Department of Gynecology and Obstetrics, Peking University First Hospital, Beijing, China.
Front Endocrinol (Lausanne). 2021 Aug 23;12:717288. doi: 10.3389/fendo.2021.717288. eCollection 2021.
Despite the great advances in assisted reproductive technology (ART), poor ovarian response (POR) is still one of the most challenging tasks in reproductive medicine. This predictive model we developed aims to predict the individual probability of clinical pregnancy failure for poor ovarian responders (PORs) under fertilization/intracytoplasmic sperm injection (IVF/ICSI).
The nomogram was developed in 281 patients with POR according to the Bologna criteria from January 2016 to December 2019, with 179 in the training group and 102 in the validation group. Univariate and multivariate logistic regression analyses were used to identify characteristics that were associated with clinical pregnancy failure. The nomogram was constructed based on regression coefficients. Performance was evaluated using both calibration and discrimination.
Age >35 years, body mass index (BMI) >24 kg/m, basic follicle-stimulating hormone (FSH) >10 mIU/ml, basic E2 >60 pg/ml, type B or C of endometrium on human chorionic gonadotropin (hCG) day, and the number of high-quality embryos <2 were associated with pregnancy failure of POR patients. The area under the receiver operating characteristic curve (AUC) of the training set is 0.786 (95% confidence interval (CI): 0.710-0.861), and AUC in the validation set is 0.748 (95% CI: 0.668-0.827), showing a satisfactory goodness of fit and discrimination ability in this nomogram.
Our nomogram can predict the probability of clinical pregnancy failure in PORs before embryo transfer in IVF/ICSI procedure, to help practitioners make appropriate clinical decisions and to help infertile couples manage their expectations.
尽管辅助生殖技术（ART）取得了巨大进步，但卵巢反应不良（POR）仍然是生殖医学中最具挑战性的任务之一。我们开发的这个预测模型旨在预测接受体外受精/卵胞浆内单精子注射（IVF/ICSI）的 POR 患者临床妊娠失败的个体概率。
该列线图根据 2016 年 1 月至 2019 年 12 月的博洛尼亚标准，在 281 名 POR 患者中开发，其中训练组 179 例，验证组 102 例。使用单变量和多变量逻辑回归分析来确定与临床妊娠失败相关的特征。该列线图基于回归系数构建。使用校准和判别评估性能。
年龄>35 岁、体重指数（BMI）>24 kg/m、基础卵泡刺激素（FSH）>10 mIU/ml、基础雌二醇（E2）>60 pg/ml、人绒毛膜促性腺激素（hCG）日内膜 B 型或 C 型、高质量胚胎数<2 与 POR 患者妊娠失败相关。训练集的受试者工作特征曲线（ROC）下面积（AUC）为 0.786（95%置信区间（CI）：0.710-0.861），验证集的 AUC 为 0.748（95%CI：0.668-0.827），表明该列线图具有良好的拟合度和判别能力。
我们的列线图可以预测 IVF/ICSI 过程中 POR 患者胚胎移植前的临床妊娠失败概率，以帮助从业者做出适当的临床决策，并帮助不孕夫妇管理他们的期望。
