexually active with policies extending vaccination to women in their late 20s; explore how uncertain assumptions about sexual mixing patterns affect results; and project temporal trends in type-specific HPV prevalence; (3) to assess the cost-effectiveness of alternative cervical cancer prevention strategies for a the general U.S. population as well as for subgroups that differ in their socioeconomic, demographic, and cervical cancer risk profile. We will explore how the cost-effectiveness of a combined screening and vaccination program could change over time, evaluate the effect of vaccination on the test performance of current HPV diagnostics; and assess how vaccine delivery (target age, upper age limit, coverage by age and risk group), vaccine characteristics, and programmatic features influence projected benefits and cost-effectiveness.
CRITIQUE 1
Significance: The ultimate significance is whether or not the results of this modeling are thought significant enough to influence policy in the area of cervical cancer prevention. This group has clearly contributed to the debate using their modeling but it's not as clear what the impact has been.
Approach: The team proposes to further develop their current cervical cancer screening model. They will expand their current natural history model into an open model that will allow them to use data where subjects data may appear and disappear throughout the period of observation, and to estimate the mortality, incidence of disease, costs and benefits of various screening strategies. They propose to calibrate this model on the US population estimating known incidence rates. They discuss validating the model on independent sets of data that are not yet specified and then linking it to a new HPV 16/18 transmission model before they begin their predictions.
Innovation: The amount and complexity of the data to be incorporated into the model is innovative. The incorporation of both epidemiologic and disease transmission dynamics in a single model is an innovative approach to handling a complex modeling problem.
Investigators: The primary investigator and the team are well qualified to carry out this project. They had an initial RO1 to develop their model initially and have had 30 publications and 40 abstracts on this work. They have contributed their findings and the use of their model to several conferences on cervical cancer control and the cost effectiveness of various methods of control.
Environment: The group has been well supported in the past and the current environment provides good support to carry out the work.
Overall Evaluation: This is an experienced and productive team with a good track record, a significant solution to a significant problem and a reasonable and innovative approach. They have provided good responses to previous criticism concerning the use of datasets from different countries and how the epidemiologic and dynamic models will be linked. This resubmission is an improved version of the original grant. There are two relatively minor things which still concern this reviewer. While they have answered the question of using data from different countries in terms of the physiology of the disease being the same, a question still remains about the data in terms of differences in reporting and quality control from the different countries. In addition there is no indication of the amount of variation in parameter values and predictions among the various validations that would lead the group to think that the final model was acceptable for prediction results in the future for 6mos., 1 year, 10 years, etc. Nor is there an indication of the variability that might be expected from this model for these predictions. The experience of the group leads me to believe that these questions will be answered but this reviewer doesn't see any reference to them in this application.
Protection of Human Subjects from Research Risks: Acceptable
Inclusion of Women Plan: Acceptable
Inclusion of Minorities Plan: Acceptable
Inclusion of Children Plan: Acceptable
Budget: No changes recommended |