Objective:To investigate the current status of preimplantation genetic testing for aneuploidies (PGT-A) in China in 2024 and to provide recommendations for ensuring the consistency of PGT-A results.Methods:This study was a nationwide external quality assessment research. The National Center for Clinical Laboratories of the National Health Commission conducted two surveys in June and December 2024, with participation from 31 laboratories across China. During each survey, quality control samples of varying concentrations were distributed: the first survey distributed 6 samples (Batch Nos. 202401-202406) and the second survey distributed 3 samples (Batch Nos. 202431-202433). Participating laboratories were required to submit information including detection platforms, single-cell amplification methods, library construction methods, sequencing instruments, and test results. Collected data were statistically analyzed using Microsoft Excel to evaluate laboratories' PGT-A testing capabilities and determine whether results met predefined quality control requirements.Results:All 31 laboratories submitted results for both surveys. In the first survey, 90.3% (28/31) met qualification criteria with a 9.7% failure rate (3/31). For individual batches, pass rates were 90.3% (28/31) for batches 202401-202403 and 100% (31/31) for batches 202404-202406. The second survey achieved 100% (31/31) compliance across all three batches (202431-202433), with each batch maintaining a 100% pass rate.Conclusion:The detection quality of PGT-A in China is generally good, but with differences, and factors such as sample concentration, transportation conditions and detection methods affect the consistency of the results. The study highlights the urgent need for nationwide external quality assessment of PGT-A in China. This will help identify issues in laboratories in a timely manner and ensure the consistency of PGT-A test results.

Objective:To analyze the quality level of maternal mid-trimester serum prenatal screening in China from 2019 to 2023.Methods:A questionnaire survey was conducted to collect information from laboratories participating in the National Health Commission′s Clinical Laboratory Center inter-laboratory quality assessment program for prenatal screening from 2019 to 2023. The collected data included screening protocols, detection methods, testing systems, and monthly laboratory screening quality indicators. The Chi-square test was used to compare the initial screening positive rates among different screening protocols, provinces, detection methods, and testing systems. A log-transformed linear regression analysis was performed to evaluate the relationship between the average annual sample size and the out-of-control rate of various median multiple of the median (mMoM) values.Results:This study included 806 laboratories from 29 provinces (including autonomous regions and municipalities). The five-year average out-of-control rates for mMoM values across indicators ranged from 15.8% to 31.3%. The initial positive rates of dual, triple, and quadruple screening protocols were statistically different ( χ2=760.2, P<0.001). The initial positive rates across different provinces ranged from 4.7% to 10.3%, with statistically significant differences ( χ2=35 388.0, P<0.001). There were also statistically significant differences in initial positive rates between different testing systems ( χ2=2 493.2, P<0.001). Testing systems using chemiluminescence methods had significantly higher initial positive rates compared to systems using time-resolved fluorescence methods (7.2% vs. 6.5%, χ2=533.6, P<0.001). Log-linear regression analysis showed that testing systems with larger annual average sample sizes had lower out-of-control rates for mMoM values (AFP: β=-0.100, P=0.005; hCG: β=-0.123, P=0.008; uE3: β=-0.139, P=0.007). Conclusion:There are significant differences in the quality of maternal mid-trimester serum screening across different detection methods, testing systems and provinces in China.

Objective:To investigate the current status of preimplantation genetic testing for aneuploidies (PGT-A) in China in 2024 and to provide recommendations for ensuring the consistency of PGT-A results.Methods:This study was a nationwide external quality assessment research. The National Center for Clinical Laboratories of the National Health Commission conducted two surveys in June and December 2024, with participation from 31 laboratories across China. During each survey, quality control samples of varying concentrations were distributed: the first survey distributed 6 samples (Batch Nos. 202401-202406) and the second survey distributed 3 samples (Batch Nos. 202431-202433). Participating laboratories were required to submit information including detection platforms, single-cell amplification methods, library construction methods, sequencing instruments, and test results. Collected data were statistically analyzed using Microsoft Excel to evaluate laboratories' PGT-A testing capabilities and determine whether results met predefined quality control requirements.Results:All 31 laboratories submitted results for both surveys. In the first survey, 90.3% (28/31) met qualification criteria with a 9.7% failure rate (3/31). For individual batches, pass rates were 90.3% (28/31) for batches 202401-202403 and 100% (31/31) for batches 202404-202406. The second survey achieved 100% (31/31) compliance across all three batches (202431-202433), with each batch maintaining a 100% pass rate.Conclusion:The detection quality of PGT-A in China is generally good, but with differences, and factors such as sample concentration, transportation conditions and detection methods affect the consistency of the results. The study highlights the urgent need for nationwide external quality assessment of PGT-A in China. This will help identify issues in laboratories in a timely manner and ensure the consistency of PGT-A test results.

Objective:To analyze the quality level of maternal mid-trimester serum prenatal screening in China from 2019 to 2023.Methods:A questionnaire survey was conducted to collect information from laboratories participating in the National Health Commission′s Clinical Laboratory Center inter-laboratory quality assessment program for prenatal screening from 2019 to 2023. The collected data included screening protocols, detection methods, testing systems, and monthly laboratory screening quality indicators. The Chi-square test was used to compare the initial screening positive rates among different screening protocols, provinces, detection methods, and testing systems. A log-transformed linear regression analysis was performed to evaluate the relationship between the average annual sample size and the out-of-control rate of various median multiple of the median (mMoM) values.Results:This study included 806 laboratories from 29 provinces (including autonomous regions and municipalities). The five-year average out-of-control rates for mMoM values across indicators ranged from 15.8% to 31.3%. The initial positive rates of dual, triple, and quadruple screening protocols were statistically different ( χ2=760.2, P<0.001). The initial positive rates across different provinces ranged from 4.7% to 10.3%, with statistically significant differences ( χ2=35 388.0, P<0.001). There were also statistically significant differences in initial positive rates between different testing systems ( χ2=2 493.2, P<0.001). Testing systems using chemiluminescence methods had significantly higher initial positive rates compared to systems using time-resolved fluorescence methods (7.2% vs. 6.5%, χ2=533.6, P<0.001). Log-linear regression analysis showed that testing systems with larger annual average sample sizes had lower out-of-control rates for mMoM values (AFP: β=-0.100, P=0.005; hCG: β=-0.123, P=0.008; uE3: β=-0.139, P=0.007). Conclusion:There are significant differences in the quality of maternal mid-trimester serum screening across different detection methods, testing systems and provinces in China.

Objective:To evaluate the quality level of early pregnancy serum screening in China.Methods:Information on the coefficient of variation, bias, quality control (QC) rules, and testing methods from 576 laboratories participating in the 2022 early pregnancy serum screening inter-laboratory proficiency testing program by the National Health Commission Clinical Laboratory Center was collected. Serological screening indicators included free human chorionic gonadotropin β subunit (β-hCG), total β-hCG, and pregnancy-associated plasma protein A (PAPP-A). Six Sigma (σ) management was used to assess the quality level of the laboratories and the rationality of QC rules.Wilcoxon test was used to evaluate whether different testing time and methods affected the Sigma level.Results:A total of 119 laboratories tested total β-hCG, 457 laboratories tested free β-hCG, and 565 laboratories tested PAPP-A. Seventeen laboratories tested only one marker, 553 laboratories tested two markers, and six laboratories tested three markers. There was no statistically significant difference in sigma levels for the same analyte tested in May and September. The proportion of free β-hCG reaching 6σ was the highest at 71.9% (567/788); although total β-hCG had the lowest proportion reaching 6σ at 53.4% (103/193), it also had the lowest proportion below 3σ at 3.1% (6/193). Early pregnancy serum prenatal screening mainly involved five reagents and primarily used chemiluminescence and time-resolved fluorescence methods (free β-hCG was only tested using chemiluminescence). Laboratories using time-resolved fluorescence had overall higher sigma levels [total β-hCG: 9.56 (7.01-13.22) vs. 5.84 (4.36-9.12), W=53 114.00; PAPP-A: 9.04 (6.40-12.62) vs. 5.71 (4.22-8.15), W=75 752.00; both P<0.001] compared to those using chemiluminescence. The proportion of QC rules conforming to Westgard sigma rules ranged from 16.1% (31/193) to 19.6% (166/846). Among them, the proportion of laboratories with overly lenient QC rules was 24.8% (210/846) to 32.1% (62/193), and the proportion with overly strict QC rules was 51.8% (100/193) to 55.6% (470/846). Conclusion:The overall QC level of prenatal screening laboratories in China is fine, but there is still room for improvement in the setting of QC rules.

Objective To discuss how to plot a power function graph and draw power function graphs corresponding to common quality control rules to assist medical laboratories in selecting quality control rules.Methods Commonly used quality control rules in clinical laboratory testing in China were collected,power function graphs based on the Monte Carlo method were plotted,and the simulation results with existing results were compared and tested the reliability of the method.Results The Monte Carlo method could be used to easily plot power function graphs for the most complex quality control rules such as 13s/22s/R4s/41s/8(x-).This method had a high level of accuracy,but the accuracy and precision were positively correlated with the number of simulations.In terms of statistical proportions of seven commonly used quality control rules,the 13s/22srule had the highest usage proportion,followed by the 13s/22s/R4s.The power function graph corresponding to the 13s/22s/R4s/41s/10(x-) rule was plotted,and the sigma level lines were marked to assist the laboratory in selecting quality control rules.Conclusion The Monte Carlo method accurately plotted power function graphs,and medical laboratories could use this method to independently plot efficiency function graphs to meet quality control requirements.

Humans ; Infant, Newborn ; Neonatal Screening ; China

This article reviews the emerging artificial intelligence (AI) technology and its application in the field of aneuploidy prenatal screening from the aspects of the research methods of AI, the status of prenatal screening, and the role of AI in the integration of the screening markers, improvement of the screening performance, and optimization of screening strategy, etc. There is no doubt that AI has great potential in improving the ability of disease prediction through, integrating various screening data, discovering additional value of the data, and reducing social medical expenses. However, AI technology should be viewed and used in a scientific, rational, and comprehensive way to achieve the ideal effect in the field of prenatal screening.

Objective:To investigate the use of the reference intervals for blood cell counting and the reference of industry standard in China.Methods:Information from all laboratories was collected using online questionnaire in 18 reference intervals survey in blood cell counting in 2019. The information includes the source of the reference intervals, the verification of the reference intervals, and the upper and lower limits of the reference intervals, the method used, the instrument, the reagent and the calibrator. Microsoft Excel 2007 software was used to analyze the results of all laboratories. The median and 95% confidence interval were calculated. The distribution of the reference intervals for blood cell counting and their conformance to industry standards were analyzed.Results:2, 869 labs reported the data. The main sources were industry standards and National Guide to Clinical Laboratory Procedures. The proportion was 33.30%-35.02% and 28.55%-30.90% respectively. 49.44%-55.13% of laboratories validated the reference interval when citing industry standards. The reference interval grouping of most laboratories (89.37%-91.69%) cited in RBC, Hgb and Hct were consistent with the industry standards. We compared the upper and lower limits of the reference intervals with that given by the industry standards, when the lower limit of the reference intervals of mean corpuscular hemoglobin concentration, absolute neutrophils count, absolute basophils count, absolute monocyte count, and lymphocyte percentage were compared. The upper limit of reference intervals of neutrophils percentage as well as upper and lower limits of reference intervals of mean corpuscular volume, mean corpuscular hemoglobin, absolute eosinophil count, basophils percentage, and monocyte percentage were also compared. The median and mode were equal and consistent with industry standards. For other labs, the upper and lower limits of the reference intervals were not consistent with the reference intervals given by the industry standards.Conclusion:The use of reference intervals for blood cell counting was not the same, and the implementation of industry standards was not optimistic. A considerable number of laboratories had not verified the reference intervals, so it was necessary to promote the industry standards for reference intervals.

Objective To eva1uate the external quality assessment results of prenatal screening for maternal serum inhibin A in the second trimester in 2018 and to improve the accuracy of prenatal screening.Methods National Center for Clinical Laboratories provided three batches of quality control urine sample (Lot:201811-201813) to 94 prenatal screening laboratories nationwide in March 2018.Laboratories participated in the assessment voluntarily and reported the results,methods,equipment,reagents and other related information as required.Clinet EQA and Microsoft Excel 2010 were used for statistical analysis of the laboratory test results and for descriptive evaluation of the accuracy rate.Results A total of 55 laboratories submitted their testing results giving a return rate of 58.5％ (55/94),of which 52 (94.5％) were consistent with the expected results,while none of the results submitted by the other three laboratories was accurate.At the mean time,the bias of all three batches in each laboratory fell into the same side (two laboratories showed negative bias and one positive bias).Conclusions The results of the external quality assessment of prenatal screening for maternal serum inhibin A are generally satisfactory except for a few laboratories.It is necessary to incorporate prenatal screening for maternal serum inhibin A in the second trimester into the formal external quality assessment plan and regularly monitor the level of its detection quality.