Cargando…
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: | , , , , , , , , |
---|---|
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 |
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. |
---|