Automated Risk Stratification, AI-Augmented Imaging, and Biobanking for Early Detection of Sporadic Pancreatic Cancer in High-Risk Adults

What this Trial Is About

Researchers are evaluating a new screening program to improve early detection of sporadic pancreatic cancer in adults aged 50 to 85 who have a high risk due to new-onset diabetes defined by blood sugar levels and an Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) score of 3 or higher. Pancreatic cancer is a deadly disease that often shows no symptoms until it progresses rapidly, and current guidelines lack clear screening pathways for these high-risk individuals. The study involves three groups: one group receives contrast-enhanced abdominal CT scans combined with blood sample collections and electronic medical record (EMR) surveillance; a second group undergoes blood sample collection and EMR surveillance; and a third group is monitored only through EMR surveillance for up to 36 months. The CT scans use artificial intelligence (AI) to help detect cancer earlier than traditional methods. Blood samples are studied to better understand why high-risk individuals develop pancreatic cancer. Participants will undergo these procedures at baseline, 6 months, and 12 months if no safety issues occur. Researchers will track recruitment, adherence to imaging and blood collections, and completeness of EMR follow-up over up to 3 years. They will also monitor the time from diabetes onset to pancreatic cancer diagnosis, the stage of diagnosed cancers, incidental findings from scans, and comparisons between AI and radiologist imaging interpretations. The total participation includes active monitoring and follow-up for up to 3 years to assess feasibility and early detection effectiveness.

A Screening Program to Improve the Early Detection of Sporadic Pancreatic Cancer in Individuals With a High-Risk of Developing Pancreatic Cancer