The increasing number of cervical cancer models that have been developed and published signals a “demand” for model-based policy analyses, comparative effectiveness analyses, and cost-effectiveness analyses. Although several review papers compare model assumptions and results post-hoc, there are limited examples of rigorous comparative modeling to try and understand how differences across models comply with the evidence and impact results.
Motivated by a strong desire to address gaps in cervical cancer control and the need for formal comparative modeling, we have assembled five independent teams of cervical cancer modelers: Harvard University (USA), University of Minnesota (USA), Erasmus Medical Center (The Netherlands), and Cancer Council New South Wales (Australia); the University of Washington (USA) focuses on key questions for HIV-positive women. Our objective is to use rigorous, comparative modeling to inform effective, efficient, and equitable policies for cervical cancer control in the United States with the following specific aims: (1) to evaluate the health benefits, harms, and costs of cervical cancer prevention strategies as currently practiced, including HPV vaccination and screening; (2) to identify the most efficient and cost-effective cervical cancer control strategies, taking into consideration new and forthcoming technologies; (3) to identify the most efficient and cost-effective cervical cancer control strategies in HIV-positive women; and (4) to leverage unique opportunities afforded by the CISNET comparative modeling approach to improve translation and validation of model-based analyses of HPV and cervical cancer control. We expect to have an impact on the analytic methods of comparative modeling; the equitable distribution and rational use of new technology; the effectiveness of interventions and strategies for cancer prevention through clinical guidelines and national policies; HPV-related cancer outcomes, including reduced incidence, enhanced quality of life, improved survival, and reduced disparities; and the financial and economic profile of delivering cancer-related health services.
For policy makers and stakeholders to be able to use model-based results in decision making, there needs to be transparency, consensus on analytic standards, some degree of harmonization across studies, and explanations of how and why results may differ. CISNET provides an unprecedented opportunity to not only fill this void in cervical cancer modeling but also address key scientific questions that move our field forward.