Development and Validation of a Parsimonious Risk Stratification Model for Pancreatic Cancer

作者：Lucas A. Mavromatis, Viktor Zlatanic, Emil Agarunov, Shenin A. Sanoba, Michael D. Kluger, Leora I. Horwitz, Narges Razavian, Anirban Maitra, Tamas A. Gonda, Morgan E. Grams · 发表于：JAMA Oncology · 年份：2026 · DOI：10.1001/jamaoncol.2026.0372 · 被引用次数：4 · 研究领域：Pancreatic and Hepatic Oncology Research、Lung Cancer Research Studies、Lung Cancer Treatments and Mutations

Importance: 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. Objective: To develop and validate a parsimonious, interpretable, and generalizable model predicting incident PDAC-termed PRIME (PDAC Risk Model for Earlier Detection)-using routinely available electronic health record (EHR) data. Design, Setting, and Participants: 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 = 4 859 833) comprised the training cohort; 31 additional systems (n = 5 619 091) served as validation. International validation was conducted in the UK Biobank (n = 498 754). Data analysis occurred July 2025 to January 2026. Exposures: Demographics, diagnosis codes, and routinely measured laboratory values were evaluated. Elastic-net regularization with 10-fold cross-validation selected the predictor set. Main Outcomes and Measures: Incident PDAC was identified by International Classification of Diseases, Ninth and Tenth Revisions (ICD-9/10) codes. Model performance was assessed using time-dependent area under the curve (AUC) and calibration metrics. Results: Overall, the study included more than 11 million adults (2.1% Asian individuals, 8.4% Blac...