A predictive model for endometriosis

Open Access
Publisher Website
Google Scholar
Abstract
BACKGROUND: Aromatase is the key enzyme in the process of estrogen biosynthesis from the precursor androgen. Recently, aromatase has been found to be aberrantly expressed in eutopic endometrium of patients suffering from endometriosis. This finding has prompted speculation about the contribution of this enzyme to the prediction of this disease. METHODS: We prospectively aimed to evaluate whether endometrial biopsy, prior to laparoscopy in symptomatic women to screen for the presence of aromatase by real-time RT–PCR and immunohistochemistry, combined with select patients' characteristics, is of value to predict endometriosis. RESULTS: Of 48 consecutive symptomatic and eligible patients, 25 (52.1%) exhibited endometriosis and 23 (47.9%) were disease-free. A multiple logistic regression model revealed that 95.5% of patients whose eutopic endometrium was found to be positive for aromatase mRNA as well as immunohistochemically detected protein and who were additionally suffering from moderate to severe dysmenorrhoea (visual analogue scale score >4/10) exhibited endometriosis at laparoscopy. CONCLUSIONS: These findings provide direct evidence that screening for eutopic endometrial aromatase in combination with clinical data could be of discriminative value in the prediction of disease.