Preoperative serum anti-Mullerian hormone level is a potential predictor of ovarian endometrioma severity and postoperative fertility

Objective: To establish a model for predicting revised American Society of Reproductive Medicine (rASRM) scores before endometrioma surgery based on serum anti-Mullerian hormone (AMH) level and to identify factors that might reliably predict postoperative fertility of women diagnosed with endometrioma. Study design: The study population was composed of 134 women with endometrioma, 58 with benign cyst, and 115 with non-ovarian lesion. Preoperative serum AMH level and clinical parameters were compared among three groups. Univariate correlation analyses and multivariate linear regression modeling with a stepwise method were performed for constructing an rASRM scores prediction model. Cox regression analysis was then used to identify predictive variables of spontaneous pregnancy following surgical treatment of endometrioma. Results: Preoperative AMH level were significantly lower in the endometrioma group than in the other two groups (p < 0.001). Multivariate linear regression analysis revealed that age (beta=-0.324, p < 0.001), rASRM scores (beta=-0.298, p < 0.001) and serum CA125 level (beta= 0.176, p =0.026) independently and negatively correlated with serum AMH level. Cox regression analysis of women with endometrioma who underwent surgical resection indicated that older age (per five-year increase, HR: 0.517; 95% CI, 0.299-0.896) and higher serum AMH level (cut-off value: >3.68 ng/ml, HR: 2.383; 95% CI, 1.093-5.197) were independent predictors for postoperative fertility. Conclusion: Patients with advanced staged endometriosis tended to have a lower serum AMH level while postoperative infertility was more likely to occur in older patients with a lower level of serum AMH. Thus, timely detection of AMH levels to assess the severity of ovarian endometriosis and possibility for postoperative pregnancy success is necessary to ensure that optimal medical treatment can be provided. (C) 2019 Elsevier B.V. All rights reserved.