REPRODUCTIVE BIOMEDICINE ONLINE | 卷:28 |
Predictive value of androgens and multivariate model for poor ovarian response | |
Article | |
Guo, Jing1  Zhang, Qingxue1  Li, Yu1  Huang, Jia1  Wang, Wenjun1  Huang, Lili1  Zhao, Xiaomiao1  Yang, Dongzi1  | |
[1] Sun Yat Sen Univ, Sun Yat Sen Mem Hosp, Dept Obstet & Gynecol, Guangzhou 510275, Guangdong, Peoples R China | |
关键词: dehydroepiandrosterone sulphate; IVF; multivariate model; poor ovarian response; pregnancy outcome; testosterone; | |
DOI : 10.1016/j.rbmo.2014.02.009 | |
来源: Elsevier | |
【 摘 要 】
No single or multivariate model is effective for predicting poor ovarian response (POR) with satisfactory sensitivity and specificity. This study investigated whether dehydroepiandrosterone sulphate (DHEAS) or basal testosterone concentrations could be effective predictors of POR defined by the Bologna criteria. This retrospective study included 79 poor responders and 128 normal responders. Serum FSH, LH, oestradiol, DHEAS and testosterone concentrations on day 3 of the menstrual cycle before the treatment cycle were measured. All patients received standard ovarian stimulation with FSH under pituitary suppression with gonadotrophin-releasing hormone agonist. DHEAS concentration was not significantly different between poor and normal responders or between pregnant and nonpregnant women. Basal testosterone, unlike DHEAS concentration, was predictive, but with limited ability as a single predictor, for POR. The multivariate model composed of age, AFC, FSH, FSH/LH and testosterone was reliably predictive for POR (ROCAUC = 0.976, cut-off point >0.51, sensitivity 88.6%, specificity 98.3%) and clinical pregnancy (ROCAUC = 0.716, cut-off point <=-0.22, sensitivity 75%, specificity 62.5%) and was better than antral follicle count for predicting both POR and clinical pregnancy. This multivariate model might be useful for identifying patients at risk of poor response in order to optimize the stimulation regimens. (C) 2014, Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
【 授权许可】
Free
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
10_1016_j_rbmo_2014_02_009.pdf | 1018KB | download |