正常孕妇中期产前筛查指标中位数数据库的建立

Establishment of median for the antepartum screening biomarkers in normal pregnant women

目的评价我国常用的3种国外产前筛查风险计算软件内嵌AFP、游离β-人绒毛膜促性腺激素（free-B-HCG）指标中位数数据库的差异，选择合适的产前筛查指标中位数计算模型，建立温州地区正常孕妇群产前筛查AFP、free-β-HCG指标中位数数据库。方法应用时间分辨荧光检测技术检测20054名正常孕妇群AFP、free-β-HCG含量，应用双因素方差分析比较本组数据与目前常用2T-risk（2T）、Lifeeycle-2．2（LC2．2）和Lifeeycle-3．0（LC3．0）3种风险软件中数据的差异，分析本组数据与国内沈阳、宁波区域数据是否存在差异，应用模型校正拟合度、模型拟合对数分布均数和标准差等指标，评价3个软件中配给的非线性回归模型的稳定性，选择适合本组数据的回归模型，建立温州地区孕妇群筛查指标中位数数据库。结果本组数据AFP、free-β-HCG测定值比2T软件内嵌中位浓度分别高10％和16％；比LC-2．2分别高15％和20％；比LC-3．0分别高6％和17％，差异有统计学意义（FAFP=161．757，P〈0．01；0．8IHcG=58．261，P〈0．01）。本组温州地区数据AFP、free-β-HCG浓度比我国沈阳地区高2％和低3％、比宁波高1％和2％，温州、沈阳、宁波3个区域数据之间AFP指标差异无统计学意义（FAFP=0．174，P=0．840），free-β-HCG指标3个地区间差异有统计学意义（Ffree HCc：13．303，P〈0．01）。2T、LC-2．2、LC-3．0风险软件中用于中位值计算的二次方程回归模型、指数二次函数回归模型、指数四次函数回归模型差别不大，以指数四次函数回归模型为佳。结论我国温州、沈阳、宁波3个区域筛查指标的数据与国外2TC、LC-2．2、LC-3．03个版本软件内嵌数据均存在显著差异，人种的不同和回归模型参数不同是造成差异的原因，我国需建立自己的模型参数和中位数数据库。我国温州、沈阳、宁波3个区域之间大样本的数据AFP指标差异无显著性，free-β-HCG指标稳定性较差，3个区域之间有些差异，温州、宁波数据较接近。提示我国小样本的实验室在相同实验条件情况下，可参考国内大样本数据建立自己实验室参数。3个软件内公认的回归计算模型稳定性差别不大，本组数据以指数四次函数回归模型为佳，可适用于同本组数据分布相似的我国其他筛查中心筛查指标中位数数据库的建立。

Objective To evaluate the differences of α-fetoprotein（ AFP）, freeβ-human chorionic gonadotropin （HCG） indexes in 3 foreign median databases for antepartum risk screening, and establish the median databases of normal pregnant women in Wenzhou for antepartum screening of AFP, free-13-HCG indexes through the suitable median computational models. Methods The levels of AFP and free 13-HCG of 20054 normal pregnant women in Wenzhou were detected by time-resolved fluorometry. The data in this paper were compared with the data of 2T-risk （2T）, Lifecycle-2. 2 （ LC2. 2 ） and Lifecycle -3.0 （ LC3.0 ） by double-factor ANOVA. The differences between the data in the paper and the data from Shenyang and Ningbo were analyzed. The median database of Wenzhou pregnant women was established by the suitable regression model, with the stability of nonlinear regression models of the 3 software assessed by model correcting fitting, distribution mean of model fitting logarithmic and standard deviation. Results The levels of AFP and freeβ- hCG reported here were 10% and 16% higher than the data of 2T-risk, 15% and 20% higher than that of LC 2. 2, 6% and 17% higher than that of LC 3.0 respectively. The differences were statistically significant. （ FAFP = 161. 757, P 〈 0. 01 ; Ffree-β-HCC = 58. 261, P 〈 0. 01 ）. The levels of AFP and free 13- hCG in Wenzhou were 2% higher and 3% lower than that of Shenyang, 1% and 2% higher than that of Ningbo. There was no statistical difference of AFP levels among Wenzhou , Shenyang and Ningbo（ FAFP = 0. 174, P = 0. 840 ） while the differences of free-β-hCG were statistically significant （Ffree-β-HCG = 13. 303, P 〈 0. 01 ）. The differences of quadratic equation regression model, exponent quadratic function regression model and exponent quadru-function regression model of 2T, LC-2. 2 and LC-3.0 were not remarkable. The exponent quadru-function regression model was the best. Conclusions There are significant differences between the data from Wenzhou, Shenyang and Ningbo and the data of T-2 risk, LC-2. 2, LC -3.0. The discrepancy is due to the ethnic and different parameters of regression models. So the model parameters and the median databases are urgently required in China. The differences of large sample size of AFP from Wenzhow, Shengyang and Ningbo are not significant, while the differences of free-β- hCG from Wenzhow, Shengyang and Ningbo is remained because of its instability. The levels from Wenzhow and Ningbo are near. It is suggested that the laboratories with small sample size can establish their own laboratory parameters using the reference obtained from large sample size under the same experimental conditions. There are no significant differences of stability among regression computational models in the 3 software. The exponent quadru-function regression model can be used to establish the median databases for the screening with the similar data distribution in the paper.