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Biomarker-based early detection of epithelial ovarian cancer based on a five-protein signature in patient's plasma - a prospective trial.

Authors :
Hasenburg A
Eichkorn D
Vosshagen F
Obermayr E
Geroldinger A
Zeillinger R
Bossart M
Source :
BMC cancer [BMC Cancer] 2021 Sep 16; Vol. 21 (1), pp. 1037. Date of Electronic Publication: 2021 Sep 16.
Publication Year :
2021

Abstract

Background: Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors.<br />Methods: In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses.<br />Results: Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor.<br />Conclusions: The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort.<br />Trial Registration: Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013.<br /> (© 2021. The Author(s).)

Details

Language :
English
ISSN :
1471-2407
Volume :
21
Issue :
1
Database :
MEDLINE
Journal :
BMC cancer
Publication Type :
Academic Journal
Accession number :
34530759
Full Text :
https://doi.org/10.1186/s12885-021-08682-y