不明原因不孕患者累积活产率的列线图模型构建

Nomogram for cumulative live birth rate in women with unexplained infertility

目的开发和验证基于真实世界临床数据的列线图,以预测不明原因不孕患者的累积活产率。方法回顾性分析2014年1月至2018年12月在西北妇女儿童医院生殖中心第1次行IVF助孕的4804例不明原因不孕患者的临床资料。将符合条件的70%患者随机分配至建模组,其余30%被分配到验证组,使用Logistic回归模型进行多变量分析。结果建模组单因素分析显示,具有统计学意义的预测因素是女性年龄、体质量指数(BMI)、孕次、产次、不孕年限、不孕类型、基础窦卵泡计数(AFC)、基础卵泡刺激素(bFSH)(P<0.05)。预测累积活产率的多因素分析模型显示,累积活产率随着年龄增长、BMI及bFSH升高有降低的趋势,而随着AFC的增加有升高趋势,提示女性年龄、BMI、AFC和bFSH水平是不明原因不孕患者累积活产率的重要预测因素。在建模组中,预测模型中受试者工作特征曲线下面积(AUC)为0.639[95%CI(0.620,0.658)]。验证组显示出良好的区分度,AUC为0.644[95%CI(0.615,0.673)]。此外,Hosmer-Lemeshow拟合优度检验χ^(2)值为9.732(P=0.284)。结论本研究为初次行IVF助孕的不明原因不孕患者建立了个性化的累积活产率列线图预测模型。通过这个预测模型,可以个性化地预测不明原因不孕患者的累积活产率,并提供证据支持。

Objective:To develop and validate a nomogram based on real-world clinical data to predict the cumulative live birth rate in women with unexplained infertility.Methods:The clinical data of 4804 patients with unexplained infertility who underwent IVF treatment firstly in Assisted Reproduction Center of Northwest Women’s and Children’s Hospital from January 2014 to December 2018 were retrospectively analyzed.Of the eligible participants,70%were randomly assigned to the modeling group,while the remaining 30%were assigned to the validation group.Multivariate analysis by using the logistic regression model was performed.Results:Univariate analysis of the modeling group showed that the significant predictors were female age,body mass index(BMI),gravidity&parity,years of infertility,type of infertility,basal antral follicle count(AFC)and basal FSH(P<0.05).The multivariate analysis model for predicting cumulative live birth rate showed that the probability of successful cumulative live birth decreased with increase of age,BMI and bFSH level.There was a significant positive correlation between AFC and cumulative live rate.It was suggested that female age,BMI,AFC and bFSH level were important predictors of cumulative live birth rate in patients with unexplained infertility.In the modeling group,the area under the operating characteristic curve(AUC)in the prediction model group was 0.639[95%CI(0.620,0.658)].The validation group showed good discrimination with an AUC of 0.644[95%CI(0.615,0.673)].In addition,χ^(2) value of Hosmer-Lemeshow Goodness-of-Fit Test was 9.732(P=0.284).Conclusions:This study established an individualized nomogram prediction model of cumulative live birth rate for unexplained infertility patients undergoing IVF for the first time.Through this prediction model,the cumulative live birth rate of patients with unexplained infertility can be individually predicted and supported by evidence.