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Title: Evaluation of a panel of 28 biomarkers for the non-invasive diagnosis of endometriosis
Authors: Vodolazkaia, Alexandra ×
El Aalamat, Yousef
Popovic, Dusan
Mihalyi, A
Bossuyt, Xavier
Kyama, C
Fassbender, Amelie
Bokor, A
Schols, Dominique
Huskens, Dana
Meuleman, Christel
Peeraer, Karen
Tomassetti, C
Gevaert, Olivier
Waelkens, Etienne
Kasran, Ahmad
De Moor, Bart
D'Hooghe, Thomas #
Issue Date: Sep-2012
Publisher: Published for the European Society of Human Reproduction and Embryology by IRL Press
Series Title: Human Reproduction vol:27 issue:9 pages:2698-2711
Abstract: Background At present, the only way to conclusively diagnose endometriosis is laparoscopic inspection, preferably with histological confirmation. This contributes to the delay in the diagnosis of endometriosis which is 6-11 years. So far non-invasive diagnostic approaches such as ultrasound (US), MRI or blood tests do not have sufficient diagnostic power. Our aim was to develop and validate a non-invasive diagnostic test with a high sensitivity (80% or more) for symptomatic endometriosis patients, without US evidence of endometriosis, since this is the group most in need of a non-invasive test. Methods A total of 28 inflammatory and non-inflammatory plasma biomarkers were measured in 353 EDTA plasma samples collected at surgery from 121 controls without endometriosis at laparoscopy and from 232 women with endometriosis (minimal-mild n = 148; moderate-severe n = 84), including 175 women without preoperative US evidence of endometriosis. Surgery was done during menstrual (n = 83), follicular (n = 135) and luteal (n = 135) phases of the menstrual cycle. For analysis, the data were randomly divided into an independent training (n = 235) and a test (n = 118) data set. Statistical analysis was done using univariate and multivariate (logistic regression and least squares support vector machines (LS-SVM) approaches in training- and test data set separately to validate our findings. Results In the training set, two models of four biomarkers (Model 1: annexin V, VEGF, CA-125 and glycodelin; Model 2: annexin V, VEGF, CA-125 and sICAM-1) analysed in plasma, obtained during the menstrual phase, could predict US-negative endometriosis with a high sensitivity (81-90%) and an acceptable specificity (68-81%). The same two models predicted US-negative endometriosis in the independent validation test set with a high sensitivity (82%) and an acceptable specificity (63-75%). Conclusions In plasma samples obtained during menstruation, multivariate analysis of four biomarkers (annexin V, VEGF, CA-125 and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by US with a sensitivity of 81-90% and a specificity of 63-81% in independent training- and test data set. The next step is to apply these models for preoperative prediction of endometriosis in an independent set of patients with infertility and/or pain without US evidence of endometriosis, scheduled for laparoscopy.
ISSN: 0268-1161
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Laboratory of Phosphoproteomics (-)
Laboratory of Clinical Immunology
Laboratory of Protein Phosphorylation and Proteomics
Department of Development and Regeneration - miscellaneous (+)
Laboratory of Virology and Chemotherapy (Rega Institute)
Experimental Laboratory Immunology
Sexual, Pelvic, Reproductive and Family Studies (-)
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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