Modeling Effective Health Policies for Colorectal Cancer
Principal Investigator: Ann Zauber, PhD
Institution: Sloan-Kettering Institute for Cancer Research
Co-PIs:
| Marjolein Van Ballegooijen, MD, PhD | Erasmus MC |
| Karen Kuntz, DSc | University of Minnesota- School of Public Health |
| Carolyn Rutter, PhD | Group Health Research Institute |
Grant Number: 1U01CA152959-01
Abstract:Colorectal cancer (CRC) is still the second most common cause of cancer death in the United States, despite the availability of a range of interventions to reduce the burden of CRC. Microsimulation modeling can inform policy makers in prioritizing among these cancer-control interventions.
The CISNET-CRC team includes three collaborative modeling groups, each with a state-of-the-art, population-based microsimulation model for CRC: MISCAN, SimCRC, and CRC-SPIN. These three modeling groups have collaborated for eight years and have delivered a substantial body of policy-oriented work. We propose to continue this collaboration, further developing our models and using them to identify optimal cancer-control policies and practices to reduce the burden of CRC.
Our proposed work centers around three specific aims. In Aim 1 we extend our models to reflect the evolving understanding of the CRC disease processes and to incorporate new and updated screening modalities, allowing us to address new policy questions. Here we focus on new data on genomics, biomarkers, pathways, and the upcoming data from randomized controlled trials of flexible sigmoidoscopy screening. In Aim 2 we apply our updated models to inform health policy, including evaluation of interventions across the cancer-control spectrum. New technologies and more individually tailored screening and treatment strategies will be evaluated with a special focus on health disparities. In Aim 3 we disseminate results from our models to inform health policy, via methods that engage policy makers and encourage appropriate use of modeling in policy making and decision support. Here we envision innovation using open-access web-based model applications.
We will begin with model extensions required for specific applications, with the balance of the work shifting heavily toward applications over the course of the funding period. Dissemination of our findings will occur throughout the funding period.
