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ACCURACY OF NON-INVASIVE PRENATAL TESTING USING MASSIVELY PARALLEL SEQUENCING FOR DETECTING TRISOMY 21: A META-ANALYSIS Almira Clarissa Sungkono; Agriefa Chrysantia Noormay El Kariim; Novia Tria Nurcahya
Journal of Innovation Research and Knowledge Vol. 5 No. 8 (2026): Januari 2026
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/jirk.v5i8.12110

Abstract

Background:Non-Invasive Prenatal Testing (NIPT) for fetal trisomy 21 aneuploidy has been widely adopted in clinical practice due to its superior accuracy. NIPT has also been developed and validated as an option for early detection of genetic abnormalities prior to invasive diagnostic procedures. The aim of this study was to evaluate the accuracy of NIPT using Massively Parallel Sequencing (MPS) technology for screening Down syndrome in singleton pregnancies across all trimesters. Methods:This systematic review and meta-analysis analyzed literature on the accuracy of NIPT with MPS technology for Down syndrome screening in singleton pregnancies across all trimesters, following PRISMA guidelines. Eight studies were included, and data extraction was performed independently by three reviewers. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Results:Among 485,365 pregnant women screened for major autosomal trisomies confirmed by fetal karyotype or newborn phenotype, 2,092 cases were verified from the total population. The sensitivity of NIPT for detecting trisomy 21 ranged from 0.80 (95% CI: 0.73–0.87) to 1.00 (95% CI: 0.48–1.00) based on the eight identified studies. NIPT showed very high specificity, with most studies reporting a specificity of 1.00 (95% CI: 1.00–1.00). Conclusion: NIPT using MPS technology demonstrated very high sensitivity and specificity in detecting trisomy 21 (Down syndrome) in singleton pregnancies across all trimesters. It is a reliable and effective screening tool due to its high accuracy in detecting true-positive cases and minimizing false-positive results.