What are the predominant parameters for Down syndrome risk estimation in first-trimester screening: a data mining study

Abstract

Abstract Objectives This study aimed to evaluate the effect size of each parameter used in the first trimester Down syndrome (DS) risk analyses by using multiple regression analysis techniques. Methods This data mining study included data of 44,260 pregnant women screened at the Acibadem Labmed laboratories from 2010 to 2019. In this study, risk was calculated using the PRISCA software on the basis of nuchal translucency (NT), crown-rump length measurement, in vitro fertilization application, diabetes mellitus, Down syndrome story, smoking, maternal age, and the level of maternal serum biochemistry markers including pregnancy-associated plasma protein-A (PAPP-A) and free beta-human chorionic gonadotropin (hCGβ). Results Forty-four thousand two hundred sixty risk analysis patients result data were re-investigate, and 851 (1.93%) risk analysis results were found as positive. PAPP-A 747 (CI%, 476–1,170) times, NT value 512 (CI%, 343–764) times, DS story 21 times (CI%, 6.7–63.2) and hCGβ value 7.01 (CI%, 6.31–7.79) times affect the combined first-trimester risk analysis results. Conclusions We have suggested that those accurate PAPP-A levels and NT levels evaluation are the most critical point of combined risk analysis and that the risk of free hCGβ levels after PAPP-A is essential as a biochemical test.