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Abstract

The Status of Quality Control Investigation and Analysis for Maternal Serum Marker of Prenatal Screening Laboratories in China by Falin He, Wei Wang, Kun Zhong, Shuai Yuan, Zhiguo Wang

Background: This national survey was initiated to investigate the current status of quality control practice of prenatal screening by statistical analysis of the previous half year data of prenatal screening in 2015.
Methods: Data were sent to all Chinese prenatal screening centers via the National Quality Assessment Scheme. This covered the software used, the risk cutoffs, monthly sample throughput, monthly median MoM of AFP, HCG, β-HCG, free β-HCG and uE3, monthly screening positive rates for trisomy 21, trisomy 18, and Open Neural Tube Defect (ONTD).
Results: Screening protocols were versatile, 73.5% (133/181) used the two-marker model, 24.3% (44/181) used the three-marker model, and 2.2% used the four-marker model. Regarding the software used, 350 laboratories never updated the screening parameters, 89 laboratories had updated their median or parameter by manufacturers, and 24 laboratories had updated the parameters by themselves. Cutoffs differ between laboratories. 59.9% (275/459) use 1/270 as their cutoffs for trisomy 21. 66.2% (296/447) use 1/350 as their cutoff for trisomy 18. 96.5% (361/374) use cutoffs between 2.0 - 2.5 MoM for ONTD. Regarding the results of the monthly median MoM, the percentage of laboratories for which all six monthly median MoMs were within the target of 0.90 - 1.10 was 46.7% (155/332) for AFP, 20.0% (4/20) for hCG, 29.2% (28/96) for β-HCG, 15.7% (31/198) for free β-HCG, and 4.8% (11/228) for uE3. The percentage of laboratories for which all six monthly median MoMs were within the target of 0.95 - 1.05 was 14.2% (47/332) for AFP, 0% (0/20) for HCG, 4.3% (4/96) for β-HCG, 12.6% (31/198) for free β-HCG, and 4.8% (11/228) for uE3. Regarding the screening positive rate, there was a difference in the trisomy 21 positive rate in the same laboratory within the six month.
Conclusions: There were variations in the types of screening protocols, different kinds of soft platforms, randomness of choice or update of medians or other important parameters, and great difference in the awareness of quality control. Effective and practical quality control measures would help laboratories improve quality control.

DOI: 10.7754/Clin.Lab.2016.160716