{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T21:26:25Z","timestamp":1791926785341,"version":"4.3.4"},"reference-count":54,"publisher":"American Medical Association (AMA)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Oncol"],"published-print":{"date-parts":[[2026,5,1]]},"abstract":"\n Importance<\/jats:title>\n Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer deaths in the US. Although early detection improves survival, the rarity of the disease has rendered population screening a difficult approach.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n \n To develop and validate a parsimonious, interpretable, and generalizable model predicting incident PDAC\u2014termed\n PRIME<\/jats:italic>\n (PDAC Risk Model for Earlier Detection)\u2014using routinely available electronic health record (EHR) data.\n <\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This cohort study used the Optum Labs Data Warehouse, a longitudinal, deidentified US EHR and claims database. Adults 40 years or older with an outpatient clinical encounter between 2016 and 2018 were included. Participants from 23 health systems (n\u2009=\u20094\u202f859\u202f833) comprised the training cohort; 31 additional systems (n\u2009=\u20095\u202f619\u202f091) served as validation. International validation was conducted in the UK Biobank (n\u2009=\u2009498\u202f754). Data analysis occurred July 2025 to January 2026.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Demographics, diagnosis codes, and routinely measured laboratory values were evaluated. Elastic-net regularization with 10-fold cross-validation selected the predictor set.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n \n Incident PDAC was identified by\n International Classification of Diseases, Ninth and Tenth Revisions (ICD-9\/10)<\/jats:italic>\n codes. Model performance was assessed using time-dependent area under the curve (AUC) and calibration metrics.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Overall, the study included more than 11 million adults (2.1% Asian individuals, 8.4% Black individuals, 4.3% Hispanic\/Latino individuals, 82.7% White individuals, and 2.4% other race\/ethnicity by EHR reporting). In the training cohort (mean [SD] age, 60.4 [11] years), 14\u202f405 individuals were diagnosed with PDAC (incidence 55 per 100\u202f000 person-years) over a mean (SD) of 5.4 (2.5) years; in the validation cohort, 11\u202f693 individuals were diagnosed with PDAC (54 per 100\u202f000 person-years) over a mean (SD) of 3.9 (2.5) years. PRIME retained 19 predictors including history of pancreatitis, gastrointestinal disorders, prior cancers, type 2 diabetes, elevated aspartate aminotransferase levels, smoking, non\u2013type-O blood, and male sex. Discrimination was strong at the 36-month time horizon (AUC\u2009=\u20090.75 in both the training and validation cohorts) with good calibration. In the validation cohort, patients in the top 1% of predicted risk had substantially higher PDAC risk (HR, 7.63; 95% CI, 6.85-8.49) compared with average-risk patients. In the UK Biobank, PRIME achieved a 36-month AUC of 0.71 with good calibration.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this validation cohort study, PRIME was a transparent EHR-based model that effectively stratified PDAC risk across diverse US health systems and generalized internationally. Prospective studies should evaluate for EHR-guided PDAC case-finding and integration with blood-based early-detection assays.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamaoncol.2026.0372","type":"journal-article","created":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:30:28Z","timestamp":1774539028000},"page":"497","source":"Crossref","is-referenced-by-count":6,"title":["Development and Validation of a Parsimonious Risk Stratification Model for Pancreatic Cancer"],"prefix":"10.1001","volume":"12","author":[{"given":"Lucas A.","family":"Mavromatis","sequence":"first","affiliation":[{"name":"Division of Precision Medicine, Department of Medicine, New York University Grossman School of Medicine, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Viktor","family":"Zlatanic","sequence":"additional","affiliation":[{"name":"Division of Gastroenterology and Hepatology, Department of Medicine, New York University Grossman School of Medicine, New 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