Predictive values of anti-müllerian hormone, antral follicle count and ovarian response prediction index (ORPI) for assisted reproductive technology outcomes. (2nd January 2017)

• Record Type: Journal Article
• Authors: Ashrafi, Mahnaz; Hemat, Mandana; Arabipoor, Arezoo; Salman Yazdi, Reza; Bahman-Abadi, Akram; Cheraghi, Rezvaneh
• Is Part Of: Journal of obstetrics and gynaecology. Volume 37:Number 1(2017)
• Page Start: 82
• Page End: 88
• Publication Date: 2017-01-02
• Subjects: Anti-müllerian hormone -- antral follicle count -- ovarian response prediction index -- live birth rate; Obstetrics -- Periodicals; Gynecology -- Periodicals; 618.05
• DOI: 10.1080/01443615.2016.1225025
• Languages: English
• ISSNs: 0144-3615

Abstract

Abstract: This prospective study was performed from June 2012 to June 2014 at Royan Institute to compare the predictive values of serum anti-müllerian hormone (AMH), antral follicle count (AFC) and ovarian response prediction index (ORPI) ([AFC × AMH]/age) for in vitro fertilisation/intracytoplasmic sperm injection (IVF/ICSI) cycle outcomes. Five hundred and fifty women included in the study with male factor and unexplained infertility were the first candidates for IVF/ICSI cycles. Serum AMH level was measured by a commercial ELISA kit and AFC was calculated by a transvaginal ultrasonography on day 2–3 of the menstrual cycle before starting ovarian stimulation. All women underwent IVF/ICSI cycles using a long standard protocol with gonadotropin-releasing hormone agonist. The receiver operating characteristic curves (ROC) analysis showed that both AMH and AFC were good predictors of ovarian response with an area under the curves (AUC) > 0.75; even it seems that AFC was being a better predictor. Combining these variables is necessary as ORPI will not improve the prediction value. All the variables had poor predictive ability (AUC <0.60) for clinical pregnancy and live birth rates. Logistic regression analysis showed the AMH less than 0.4 ng/ml and quality of transferred embryos were significant predictors for clinical pregnancy rate.