Diagnosis of epithelial ovarian cancer using a combined protein biomarker panel.

ABSTRACT:

Background

An early detection tool for EOC was constructed from analysis of biomarker expression data from serum collected during the UKCTOCS.

Methods

This study included 49 EOC cases (19 Type I and 30 Type II) and 31 controls, representing 482 serial samples spanning seven years pre-diagnosis. A logit model was trained by analysis of dysregulation of expression data of four putative biomarkers, (CA125, phosphatidylcholine-sterol acyltransferase, vitamin K-dependent protein Z and C-reactive protein); by scoring the specificity associated with dysregulation from the baseline expression for each individual.

Results

The model is discriminatory, passes k-fold and leave-one-out cross-validations and was further validated in a Type I EOC set. Samples were analysed as a simu

SUBMITTER: Russell MR 

PROVIDER: S-EPMC6738042 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature