Purpose Incidental detection of pancreas lesions (IPLs) is common and creates an opportunity to intercept pancreatic ductal adenocarcinoma (PDAC). However, identifying patients at risk for progression who can benefit from surgical resection remains challenging. The current role of blood tests for risk stratification in patients with IPLs is limited. Methods We evaluated the performance of circulating glycoproteins (CA19-9, CEA and CA125), plasma DNA fragmentation analysis, and their combination, in 99 asymptomatic patients with IPLs, for detection of advanced pathology (high-grade dysplasia or invasive carcinoma). Plasma DNA fragmentation was analyzed using a machine learning model, adapted to detect PDAC in 242 patients with cancer and 300 healthy individuals. Results During 18.8 months of median follow-up by a multidisciplinary clinical team, 11 of 99 patients with IPLs were diagnosed with advanced pathology. We observed area under the receiver operating characteristic curves (AUROCs) of 0.78, 0.63, 0.54 and 0.74 using CA19-9, CEA, CA125 and plasma DNA fragmentation, respectively. Combined analysis of CA19-9, CA125 and plasma DNA fragmentation showed an AUROC of 0.93, with 91% sensitivity and 53% positive predictive value (PPV) at 90% specificity. In a subset of 25 patients with histologically confirmed diagnoses, AUROC improved to 0.96 and PPV improved to 91%. In one patient with an equivocal initial endoscopy, multi-analyte blood analysis predicted cancer 3 months before diagnosis of stage IA cancer. Conclusion Our results demonstrate a multianalyte blood test combining glycoprotein biomarkers with plasma DNA fragmentation could complement current clinical workflows for cancer detection in patients with IPLs.

M. Murtaza and B. McDonald are co-inventors on pending patent applications for methods of plasma DNA analysis evaluated in this study. M. Murtaza consults for the Translational Genomics Research Institute (TGen), a not-for-profit research institution. S. Sivakumar receives research funding from Bristol Myers Squibb and Alchemab; receives speaker fees and travel funding from AstraZeneca and Novartis; and conducts clinical trials with AstraZeneca, Novarits, Roche, Genentech, and BioNTech.

C. Marcinak is supported by grant 5 T32 HG002760 from the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) to the University of Wisconsin Madison Genomic Sciences Training Program. S. N. Zafar receives partial salary support from the Early Stage Surgeon Scientist Program Grant P30 CA014520 48S4 from the National Cancer Institute (NCI) of the NIH. M. Murtaza is supported by grants 5 U01 CA243078 and 5 R01 CA223481 from the NCI of the NIH. This work was supported by the University of Wisconsin Carbone Cancer Center Pancreas Idea Development Grant.

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