Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA; Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
Am J Obstet Gynecol. 2023 May;228(5):557.e1-557.e10. doi: 10.1016/j.ajog.2023.01.014. Epub 2023 Jan 23.
As the use of in vitro fertilization continues to increase in the United States, up-to-date models that estimate cumulative live birth rates after multiple oocyte retrievals and embryo transfers (fresh and frozen) are valuable for patients and clinicians weighing treatment options.
This study aimed to develop models that generate predicted probabilities of live birth in individuals considering in vitro fertilization based on demographic and reproductive characteristics.
Our population-based cohort study used data from the National Assisted Reproductive Technology Surveillance System 2016 to 2018, including 196,916 women who underwent 207,766 autologous embryo transfer cycles and 25,831 women who underwent 36,909 donor oocyte transfer cycles. We used data on autologous in vitro fertilization cycles to develop models that estimate a patient's cumulative live birth rate after all embryo transfers (fresh and frozen) within 12 months after 1, 2, and 3 oocyte retrievals in new and returning patients. Among patients using donor oocytes, we estimated the cumulative live birth rate after their first, second, and third embryo transfers. Multinomial logistic regression models adjusted for age, prepregnancy body mass index (imputed for 18% of missing values), parity, gravidity, and infertility diagnoses were used to estimate the cumulative live birth rate.
Among new and returning patients undergoing autologous in vitro fertilization, female age had the strongest association with cumulative live birth rate. Other factors associated with higher cumulative live birth rates were lower body mass index and parity or gravidity ≥1, although results were inconsistent. Infertility diagnoses of diminished ovarian reserve, uterine factor, and other reasons were associated with a lower cumulative live birth rate, whereas male factor, tubal factor, ovulatory disorders, and unexplained infertility were associated with a higher cumulative live birth rate. Based on our models, a new patient who is 35 years old, with a body mass index of 25 kg/m, no previous pregnancy, and unexplained infertility diagnoses, has a 48%, 69%, and 80% cumulative live birth rate after the first, second, and third oocyte retrieval, respectively. Cumulative live birth rates are 29%, 48%, and 62%, respectively, if the patient had diminished ovarian reserve, and 25%, 41%, and 52%, respectively, if the patient was 40 years old (with unexplained infertility). Very few recipient characteristics were associated with cumulative live birth rate in donor oocyte patients.
Our models provided estimates of cumulative live birth rate based on demographic and reproductive characteristics to help inform patients and providers of a woman's probability of success after in vitro fertilization.
随着美国体外受精的使用不断增加,对于权衡治疗选择的患者和临床医生来说,能够预测多次取卵和胚胎移植(新鲜和冷冻)后累积活产率的最新模型非常有价值。
本研究旨在建立模型,根据人口统计学和生殖特征,为考虑接受体外受精的个体生成活产预测概率。
本基于人群的队列研究使用了 2016 年至 2018 年国家辅助生殖技术监测系统的数据,包括 196916 名接受了 207766 次自体胚胎移植周期和 25831 名接受了 36909 次供卵胚胎移植周期的女性。我们使用自体体外受精周期的数据,为新患者和复诊患者建立了模型,以估计在取卵后 1、2 和 3 个卵母细胞后的 12 个月内所有胚胎移植(新鲜和冷冻)后患者的累积活产率。在使用供卵的患者中,我们估计了她们首次、第二次和第三次胚胎移植后的累积活产率。采用多分类逻辑回归模型调整年龄、孕前体重指数(缺失值的 18% 进行了推断)、产次、孕次和不孕诊断,以估计累积活产率。
在接受自体体外受精的新患者和复诊患者中,女性年龄与累积活产率的关联最强。与较高的累积活产率相关的其他因素包括较低的体重指数和产次或孕次≥1,尽管结果不一致。卵巢储备功能减退、子宫因素和其他原因的不孕诊断与较低的累积活产率相关,而男性因素、输卵管因素、排卵障碍和不明原因的不孕与较高的累积活产率相关。根据我们的模型,一位 35 岁、体重指数为 25kg/m、无既往妊娠且诊断为不明原因不孕的新患者,在第一次、第二次和第三次取卵后,其累积活产率分别为 48%、69%和 80%。如果患者患有卵巢储备功能减退症,其累积活产率分别为 29%、48%和 62%;如果患者为 40 岁(伴有不明原因不孕),其累积活产率分别为 25%、41%和 52%。供卵患者中,很少有受体特征与累积活产率相关。
我们的模型根据人口统计学和生殖特征提供了累积活产率的估计值,以帮助患者和提供者了解女性在体外受精后的成功概率。