Heidari Reza, Akbariqomi Mostafa, Motevaseli Elaheh, Omrani Mir Davood, Kooshki Hamid, Shamshiri Ahmad Reza, Shafei Shilan, Absalan Moloud, Mazlomi Mohammad Ali, Saleh Gargari Soraya, Tavoosidana Gholamreza
Department of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
J Family Reprod Health. 2018 Sep;12(3):121-128.
To investigate the performance of first trimester Down syndrome (DS) screening markers in Iranian pregnancies.Although sonographic and serum markers are currently recommended for the first trimester screening of Down syndrome, the screening performance of the markers depends on the race and ethnicity. A retrospective case-control study using first trimester screening results recorded with the prenatal diagnostic multi-centers in Iran. A total of 6,384 pregnant women were examined from March 2012 to February 2017. Totally 100 Down syndrome cases and 266 matched controls were selected and the maternal characteristics, sonographic and biochemical screening data were collected. Statistical analysis was performed using logistic regression and descriptive statistics. A decision tree model was designed using the chi-squared automatic interaction detection method based on serum markers. For screening of DS pregnancies, PAPP-A (cut-off 0.795 MoM) yielded the highest sensitivity (86%) and NB marker presented highest specificity (96.24%). combination of the biochemical markers PAPP-A and β-hCG (cut-off: 1.55 MoM) showed the highest sensitivity over other combined markers. The decision-tree model based on serum markers improved (91% DR For a 5% FPR) first trimester screening performance. The novel decision-tree model base on serum markers revealed a better predictive value to achieve high sensitivity and specificity of first trimester Down syndrome screening in Iranian population.
探讨孕早期唐氏综合征(DS)筛查标志物在伊朗孕妇中的表现。尽管目前推荐超声和血清标志物用于孕早期唐氏综合征筛查,但这些标志物的筛查性能取决于种族和民族。一项回顾性病例对照研究,使用伊朗产前诊断多中心记录的孕早期筛查结果。2012年3月至2017年2月期间,共检查了6384名孕妇。共选择了100例唐氏综合征病例和266例匹配对照,并收集了产妇特征、超声和生化筛查数据。使用逻辑回归和描述性统计进行统计分析。基于血清标志物,采用卡方自动交互检测方法设计了决策树模型。对于DS妊娠筛查,妊娠相关血浆蛋白A(PAPP - A,截断值0.795 MoM)的敏感性最高(86%),颈部透明带(NB)标志物的特异性最高(96.24%)。生化标志物PAPP - A和β - 人绒毛膜促性腺激素(β - hCG,截断值:1.55 MoM)的组合在其他联合标志物中显示出最高的敏感性。基于血清标志物的决策树模型提高了孕早期筛查性能(5%假阳性率下的检出率为91%)。基于血清标志物的新型决策树模型显示出更好的预测价值,可在伊朗人群中实现孕早期唐氏综合征筛查的高敏感性和特异性。