Early Detection of Pancreatic Cancer

Abstract

The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic and other cancers remains underexplored. The Kenner Family Research Fund, in collaboration with the Cancer Biomarker Research Group at the National Cancer Institute, organized the workshop entitled: “Early Detection of Pancreatic Cancer: Opportunities and Challenges in Utilizing Electronic Health Records (EHR)” in March 2021. The workshop included a select group of panelists with expertise in pancreatic cancer, EHR data mining, and AI-based modeling. This review article reflects the findings from the workshop and assesses the feasibility of AI-based data extraction and modeling applied to EHRs. It highlights the increasing role of data sharing networks and common data models in improving the secondary use of EHR data. Current efforts using EHR data for AI-based modeling to enhance early detection of pancreatic cancer show promise. Specific challenges (biology, limited data, standards, compatibility, legal, quality, AI chasm, incentives) are identified, with mitigation strategies summarized and next steps identified.

Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers

“…One of the major areas where AI could have a significant impact is early cancer detection [ 20 , 48 , 49 ]. This was one of the most preferred applications of AI in cancer care by the respondents of this survey.…”

“…By analyzing medical images and other data, AI algorithms can help identify signs of cancer at an early stage, increasing the chances of successful treatment. For example, AI can analyze mammograms to identify breast cancer, CT scans to identify lung cancer, and polyps indicative of colorectal cancer in real-time [ 18 , 20 , 48 , 49 , 50 , 64 , 65 ]. AI can also help with early detection by analyzing a patient’s medical history [ 5 ] and test results to identify patterns that may indicate the presence of cancer [ 47 ].…”

Pancreatic cancer is associated with medication changes prior to clinical diagnosis

“…Indeed, changes in use for several medications were associated with increased two-year risk of pancreatic cancer diagnosis after accounting for other risk factors, suggesting that recent changes in health status may provide additive risk stratification information. Since few conditions are known to portend sufficiently high pancreatic cancer risk to justify imaging surveillance 2 , the identification of such further predictive features may allow construction of multi-factor models with sufficient predictive capacity for clinical utility 25 – 28 . It should be emphasized that the premise of the current study was that pancreatic cancer would cause symptoms or signs that lead to medication changes in the 1–2 years before diagnosis, rather than these medication changes were causally responsible for the development of pancreatic cancer.…”

Artificial Intelligence in Medicine and Dentistry

“…Early detection and prevention: AI can help monitor vital signs, symptoms, and other data to detect potential health problems early, especially chronic diseases, to avoid complications ( 66 ).…”