In Down’s syndrome (DS) screening, multi-variate Gaussian modeling is used to estimate the risk of an af­fected pregnancy from the marker profile, maternal age and family history. The most reliable models use parame­ters based on meta-analysis of published studies and tai­lored to the local screening population. In this paper the meta-analysis approach is extended to second trimester inhibin, combining first trimester pregnancy associated plasma protein (PAPP)-A, with second trimester markers, and ultrasound first trimester nuchal translucency (NT)and second trimester nuchal skin-fold (NF) thickness. The existing and updated meta-analysis parameters are used to predict screening performance for the related policies yielding a detection rate for a 5% false-positive as high as 90-93%.

Keywords: Down’s syndrome (DS); Screening; Pa­rameters; Modeling; Performance.