预测中国孕妇的早期子痫前症的多标志物模型适用性究竟如何？| BMC Pregnancy and Childbirth
论文标题：Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study
期刊：BMC Pregnancy and Childbirth
作者：Jing Zhang, Luhao Han et.al
最新证据表明子痫前症和小于胎龄儿（small-for-gestational-age，SGA）的早期筛查并在随后预防性使用阿司匹林对于妊娠有益。多标志物模型能够在早期妊娠中预测早孕子痫前症和SGA。但是，目前这一组合筛选模型对中国孕妇的临床可行性还没有经过全面的评估。近期发表在BMC Pregnancy and Childbirth 上的研究就是为了评估多标志物筛选模型在妊娠早期（特别是中国人群）预测子痫前症和SGA的适用性。
近期发表在BMC Pregnancy and Childbirth期刊上，题为Early prediction of preeclampsia and small-for-gestational-age via multi-marker model in Chinese pregnancies: a prospective screening study 的研究对符合标准的3270名孕妇进行了妊娠早期的子痫前症和SGA筛查，并对基于母体特征的先验风险进行了评估。后验风险则通过综合先验风险与平均动脉压（mean arterial pressure，MAP）、血清胎盘生长因子（serum placental growth factor，PLGF）和妊娠相关血浆蛋白A（pregnancy associated plasma protein A，PAPP-A）中位数倍数（multiple of median，MoM）来计算。这两种风险均通过Perkin Elmer的Preeclampsia PREDICTOR™ 软件计算得出。受试者工作特征曲线（receiver operating characteristic curve，ROC曲线）反映了PREDICTOR软件对于早期和晚期子痫前症的先验和后验风险的筛查情况。然后，我们估计了子痫前症和SGA的检出率和假阳性率。
BMC Pregnancy & Childbirth
BMC Pregnancy & Childbirth is an open access, peer-reviewed journal that considers articles on all aspects of pregnancy and childbirth. The journal welcomes submissions on the biomedical aspects of pregnancy, breastfeeding, labor, maternal health, maternity care, trends and sociological aspects of pregnancy and childbirth.
Recent evidence suggests early screening of preeclampsia and small-for-gestational-age (SGA) would benefit pregnancies followed by subsequent prophylactic use of aspirin. Multi-marker models have shown capability of predicting preeclampsia and SGA in first trimester. Yet the clinical feasibility of combined screening model for Chinese pregnancies has not been fully assessed. The aim of this study is to evaluate the applicability of a multi-marker screening model to the prediction of preeclampsia and SGA in first trimester particularly among Chinese population.
Three thousand two hundred seventy pregnancies meeting the inclusion criteria took first-trimester screening of preeclampsia and SGA. A prior risk based on maternal characteristics was evaluated, and a posterior risk was assessed by combining prior risk with multiple of median (MoM) values of mean arterial pressure (MAP), serum placental growth factor (PLGF) and pregnancy associated plasma protein A (PAPP-A). Both risks were calculated by Preeclampsia PREDICTOR™ software, Perkin Elmer. Screening performance of prior and posterior risks for early and late preeclampsia by using PREDICTOR software was shown by Receiver Operating Characteristics (ROC) curves. The estimation of detection rates and false positive rates of delivery with both preeclampsia and SGA was made.
Eight cases developed early preeclampsia (0.24%) and 35 were diagnosed as late preeclampsia (1.07%). Five with early preeclampsia and ten with late preeclampsia later delivered SGA newborns (0.46%); 84 without preeclampsia gave birth to the SGAs (2.57%). According to ROC curves, posterior risks performed better than prior risks in terms of preeclampsia, especially in early preeclampsia. At 10% false positive rate, detection rates of early and late preeclampsia were 87.50 and 48.57%, detection rates of early and late SGA were 41.67 and 28.00%, respectively. For SGA, detection rates in cases with preeclampsia were much higher than those in absence of it.
This study demonstrates that combined screening model could be useful for predicting early preeclampsia in Chinese pregnancies. Furthermore, the performance of SGA screening by same protocol is strongly associated with preeclampsia.