JCO Clin Cancer Inform. 2026 Apr;10(2):e2500139. doi: 10.1200/CCI-25-00139. Epub 2026 Jun 1.
ABSTRACT
PURPOSE: Cancer registries are often asked to present cancer data for small geographic areas to inform and facilitate targeted interventions and prevention programs. However, it is challenging to compute and visualize reliable cancer estimates for areas with small case counts and populations to support cancer control planning.
METHODS: Leveraging a user-centered design process, we developed a visual analytics platform and interactive graphics to display modeled cancer risk estimates for small areas. Development of our visual analytics platform was informed by cancer registry and public health professionals through focus groups and surveys. The reliable cancer risk estimates for small areas that we displayed on this platform were created using a Bayesian hierarchical model that borrows strength from neighboring areas and over time to produce cancer estimates for small areas.
RESULTS: The Cancer Analytics and Maps for Small Areas tool (CAMSA) provided age-adjusted cancer incidence and mortality rates and risk probabilities for eight cancers at the county and ZIP-code tabulation area levels. It allowed the user to identify areas of high cancer incidence, including among subgroups defined by sex and race/ethnicity. Potential end users were enthusiastic about the opportunity to implement CAMSA within their practice, emphasizing the tool’s potential for increased collaborative opportunities at local and state levels. Suggestions for improvement included adding map overlays such as additional cancer risk variables and incorporating functionalities such as exportable data tables.
CONCLUSION: CAMSA presented cancer rate and risk estimates for small geographic areas where they may have previously been suppressed. Through our user-centered design process, we developed statistical models and data visualizations to support the needs of an array of potential end users.
PMID:42224633 | DOI:10.1200/CCI-25-00139
