Plenary Session 3
| Friday, July 18, 2025 |
| 1:00 PM - 2:00 PM |
| Grand Ballroom |
Overview
Accelerating Discovery: Modernizing Epidemiologic Cohorts for Impact
Details
The Cancer Prevention Study-3 is a large nationwide prospective cohort study conducted by the American Cancer Society. Enrollment of approximately 300,000 cancer-free participants between the ages of 30
and 65 years took place between 2006 and 2013 across the United States at various community sites. Participants signed an informed consent, completed a lifestyle and health history survey, and provided a
small blood sample. While participants are minimally followed with triennial surveys and routine linkages for cancer and mortality outcomes, several innovative enhancements have taken place in this study.
This presentation will highlight strategies to advance data and study management through technology, use of AI to expand clinical data collection, collection of various biologic specimens, and novel types of
data collection through remote engagement with study participants. With these new tools, prospective epidemiologic cohorts have the potential to have a broader impact in scientific discovery.
Speaker
Dr. Alpa Patel
Senior Vice President, Population Science
American Cancer Society
Accelerating Discovery: Modernizing Epidemiologic Cohorts for Impact
Abstract
The Cancer Prevention Study-3 is a large nationwide prospective cohort study conducted by the American Cancer Society. Enrollment of approximately 300,000 cancer-free participants between the ages of 30 and 65 years took place between 2006 and 2013 across the United States at various community sites. Participants signed an informed consent, completed a lifestyle and health history survey, and provided a small blood sample. While participants are minimally followed with triennial surveys and routine linkages for cancer and mortality outcomes, several innovative enhancements have taken place in this study. This presentation will highlight strategies to advance data and study management through technology, use of AI to expand clinical data collection, collection of various biologic specimens, and novel types of data collection through remote engagement with study participants. With these new tools, prospective epidemiologic cohorts have the potential to have a broader impact in scientific discovery.
