AI model may predict pancreatic cancer risk up to 5 years before diagnosis

• A new study suggests that an AI model can identify people at higher risk of pancreatic cancer up to 5 years before diagnosis, using routine electronic health records and laboratory data.
• The findings show promising predictive performance, suggesting the AI model could effectively distinguish people at higher and lower risk of pancreatic cancer.
• However, further research is still necessary, and prospective testing is underway, with plans to evaluate the AI model within a healthcare system before determining whether it could play a role in routine clinical care.

Pancreatic cancer is relatively uncommon but has a disproportionately high mortality burden. In the United States, estimates suggest that approximately 67,530 people will receive a diagnosis in 2026, and 52,740 will die from the disease.

Despite pancreatic cancer accounting for roughly 3% of all new cancer cases, it is responsible for approximately 8% of cancer deaths, highlighting its particularly high mortality burden.

Pancreatic cancer can be difficult to detect, with many cases diagnosed after it has spread. An early diagnosis could be particularly beneficial, as data show a 5-year relative survival of about 44% when the cancer is still localized, compared with just 3% when it has spread to distant parts of the body.

Now, research suggests that an artificial intelligence (AI) model could identify people at increased risk of pancreatic cancer as early as 5 years before it becomes clinically apparent, using information routinely collected in electronic health records.

The findings were presented at the American College of Surgeons (ACS) Clinical Congress 2026 in Washington, D.C., by Mayo Clinic researchers. As such, it is important to note that the findings have not yet been peer-reviewed.