Harris Birthright Research Centre for Fetal Medicine, King's College, London, United Kingdom.
Institute of Health Research, University of Exeter, Exeter, United Kingdom.
Am J Obstet Gynecol. 2016 May;214(5):619.e1-619.e17. doi: 10.1016/j.ajog.2015.11.016. Epub 2015 Nov 25.
Preeclampsia (PE) affects 2-3% of all pregnancies and is a major cause of maternal and perinatal morbidity and mortality. The traditional approach to screening for PE is to use a risk-scoring system based on maternal demographic characteristics and medical history (maternal factors), but the performance of such an approach is very poor.
To develop a model for PE based on a combination of maternal factors with second-trimester biomarkers.
The data for this study were derived from prospective screening for adverse obstetric outcomes in women attending their routine hospital visit at 19-24 weeks' gestation in 3 maternity hospitals in England between January 2006 and July 2014. We had data from maternal factors, uterine artery pulsatility index (UTPI), mean arterial pressure (MAP), serum placental growth factor (PLGF), and serum soluble fms-like tyrosine kinase-1 (SFLT) from 123,406, 67,605, 31,120, 10,828, and 8079 pregnancies, respectively. Bayes' theorem was used to combine the a priori risk from maternal factors with various combinations of biomarker multiple of the median (MoM) values. The modeled performance of screening for PE requiring delivery at <32, <37, and ≥37 weeks' gestation was estimated. The modeled performance was compared to the empirical one, which was derived from 5-fold cross validation. We also examined the performance of screening based on risk factors from the medical history, as recommended by the American Congress of Obstetricians and Gynecologists (ACOG).
In pregnancies that developed PE, the values of MAP, UTPI, and SFLT were increased and PLGF was decreased. For all biomarkers the deviation from normal was greater for early than for late PE, and therefore the performance of screening was inversely related to the gestational age at which delivery became necessary for maternal and/or fetal indications. Screening by maternal factors predicted 52%, 47%, and 37% of PE at <32, <37, and ≥37 weeks' gestation, respectively, at a false-positive rate of 10%. The respective values for combined screening with maternal factors and MAP, UTPI, and PLGF were 99%, 85%, and 46%; the performance was not improved by the addition of SFLT. In our population of 123,406 pregnancies, the DR of PE at <32, <37, and ≥37 weeks with the ACOG recommendations was 91%, 90%, and 91%, respectively, but at a screen positive rate of 67%.
The performance of screening for PE by maternal factors and biomarkers in the middle trimester is superior to taking a medical history.
子痫前期（PE）影响所有妊娠的 2-3%，是孕产妇和围产儿发病率和死亡率的主要原因。PE 的传统筛查方法是使用基于产妇人口统计学特征和病史（产妇因素）的风险评分系统，但这种方法的性能非常差。
基于产妇因素和中期妊娠生物标志物建立 PE 模型。
本研究的数据来自于 2006 年 1 月至 2014 年 7 月在英格兰的 3 家产科医院，在妊娠 19-24 周时对常规就诊的妇女进行的不良产科结局的前瞻性筛查。我们有来自产妇因素、子宫动脉搏动指数（UTPI）、平均动脉压（MAP）、血清胎盘生长因子（PLGF）和血清可溶性 fms 样酪氨酸激酶-1（SFLT）的数据，分别来自 123406、67605、31120、10828 和 8079 例妊娠。贝叶斯定理用于结合产妇因素的先验风险与各种生物标志物中位数倍数（MoM）值的组合。估计了需要在<32、<37 和≥37 周分娩的 PE 的筛查模型性能。比较了从 5 折交叉验证得出的经验模型性能。我们还检查了根据美国妇产科医师大会（ACOG）推荐的病史风险因素进行筛查的性能。
在发生 PE 的妊娠中，MAP、UTPI 和 SFLT 值增加，PLGF 值降低。对于所有生物标志物，早期 PE 的偏离正常值程度大于晚期 PE，因此筛查的性能与需要分娩的孕龄呈负相关，以满足母亲和/或胎儿的指征。产妇因素预测在<32、<37 和≥37 周分娩的 PE 的发生率分别为 52%、47%和 37%，假阳性率为 10%。用产妇因素和 MAP、UTPI 和 PLGF 联合筛查的相应值为 99%、85%和 46%；添加 SFLT 并不能提高性能。在我们的 123406 例妊娠人群中，ACOG 建议的<32、<37 和≥37 周的 PE 发生率分别为 91%、90%和 91%，但筛查阳性率为 67%。
中期妊娠中，产妇因素和生物标志物筛查 PE 的性能优于采集病史。
