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早发型子痫前期的预测中,第一孕期生化标记物和平均动脉压的表现。

Performance of first trimester biochemical markers and mean arterial pressure in prediction of early-onset pre-eclampsia.

机构信息

Department of Obstetrics and Gynecology, Oulu University Hospital, Finland.

PerkinElmer, Mustionkatu 6, 20750 Turku, Finland.

出版信息

Metabolism. 2017 Oct;75:6-15. doi: 10.1016/j.metabol.2017.07.004. Epub 2017 Jul 18.

DOI:10.1016/j.metabol.2017.07.004
PMID:28964327
Abstract

OBJECTIVE

To develop a predictive risk model for early-onset pre-eclampsia (EO-PE) using maternal characteristics, combined screening markers, previously reported biomarkers for PE and mean arterial pressure (MAP).

METHODS

This retrospective study was conducted at Oulu University hospital between 2006 and 2010. Maternal serum from first trimester combined screening was further analyzed for alpha fetoprotein (AFP), placental growth factor (PlGF), soluble tumor necrosis factor receptor-1 (sTNFR1), retinol binding protein-4 (RBP4), a disintegrin and metalloprotease-12 (ADAM12), soluble P-selectin (sP-selectin), follistatin like-3 (FSTL3), adiponectin, angiopoietin-2 (Ang-2) and sex hormone binding globulin (SHBG). First, the training sample set with 29 cases of EO-PE and 652 controls was developed to study whether these biomarkers separately or in combination with prior risk (maternal characteristics, first trimester pregnancy associated plasma protein-A (PAPP-A) and free beta human chorionic gonadotrophin (fβ-hCG)) could be used to predict the development of EO-PE. Second, the developed risk models were validated with a test sample set of 42 EO-PE and 141 control subjects. For the test set MAP data was also available.

RESULTS

Single marker statistically significant (ANOVA p<0.05) changes between control and EO-PE pregnancies were observed with AFP, RBP4 and sTNFR1 with both training and test sample sets. Based on the test sample set performances, the best detection rate, 47% for a 10% false positive rate, was achieved with PlGF and sTNFR1 added with prior risk and MAP.

CONCLUSION

Based on our results, the best first trimester biomarkers to predict the subsequent EO-PE were AFP, PlGF, RBP4 and sTNFR1. The risk models that performed best for the prediction of EO-PE included prior risk, MAP, sTNFR1 and AFP or PlGF or RBP4.

摘要

目的

利用母体特征、联合筛查标志物、先前报道的子痫前期生物标志物和平均动脉压(MAP),开发一种用于预测早发型子痫前期(EO-PE)的风险预测模型。

方法

本回顾性研究于 2006 年至 2010 年在奥卢大学医院进行。进一步分析了第一孕期联合筛查的母体血清中的甲胎蛋白(AFP)、胎盘生长因子(PlGF)、可溶性肿瘤坏死因子受体-1(sTNFR1)、视黄醇结合蛋白-4(RBP4)、解整合素金属蛋白酶 12(ADAM12)、可溶性 P 选择素(sP-selectin)、卵泡抑素样蛋白 3(FSTL3)、脂联素、血管生成素-2(Ang-2)和性激素结合球蛋白(SHBG)。首先,使用 29 例 EO-PE 和 652 例对照的训练样本集来研究这些生物标志物单独或与先前的风险(母体特征、第一孕期妊娠相关血浆蛋白-A(PAPP-A)和游离β人绒毛膜促性腺激素(fβ-hCG))结合是否可以预测 EO-PE 的发生。其次,使用包含 42 例 EO-PE 和 141 例对照的测试样本集验证开发的风险模型。对于测试集,还可以获得 MAP 数据。

结果

在训练和测试样本集中,与 EO-PE 妊娠相比,AFP、RBP4 和 sTNFR1 的单标记统计差异显著(ANOVA p<0.05)。基于测试样本集的表现,在 10%假阳性率下,PlGF 和 sTNFR1 与先前的风险和 MAP 结合可达到最佳检测率 47%。

结论

根据我们的结果,预测随后 EO-PE 的最佳第一孕期生物标志物是 AFP、PlGF、RBP4 和 sTNFR1。用于预测 EO-PE 的最佳风险模型包括先前的风险、MAP、sTNFR1 以及 AFP 或 PlGF 或 RBP4。

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