吉林大学学报(医学版) ›› 2023, Vol. 49 ›› Issue (1): 158-165.doi: 10.13481/j.1671-587X.20230120

• 临床研究 • 上一篇    

基于多个影响因素建立列线图模型预测IVF-ET患者发生异位妊娠的风险

翁丹,段海霞()   

  1. 西北妇女儿童医院生殖妇科,陕西 西安 710003
  • 收稿日期:2021-10-07 出版日期:2023-01-28 发布日期:2023-02-03
  • 通讯作者: 段海霞 E-mail:hx840315@126.com
  • 作者简介:翁 丹(1989-),女,陕西省西安市人,住院医师,医学硕士,主要从事围产医学和妇科肿瘤方面的研究。
  • 基金资助:
    陕西省重点研发计划一般项目(2021SF-206);陕西省西安市科技局项目[20YXYJ0005(9)]

Risk of ectopic pregnancy in patients with IVF-ET predicted with nomogram model based on multiple influencing factors

Dan WENG,Haixia DUAN()   

  1. Department of Reproductive Obstetrics,Northwest Women’s and Children’s Hospital,Xi’an 710003,China
  • Received:2021-10-07 Online:2023-01-28 Published:2023-02-03
  • Contact: Haixia DUAN E-mail:hx840315@126.com

摘要:

目的 分析体外受精-胚胎移植(IVF-ET)患者发生异位妊娠的影响因素,并建立列线图模型预测IVF-ET患者发生异位妊娠的风险。 方法 制定研究对象的纳入和排除标准,回顾性分析522例接受IVF-ET且成功妊娠患者的临床资料,用于建模和内部验证;参照上述纳入和排除标准,筛选非本院的1 126例IVF-ET且成功妊娠患者的临床资料,用于外部验证。记录患者的基线资料,依据IVF-ET患者是否发生异位妊娠情况分为异位妊娠发生组和异位妊娠未发生组,采用Logistic回归分析IVF-ET患者发生异位妊娠的影响因素,并基于上述影响因素建立预测IVF-ET患者发生异位妊娠的列线图模型;采用Bootstrap法进行模型验证,计算一致性指数(C-index),检验模型准确性;采用受试者工作特征曲线(ROC)下面积(AUC)和校准曲线评估列线图模型的区分度和校准度。 结果 内部验证组522例患者中,有45例患者发生异位妊娠,发生率为8.62%;对比异位妊娠发生组和异位妊娠未发生组患者基线资料后进行Logistic回归分析,宫腔操作史、吸烟史、盆腔炎性疾病史、既往异位妊娠史、注射人绒毛膜促性腺激素(hCG)当天血雌二醇(E2)水平升高是IVF-ET患者发生异位妊娠的影响因素(OR>1,P<0.05)。构建预测IVF-ET患者发生异位妊娠的列线图模型,采用Bootstrap内部验证法验证,模型校准度良好,C-index为0.702,表明模型具有良好的区分度。对列线图模型进行内部验证,绘制ROC曲线,列线图模型预测IVF-ET患者异位妊娠发生风险的AUC为0.735(>0.70),有一定预测价值;对列线图模型进行外部验证,绘制ROC曲线,列线图模型预测IVF-ET患者异位妊娠发生风险的AUC为0.862(>0.80),有较好的预测价值。 结论 IVF-ET患者发生异位妊娠受宫腔操作史、吸烟史、盆腔炎性疾病史、既往异位妊娠史和注射hCG当天血E2水平等多种因素影响,基于多个影响因素建立的列线图模型为临床合理预测IVF-ET患者异位妊娠发生风险提供了有效方法。

关键词: 体外受精-胚胎移植, 异位妊娠, 影响因素, 列线图模型

Abstract:

Objective To analyze the influencing factors of ectopic pregnancy in the patients with in vitro fertilization-embryo transfer (IVF-ET),and to establish the nomogram model to predict the risk of ectopic pregrancy in the patients with IVF-ET. Methods The inclusion and exclusion criteria of the subjects were developed, the clinical informations of 522 patients with IVF-ET and successful pregnancy were analyzed retrospectively for modeling and internal validation; according to the above inclusion and exclusion criteria, the clinical informations of 1 126 patients with IVF-ET and successful pregnancy who were not in our hospital were screened for external verification. The baseline data of the patients were recorded, according to the occurrence of ectopic pregnancy in the IVF-ET patients, they were divided into occurrence group and non-occurrence group, Logistic regression was used to analyze the influencing factors of ectopic pregnancy in the patients with IVF-ET; based on the above influencing factors, the nomogram model for predicting the occurrence of ectopic pregnancy in the IVF-ET patients was established. The Bootstrap method was used for model verification, and the consistency index (C-index) was calculated to test the accuracy of the model; the area under the curve (AUC) of receiver operating characteristics (ROC) and calibration curve were used to evaluate the discrimination and calibration of the nomogram model. Results Among 522 patients in the internal validation group, 45 patients had ectopic pregnancy, the incidence rate was 8.62%; after the baseline data of the patients in two groups were compared, the Logistic regression analysis results showed that the history of intrauterine operation, smoking,pelvic inflammatory disease, previous ectopic pregnancy and elevated serum estradiol (E2) level on the day of human chorionic gonadotrophin (hCG) injection were the influencing factors of ectopic pregnancy in the patients with IVF-ET (OR>1,P<0.05); the nomogram model for predicting the ectopic pregnancy in the IVF-ET patients was constructed; Bootstrap internal verification method was used to verify the nomogram model, the calibration degree of the model was good, and the C-index was 0.702; it showed that the model had good discrimination. The nomogram model was internally verified, the ROC curve was drawn and the AUC of nomogram model in predicting the risk of ectopic pregnancy in the patients with IVF-ET was 0.735(>0.70), which had certain predictive value; the nomogram model was externally verified, the ROC curve was drawn and the AUC of nomogram model for predicting the risk of ectopic pregnancy in the patients with IVF-ET was 0.862(>0.80), which had better predictive value. Conclusion Ectopic pregnancy in the patients with IVF-ET is affected by many factors such as history of intrauterine operation, smoking, pelvic inflammatory disease, previous ectopic pregnancy and the E2 level on the day of hCG injection, and the nomogram model based on multiple influencing factors provides an effective method for reasonably predicting the risk of ectopic pregnancy in the patients with IVF-ET.

Key words: In vitro fertilization-embryo transfer, Ectopic pregnancy, Influencing factors, Nomogram model

中图分类号: 

  • R711.6