Impact of non-invasive prenatal testing in the detection of aneuploidy

被引:0
|
作者
Ortiz, C. Valldecabres [1 ]
Garcia, F. De la Fuente [1 ]
Pintado, S. Gorriz [1 ]
机构
[1] Hosp Univ Ribera, Area Diagnost Biol, Valencia, Spain
关键词
Aneuploidy; Prenatal testing; NIPT; Genetic diagnosis; CELL-FREE DNA; MATERNAL BLOOD;
D O I
10.1016/j.gine.2024.100985
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
Background: The non-invasive prenatal test (NIPT) is a screening test that allows for conducting a screening of major chromosomal abnormalities in the fetus during pregnancy using maternal blood. In February 2019, NIPT was included as part of the prenatal diagnosis for genetic anomalies during the first trimester of pregnancy by the Public Health System of the Valencian Community. The objective is to assess the diagnostic and economic performance of NIPT in pregnant women within our Department since its implementation. Methods: A retrospective observational study was conducted, analyzing NIPT performed since its integration into the screening for chromosomal abnormalities in pregnant women within our department. The analysis includes the number of invasive tests conducted, improvements in the detection of studied chromosomal abnormalities, and the economic feasibility in comparison to invasive testing. Results: A total of 4719 combined first and second-trimester screenings were conducted with a population coverage of 98%, of which TPNI was indicated in 337 patients. Aneuploidies were detected in 4 patients: two cases of Down syndrome, one case of Patau syndrome, and one case of Turner syndrome, with the first three confirmed and the latter resulting in a false positive. The sensitivity obtained was 100%, and the specificity was 99% (95% CI). The economic savings amounted to D 52,035.90. Conclusions: TPNI is a highly sensitive test with high specificity. Since its incorporation into the screening for aneuploidies in pregnant women, the performance of invasive tests has been reduced, resulting in a corresponding decrease in the risk of fetal loss and significant economic savings. (c) 2024 Elsevier Espana, S.L.U. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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