Nomogram for Predicting Live Birth after the First Fresh Embryo Transfer in Patients with PCOS Undergoing IVF/ICSI Treatment with the GnRH-Ant Protocol

Author:

Si Manfei1234,Jiang Huahua1234,Zhao Yue1234,Qi Xinyu1234,Li Rong1234,Long Xiaoyu1234,Qiao Jie123456ORCID

Affiliation:

1. Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China

2. National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China

3. Key Laboratory of Assisted Reproduction, Peking University, Ministry of Education, Beijing 100191, China

4. Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing 100191, China

5. Beijing Advanced Innovation Center for Genomics, Beijing 100191, China

6. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100191, China

Abstract

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility. A better understanding of factors associated with pregnancy outcomes and successful prediction of live birth after IVF/ICSI are important to guide clinical practice. This was a retrospective cohort study investigating live birth after the first fresh embryo transfer using the GnRH-ant protocol in patients with PCOS between 2017 and 2021 at the Reproductive Center of Peking University Third Hospital. A total of 1018 patients with PCOS were qualified for inclusion in this study. BMI, AMH level, initial FSH dosage, serum LH and progesterone levels on the hCG trigger day, and endometrial thickness were all independent predictors of live birth. However, age and infertility duration were not significant predictors. We developed a prediction model based on these variables. The predictive ability of the model was demonstrated well, with areas under the curve of 0.711 (95% CI, 0.672–0.751) and 0.713 (95% CI, 0.650–0.776) in the training cohort and validation cohort, respectively. Additionally, the calibration plot showed good agreement between the prediction and the observation (p = 0.270). The novel nomogram could be helpful for clinicians and patients in clinical decision-making and outcome evaluation.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

China Postdoctoral Science Foundation

Publisher

MDPI AG

Subject

Clinical Biochemistry

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