Development of a multimarker assay for early detection of ovarian cancer.

Published

Journal Article

PURPOSE: Early detection of ovarian cancer has great promise to improve clinical outcome. PATIENTS AND METHODS: Ninety-six serum biomarkers were analyzed in sera from healthy women and from patients with ovarian cancer, benign pelvic tumors, and breast, colorectal, and lung cancers, using multiplex xMAP bead-based immunoassays. A Metropolis algorithm with Monte Carlo simulation (MMC) was used for analysis of the data. RESULTS: A training set, including sera from 139 patients with early-stage ovarian cancer, 149 patients with late-stage ovarian cancer, and 1,102 healthy women, was analyzed with MMC algorithm and cross validation to identify an optimal biomarker panel discriminating early-stage cancer from healthy controls. The four-biomarker panel providing the highest diagnostic power of 86% sensitivity (SN) for early-stage and 93% SN for late-stage ovarian cancer at 98% specificity (SP) was comprised of CA-125, HE4, CEA, and VCAM-1. This model was applied to an independent blinded validation set consisting of sera from 44 patients with early-stage ovarian cancer, 124 patients with late-stage ovarian cancer, and 929 healthy women, providing unbiased estimates of 86% SN for stage I and II and 95% SN for stage III and IV disease at 98% SP. This panel was selective for ovarian cancer showing SN of 33% for benign pelvic disease, SN of 6% for breast cancer, SN of 0% for colorectal cancer, and SN of 36% for lung cancer. CONCLUSION: A panel of CA-125, HE4, CEA, and VCAM-1, after additional validation, could serve as an initial stage in a screening strategy for epithelial ovarian cancer.

Full Text

Duke Authors

Cited Authors

  • Yurkovetsky, Z; Skates, S; Lomakin, A; Nolen, B; Pulsipher, T; Modugno, F; Marks, J; Godwin, A; Gorelik, E; Jacobs, I; Menon, U; Lu, K; Badgwell, D; Bast, RC; Lokshin, AE

Published Date

  • May 1, 2010

Published In

Volume / Issue

  • 28 / 13

Start / End Page

  • 2159 - 2166

PubMed ID

  • 20368574

Pubmed Central ID

  • 20368574

Electronic International Standard Serial Number (EISSN)

  • 1527-7755

Digital Object Identifier (DOI)

  • 10.1200/JCO.2008.19.2484

Language

  • eng

Conference Location

  • United States