卵巢低反应患者新鲜周期妊娠结局的列线图预测模型的构建和评价

Establishment and evaluation of a nomogram prediction model for predicting pregnancy outcomes of poor ovarian response patients in fresh cycles

目的探究卵巢低反应(poor ovarian response,POR)患者新鲜周期妊娠结局的影响因素,构建和验证列线图模型预估POR患者最终活产概率。方法回顾性队列研究分析2015年2月1日至2019年2月28日期间在商丘市第一人民医院生殖医学中心及新疆医科大学第一附属医院生殖医学中心行助孕治疗的2667例预期POR患者,采用单因素和多因素逻辑回归分析筛选出POR患者妊娠结局的独立影响因素,根据因素变量的回归系数绘制相应的列线图预测模型,内部验证按完全随机化分组及对照原则分为建模组和验证组,通过受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under the curve,AUC)验证列线图模型的预测准确度。结果通过多因素逻辑回归分析,女性年龄(OR=0.876,95%CI=0.849~0.902,P<0.001)、窦卵泡计数(OR=1.283,95%CI=1.133~1.463,P<0.001)、促性腺激素使用总量(OR=1.002,95%CI=1.001~1.004,P<0.001)、促性腺激素使用时间(OR=0.786,95%CI=0.636~0.963,P=0.018)、MII卵数(OR=0.842,95%CI=0.712~0.985,P=0.033)和可移植胚胎数(OR=2.052,95%CI=1.762~2.403,P<0.001)是最终活产率的独立影响因子,根据上述独立影响因子构建POR患者妊娠结局的预测模型,建模组的AUC为0.894(95%CI=0.878~0.909),验证组的AUC为0.902(95%CI=0.896~0.912),提示模型符合度良好。结论女性年龄、窦卵泡计数、促性腺激素使用总量及时间、MII卵数、可移植胚胎数是接受人类辅助生殖技术治疗的POR患者新鲜周期妊娠结局的独立影响因素,列线图模型的成功构建能够有效、简便和直观地预测POR患者最终活产概率。

Objective To explore the predictive factors associated with the pregnancy outcome for poor ovarian response(POR)patients,and to establish Nomogram prediction model to evaluate the probability of the live birth of POR patients.Methods The clinical data of 2667 patients who underwent in vitro fertilization(IVF)/intracytoplasmic sperm injection(ICSI)treatment in the Center of Reproductive Medicine,the First People's Hospital of Shangqiu and the First Affiliated Hospital of Xinjiang Medical University from February 1,2015 to February 28,2019 were retrospectively analyzed by a cohort study.Logistic regression was used to screen out the independent predictive factors on the pregnancy outcome of IVF/ICSI in poor ovarian reserve patients,which was the model enrollment variable,and the Nomogram model was established according to the regression coefficient of the relevant variables.The prediction accuracy of the pregnancy outcome nomogram model was evaluated by calculating the receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results Multivariate logistic regression analysis showed that female age(OR=0.876,95%CI=0.849-0.902,P<0.001),antral follicle count(AFC)(OR=1.283,95%CI=1.133-1.463,P<0.001),total dosage of gonadotropin(Gn)used(OR=1.002,95%CI=1.001-1.004,P<0.001),duration of Gn used(OR=0.786,95%CI=0.636-0.963,P=0.018),No.of MII oocytes(OR=0.842,95%CI=0.712-0.985,P=0.033)and No.of transferable embryos(OR=2.052,95%CI=1.762-2.403,P<0.001)were independent predictive factors of live birth.According to the independent predictive factors,the prediction model of pregnancy outcome of POR patients was established,and the AUC of the modeling group was 0.894(95%CI=0.879-0.909),the AUC of the validation group was 0.902(95%CI=0.896-0.912),indicating good model compliance.Conclusion Age,AFC,total dosage of Gn used,duration of Gn used,No.of MII oocytes and No.of transferable embryos are independent predictive factors of the pregnancy outcome for poor ovarian reserve patients,the successful establishment of nomogram model can effectively predict the live birth for POR patients.