Cohen Jennifer L, Smilen Kaila E, Bianco Angela T, Moshier Erin L, Ferrara Lauren A, Stone Joanne L
The Mount Sinai Hospital, Department of Obstetrics, Gynecology and Reproductive Science, Division of Maternal & Fetal Medicine, New York, NY, United States.
The Mount Sinai Hospital, Department of Obstetrics, Gynecology and Reproductive Science, Division of Maternal & Fetal Medicine, New York, NY, United States.
Eur J Obstet Gynecol Reprod Biol. 2014 Oct;181:89-94. doi: 10.1016/j.ejogrb.2014.07.018. Epub 2014 Jul 31.
To determine if a combination of first and second trimester serum biomarkers (pregnancy-associated plasma protein A (PAPP-A), free βhCG, and maternal serum alpha-fetoprotein (msAFP)) may be utilized to develop a predictive model for adverse pregnancy outcomes.
We conducted a retrospective analysis including all women who delivered at our institution between 2007 and 2010. We estimated the area under the ROC curve (AUC) to compare predictive abilities of PAPP-A, free βhCG, and msAFP singularly, and in combination for adverse pregnancy outcomes. We sought to predict the risks of preeclampsia, preterm delivery (PTD, <37 weeks gestational age) and low birth weight (LBW, <2500g). Using logistic regression analysis, we created models that controlled for maternal age, race, parity, body mass index, and histories of chronic hypertension and tobacco use.
The final sample included 2199 women. Determining the AUC and optimal cutoff probability values for each of the biomarkers, we found that for PTD and LBW, the combination of all three biomarkers was most predictive, while for preeclampsia the combination of msAFP and PAPP-A was most predictive. The AUC of the three biomarker combination to detect adverse pregnancy outcomes are as follows: LBW 67%, PTD 72%, and preeclampsia 77%. We created race-specific logistic regression models to predict the risk probabilities. To illustrate, the predictive probability for a 33-year-old African American, nullipara with a BMI of 50, chronic hypertension, tobacco use, PAPP-A 0.3, msAFP 2.0 and free βhCG 0.98 MOMs are: PTD 59%, LBW 61% and Preeclampsia 91%.
The combination of biomarkers currently utilized in Down syndrome screening may also be used to predict additional adverse pregnancy outcomes. Further studies are needed to determine optimal maternal and fetal surveillance, if and when increased risks are identified.
确定孕早期和孕中期血清生物标志物（妊娠相关血浆蛋白A（PAPP-A）、游离β人绒毛膜促性腺激素（βhCG）和母体血清甲胎蛋白（msAFP））的组合是否可用于建立不良妊娠结局的预测模型。
我们进行了一项回顾性分析，纳入了2007年至2010年在我院分娩的所有女性。我们估计了受试者工作特征曲线（ROC曲线）下面积（AUC），以比较PAPP-A、游离βhCG和msAFP单独及联合对不良妊娠结局的预测能力。我们试图预测先兆子痫、早产（PTD，孕龄<37周）和低出生体重（LBW，<2500g）的风险。使用逻辑回归分析，我们创建了控制产妇年龄、种族、产次、体重指数以及慢性高血压和吸烟史的模型。
最终样本包括2199名女性。确定每种生物标志物的AUC和最佳截断概率值后，我们发现，对于早产和低出生体重，三种生物标志物的组合预测性最强，而对于先兆子痫，msAFP和PAPP-A的组合预测性最强。三种生物标志物组合检测不良妊娠结局的AUC如下：低出生体重为67%，早产为72%，先兆子痫为77%。我们创建了种族特异性逻辑回归模型来预测风险概率。举例来说，一名33岁、非裔美国籍、未生育、体重指数为50、患有慢性高血压、吸烟、PAPP-A为0.3、msAFP为2.0且游离βhCG为0.98中位数倍数（MOMs）的女性，其早产的预测概率为59%，低出生体重的预测概率为61%，先兆子痫的预测概率为91%。
目前用于唐氏综合征筛查的生物标志物组合也可用于预测其他不良妊娠结局。如果确定风险增加，需要进一步研究以确定最佳的母胎监测方法。
