Evaluation of a panel of 28 biomarkers for the non-invasive diagnosis of endometriosis

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 611 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. 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 (minimalmild n 148; moderatesevere 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. In the training set, two models of four biomarkers (Model 1: annexin V, VEGF, CA-125and glycodelin; Model 2: annexin V, VEGF, CA-125and sICAM-1) analysed in plasma, obtained during the menstrual phase, could predict US-negative endometriosis with a high sensitivity (8190) and an acceptable specificity (6881). The same two models predicted US-negative endometriosis in the independent validation test set with a high sensitivity (82) and an acceptable specificity (6375). In plasma samples obtained during menstruation, multivariate analysis of four biomarkers (annexin V, VEGF, CA-125and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by US with a sensitivity of 8190 and a specificity of 6381 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.