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Modification of non-invasive prenatal screening of Down syndrome: New approach using data mining analysis
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Fatemeh Karami   , Nafiseh Sedaghat  , Sedigheh Kolivand , Maryam Esmaeili , Sarang Younesi , Mohammad Hossein Modarressi * |
| Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran , modaresi@tums.ac.ir |
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Abstract: (3656 Views) |
Background: The introduction of next generation sequencing (NGS) in recent decade to determine fetal aneuploidies through cell free fetal DNA (cffDNA) in maternal circulation has caused new challenges for conventional prenatal first and trimester screening. Limiting the conventional screening tests to the most powerful criteria would be an appropriate strategy in reducing the time around and cost of traditional tests before non-invasive NGS method.
Methods: In this study, the most important factors affecting the risk of Down syndrome was found using statistical and data mining analysis of pregnant women undergoing conventional prenatal screening.
Results: First trimester proteinuria, previous history of Down syndrome, consanguinity, nuchal translucency (NT) and inhibin-A were the most significant factors identified to be associated with the risk of Down syndrome.
Conclusion: Incorporating those critical factors into new screening software could be valuable in advance of cffDNA testing as a perfect accurate non-invasive prenatal screening. |
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| Keywords: Data Mining, Down syndrome, Prenatal screening, Risk factor |
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Full-Text [PDF 199 kb]
(896 Downloads)
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Type of Study: Original Research |
Subject:
Reproductive Health
Received: 2020/03/20 | Accepted: 2020/04/28 | Published: 2020/05/28
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