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Combined Model-Based Prediction for Non-Invasive Prenatal Screening

The risk of chromosomal abnormalities in the child increases with increasing maternal age. Although non-invasive prenatal testing (NIPT) is a safe and effective prenatal screening method, the accuracy of the test results needs to be improved owing to various testing conditions. We attempted to achie...

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Detalles Bibliográficos
Autores principales: Yang, So-Yun, Kang, Kyung Min, Kim, Sook-Young, Lim, Seo Young, Jang, Hee Yeon, Hong, Kirim, Cha, Dong Hyun, Shim, Sung Han, Joung, Je-Gun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737181/
https://www.ncbi.nlm.nih.gov/pubmed/36499318
http://dx.doi.org/10.3390/ijms232314990
Descripción
Sumario:The risk of chromosomal abnormalities in the child increases with increasing maternal age. Although non-invasive prenatal testing (NIPT) is a safe and effective prenatal screening method, the accuracy of the test results needs to be improved owing to various testing conditions. We attempted to achieve a more accurate and robust prediction of chromosomal abnormalities by combining multiple methods. Here, three different methods, namely standard Z-score, normalized chromosome value, and within-sample reference bin, were used for 1698 reference and 109 test samples of whole-genome sequencing. The logistic regression model combining the three methods achieved a higher accuracy than any single method. In conclusion, the proposed method offers a promising approach for increasing the reliability of NIPT.