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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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 |
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author | 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 |
author_facet | 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 |
author_sort | Yang, So-Yun |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9737181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97371812022-12-11 Combined Model-Based Prediction for Non-Invasive Prenatal Screening 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 Int J Mol Sci Communication 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. MDPI 2022-11-30 /pmc/articles/PMC9737181/ /pubmed/36499318 http://dx.doi.org/10.3390/ijms232314990 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication 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 Combined Model-Based Prediction for Non-Invasive Prenatal Screening |
title | Combined Model-Based Prediction for Non-Invasive Prenatal Screening |
title_full | Combined Model-Based Prediction for Non-Invasive Prenatal Screening |
title_fullStr | Combined Model-Based Prediction for Non-Invasive Prenatal Screening |
title_full_unstemmed | Combined Model-Based Prediction for Non-Invasive Prenatal Screening |
title_short | Combined Model-Based Prediction for Non-Invasive Prenatal Screening |
title_sort | combined model-based prediction for non-invasive prenatal screening |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737181/ https://www.ncbi.nlm.nih.gov/pubmed/36499318 http://dx.doi.org/10.3390/ijms232314990 |
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