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Reproducibility of Risk Figures in 2nd-Trimester Maternal Serum Screening for Down Syndrome: Comparison of 2 Laboratories

¹ Division of Human Genetics, Department of Genetics and Developmental Biology, ² Department of Laboratory Medicine, and ³ Department of Obstetrics and Gynecology, University of Connecticut Health Center, Farmington, CT.
⁴ Department of Mathematics and Statistics, University of Plymouth, Plymouth, United Kingdom.

^aAddress correspondence to this author at: University of Connecticut Health Center, Division of Human Genetics, Department of Genetics and Developmental Biology, 263 Farmington Ave., Farmington, CT 06030-6140. Fax 860-679-3616; e-mail Benn{at}nso1.uchc.edu.

Background: Analytical error affects 2nd-trimester maternal serum screening for Down syndrome risk estimation. We analyzed the between-laboratory reproducibility of risk estimates from 2 laboratories.

Methods: Laboratory 1 used Bayer ACS180 immunoassays for -fetoprotein (AFP) and human chorionic gonadotropin (hCG), Diagnostic Systems Laboratories (DSL) RIA for unconjugated estriol (uE3), and DSL enzyme immunoassay for inhibin-A (INH-A). Laboratory 2 used Beckman immunoassays for AFP, hCG, and uE3, and DSL enzyme immunoassay for INH-A. Analyte medians were separately established for each laboratory. We used the same computational algorithm for all risk calculations, and we used Monte Carlo methods for computer modeling.

Results: For 462 samples tested, risk figures from the 2 laboratories differed >2-fold for 44.7%, >5-fold for 7.1%, and >10-fold for 1.7%. Between-laboratory differences in analytes were greatest for uE3 and INH-A. The screen-positive rates were 9.3% for laboratory 1 and 11.5% for laboratory 2, with a significant difference in the patients identified as screen-positive vs screen-negative (McNemar test, P <0.001). Computer modeling confirmed the large between-laboratory risk differences.

Conclusion: Differences in performance of assays and laboratory procedures can have a large effect on patient-specific risks. Screening laboratories should minimize test imprecision and ensure that each assay performs in a manner similar to that assumed in the risk computational algorithm.

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