We determined whether a large, multi-analyte panel of circulating biomarkers can improve detection of early-stage pancreatic ductal adenocarcinoma (PDAC). We defined a biologically relevant subspace of blood analytes based on previous identification in premalignant lesions or early-stage PDAC and evaluated each in pilot studies. The 31 analytes that met minimum diagnostic accuracy were measured in serum of 837 subjects (461 healthy, 194 benign pancreatic disease, 182 early stage PDAC). We used machine learning to develop classification algorithms using the relationship between subjects based on their changes across the predictors. Model performance was subsequently evaluated in an independent validation data set from 186 additional subjects.

Last modified

• 12/04/2023

Creator

• Firpo, Matthew A.

Subject

• medicine

Language

• English

Keyword

• serum
• pancreatic cancer
• PDAC
• ELISA
• early stage
• bio marker

Date created

• 2005-01-01-2019-01-31

Location

• Salt Lake City, Utah, United States

Related url

•  https://doi.org/10.1101/2022.03.03.22271867

Resource type

• Dataset

Source

• MeSH

License

• CC BY NC - Allows others to use and share your data non-commercially and with attribution.