Qin Xuzhen, Tang Guodong, Qiu Ling, Li Peng Chang, Xia Liangyu, Chen Ming, Tao Zhihua, Li Shijun, Liu Min, Wang Liang, Gao Shang, Yu Songlin, Cheng Xinqi, Han Jianhua, Hou Li'an, Kawano Reo, Ichihara Kiyoshi
From the Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing (XQ, LQ, PL, LX, SY, XC, JH, LH); Beijing Hospital of the Ministry of Health (GT); Department of Clinical Laboratory, Third Affiliated Hospital of Third Military Medical University, Chongqing (MC); Department of Clinical Laboratory, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou (ZT); Department of Clinical Laboratory, The First Affiliated Hospital of Dalian Medical University, Dalian (SL); Department of Clinical Laboratory, The first Affiliated Hospital, Sun Yat-sen University, Guangzhou (ML); Department of Clinical Laboratory, Xinjiang Medical University, Urumuqi (LW); Department of Clinical Laboratory, Hospital of Beijing Prison Administration Bureau Qinghe Branch, China (SG); and Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Ube, Japan (KI).
Medicine (Baltimore). 2015 Dec;94(49):e2211. doi: 10.1097/MD.0000000000002211.
A multicenter study conducted in healthy population of 6 cities from the 4 corners and central China for 7 serum-specific proteins to identify the sources of variation and establish the reference intervals on 2 automation platforms.A total of 3148 subjects aged 19 to 64 years old were enrolled in this study to ensure at least 120 participants in each 10-year age group and each city. The majority of samples were transported to central laboratory and measured on both Beckman AU5800 and Immage 800 analytical systems. Three-level nested ANOVA, multiple regression analysis, and the scatter plot were used to explore the variations from sex, age, region, BMI, cigarette smoking, and so on. The latent abnormal value exclusion (LAVE) method was applied at the time of computing RIs as a method for secondary exclusion.Regionality was not observed in any of the immunoassay in China. Variations for sex were significant for IgM among the immune analytes. For CRP and hsCRP results with turbidimetry method (Beckman Coulter AU5800) were lower than the nephelometry method (Beckman Immage). The LAVE method did not affect the RIs computed for the majority of analytes except C4, CRP, and hsCRP. In the scatter plot at the age of 45 years old C3, C4, and IgM reached an inflection point, accordingly RIs were separated by the age group.With the lack of regional differences and the well-standardized status of test results, the RIs of C3, IgG, IgA, IgM derived from this nationwide study can be used for the entire Chinese population. C4, CRP, and hsCRP were affected by different platforms and gender was a significant source of variation for IgM, so they had separated RIs.
在中国中部和四个角落的6个城市的健康人群中开展了一项多中心研究，检测7种血清特异性蛋白，以确定变异来源并在2个自动化平台上建立参考区间。本研究共纳入3148名年龄在19至64岁之间的受试者，确保每个10岁年龄组和每个城市至少有120名参与者。大多数样本被运送到中心实验室，在贝克曼AU5800和Immage 800分析系统上进行检测。采用三级嵌套方差分析、多元回归分析和散点图来探讨性别、年龄、地区、体重指数、吸烟等因素的变异情况。在计算参考区间时采用潜在异常值排除（LAVE）方法作为二次排除方法。在中国，任何免疫测定中均未观察到地区差异。在免疫分析物中，IgM的性别差异显著。对于CRP和hsCRP，比浊法（贝克曼库尔特AU5800）的结果低于散射比浊法（贝克曼Immage）。LAVE方法对大多数分析物（除C4、CRP和hsCRP外）计算的参考区间没有影响。在散点图中，45岁时C3、C4和IgM达到拐点，因此参考区间按年龄组划分。由于缺乏地区差异且检测结果标准化良好，这项全国性研究得出的C3、IgG、IgA、IgM的参考区间可用于全体中国人群。C4、CRP和hsCRP受不同平台影响，IgM的性别是一个显著的变异来源，因此它们有不同的参考区间。
