Evaluation of interpretation methods to improve accuracy of the prenatal BACs‑on‑Beads™ assay in prenatal diagnosis
- Yu Jiang
- Jian Zhang
- Lili Wu
- Wenbo Wang
- Qiwei Guo
Affiliations: Prenatal Diagnosis Centre, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, Fujian 361003, P.R. China, Department of Obstetrics and Gynecology, Women and Children's Hospital, School of Medicine, Xiamen University, Xiamen, Fujian 361003, P.R. China, Department of Experimental Medicine, United Diagnostic and Research Center for Clinical Genetics, School of Public Health, Xiamen University, Xiamen, Fujian 361102, P.R. China
- Published online on: December 3, 2020 https://doi.org/10.3892/etm.2020.9553
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Prenatal BACs‑on‑Beads™ (PNBoBs™) technology has been approved for use in routine clinical prenatal diagnosis in numerous countries. However, the influence of data interpretation on the accuracy of the results remains to be evaluated. The present study aimed to determine the accuracy of existing data interpretation approaches and develop an optimization method to improve the performance of the PNBoBs™ assay in prenatal diagnosis. A total of 2,289 prenatal cases with known karyotypes and raw ratio data from PNBoBs™ assays were recruited for the present study. Positive results, according to the data interpretation methods used for the PNBoBs™ test, were validated against current gold‑standard approaches. Statistical analyses were then performed to evaluate the accuracy of existing methods in data interpretation to provide a basis for the optimization of a follow‑up approach. Among the existing methods, the ‘trimmed standard deviation threshold’ approach had the highest sensitivity and false‑positive rates, with 98.1 and 4.2%, respectively. The ‘n‑1 or greater probes’ rule had the highest specificity (99.7%) and the second‑highest false‑negative rate (11.5%). The method optimized in the present study provided a reasonable balance between sensitivity (98.1%) and specificity (99.6%) with regards to the interpretation of the data obtained from the PNBoBs™ assay. The results indicated that the present optimization method outperforms existing approaches in data interpretation for the PNBoBs™ assay, and as a result, may reduce unnecessary verification turnaround time and cost in prenatal diagnosis.