Validation of the Enriching New-Onset Diabetes for Pancreatic Cancer Model in a Diverse and Integrated Healthcare Setting

Background: The risk of pancreatic cancer is elevated among people with new-onset diabetes (NOD). Based on Rochester Epidemiology Project Data, the Enriching New-Onset Diabetes for Pancreatic Cancer (END-PAC) model was developed and validated. Aims: We validated the END-PAC model in a cohort of patients with NOD using retrospectively collected data from a large integrated health maintenance organization. Methods: A retrospective cohort of patients between 50 and 84 years of age meeting the criteria for NOD in 2010–2014 was identified. Each patient was assigned a risk score (< 1: low risk; 1–2: intermediate risk; ≥ 3: high risk) based on the values of the predictors specified in the END-PAC model. Patients who developed pancreatic ductal adenocarcinoma (PDAC) within 3 years were identified using the Cancer Registry and California State Death files. Area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were estimated. Results: Out of the 13,947 NOD patients who were assigned a risk score, 99 developed PDAC in 3 years (0.7%). Of the 3038 patients who had a high risk, 62 (2.0%) developed PDAC in 3 years. The risk increased to 3.0% in white patients with a high risk. The AUC was 0.75. At the 3+ threshold, the sensitivity, specificity, PPV, and NPV were 62.6%, 78.5%, 2.0%, and 99.7%, respectively. Conclusions: It is critical that prediction models are validated before they are implemented in various populations and clinical settings. More efforts are needed to develop screening strategies most appropriate for patients with NOD in real-world settings.