Title: HE4 and CA125 as a diagnostic test in ovarian cancer : prospective validation of the risk of ovarian malignancy algorithm
Authors: Van Gorp, T ×
Cadron, I
Despierre, E
Daemen, Anneleen
Leunen, K
Amant, Frédéric
Timmerman, Dirk
De Moor, Bart
Vergote, Ignace #
Issue Date: Mar-2011
Publisher: Harcourt Publishers
Series Title: British Journal of Cancer vol:104 issue:5 pages:863-870
Abstract: Background:Recently, a Risk of Ovarian Malignancy Algorithm (ROMA) utilising human epididymis secretory protein 4 (HE4) and CA125 successfully classified patients as presenting a high or low risk for epithelial ovarian cancer (EOC). We validated this algorithm in an independent prospective study.Methods:Women with a pelvic mass, who were scheduled to have surgery, were enrolled in a prospective study. Preoperative serum levels of HE4 and CA125 were measured in 389 patients. The performance of each of the markers, as well as that of ROMA, was analysed.Results:When all malignant tumours were included, ROMA (receiver operator characteristic (ROC)-area under curve (AUC)=0.898) and HE4 (ROC-AUC)=0.857) did not perform significantly better than CA125 alone (ROC-AUC=0.877). Using a cutoff for ROMA of 12.5% for pre-menopausal patients, the test had a sensitivity of 67.5% and a specificity of 87.9%. With a cutoff of 14.4% for post-menopausal patients, the test had a sensitivity of 90.8% and a specificity of 66.3%. For EOC vs benign disease, the ROC-AUC of ROMA increased to 0.913 and for invasive EOC vs benign disease to 0.957.Conclusion:This independent validation study demonstrated similar performance indices to those recently published. However, in this study, HE4 and ROMA did not increase the detection of malignant disease compared with CA125 alone. Although the initial reports were promising, measurement of HE4 serum levels does not contribute to the diagnosis of ovarian cancer.
ISSN: 0007-0920
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Gynaecological Oncology
Basic Research in Gynaecology Section (-)
Screening, Diagnostics and Biomarkers (-)
× corresponding author
# (joint) last author

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