{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T11:31:35Z","timestamp":1793791895183,"version":"4.6.1"},"reference-count":88,"publisher":"S. Karger AG","issue":"5","license":[{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Visc Med"],"abstract":"<jats:p>Background: Pancreatic cancer remains the fourth leading cause of cancer-related deaths in the USA despite its lower incidence, primarily due to late-stage diagnosis. While early detection could double survival rates, screening the general population is not cost-effective due to low disease prevalence and technical limitations. Summary: This review examines the relationship between diabetes and pancreatic cancer, highlighting how diabetes types differently impact cancer risk. New-onset diabetes triples pancreatic cancer risk compared to the general population, while long-standing diabetes doubles it. Several prediction models have been developed to identify high-risk individuals among new-onset diabetes patients, with recent models achieving AUCs up to 0.91. Current biomarkers like CA 19-9 show improved utility when combined with other clinical parameters, though they remain inadequate for general population screening. Cost-effectiveness analysis suggests that screening becomes viable when 3-year cancer incidence exceeds 2% and 25% of cases are detected at a localized stage. Key Messages: (1) New-onset diabetes presents a stronger risk factor for pancreatic cancer than long-standing diabetes. (2) Multiple prediction models show promise but face challenges with missing data and cross-population validation. (3) Integrated approaches combining clinical parameters, biomarkers, and machine learning offer the most promising path forward for early detection. (4) Current detection rates fall below cost-effectiveness thresholds, highlighting the need for improved screening strategies. <\/jats:p>","DOI":"10.1159\/000543479","type":"journal-article","created":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T12:01:20Z","timestamp":1736510480000},"page":"254-261","source":"Crossref","is-referenced-by-count":7,"title":["Prediction of Pancreatic Cancer Risk in Patients with New-Onset 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