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中位数倍数(MoM)值中的偏倚对唐氏综合征患者风险及筛查性能的影响。

The impact of bias in MoM values on patient risk and screening performance for Down syndrome.

作者信息

Nix Barry, Wright Dave, Baker Amy

机构信息

Medical School, Heath Campus, Cardiff University, CF14 4XN, UK.

出版信息

Prenat Diagn. 2007 Sep;27(9):840-5. doi: 10.1002/pd.1791.

Abstract

UNLABELLED

First and second trimester screening protocols for Down syndrome rely on marker values being referred to smoothed median values to produce adjusted multiple of the median (MoM) values to standardise for factors such as assay, gestation, maternal weight, smoking status, and so on. Changes in assay components, such as reagent lot, and inappropriate use of published regression equations for smoothed medians have resulted in biases in reported MoM values that in many applications remain uncorrected. This paper investigates the impact of these biases on patient-specific risk estimates and screening performance, and concludes that a 10% bias for an individual marker can result in an increase of between 1 and 2% in the false positive rate of the programme. A simple formula is also derived that enables the impact of these biases to be determined without the need for simulation, thus making it easier to design effective statistical quality control procedures to monitor the output of screening software algorithms.

OBJECTIVE

To determine the impact of bias in MoM values on detection rates, false positive rates and patient-specific risks for Down syndrome.

METHODS

We show that bias in MoM values affects risk through a multiplicative factor, and present an approximation to estimate this factor. We then show how bias in MoM values changes the effective risk threshold in the screening test, and hence the test's performance characteristics are determined by reference to a different point on the ROC curve for that test. Our approximation is based on the assumption of equal variance covariance structure for the unaffected and T21 log MoM values. We demonstrate, using computer simulation and supportive theoretical results, that the approximation is reliable in situations encountered in practice. Applications of the approximation are also discussed in respect of establishing effective quality control rules for median MoMs.

RESULTS

Substantial changes in patient risk estimates and overall screening performance can result from the sort of biases in marker MoM values encountered in routine practice. In particular, biases of 10% in individual median marker MoM values can produce a four-fold range of risks when using the triple test. A 10% bias in a single marker will change the false positive rates by up to 2%. The effects on the false positive rate are approximately additive and, in cases where all markers are biased towards Down syndrome, biases in all three markers for the triple test can more than double the false positive rate.

CONCLUSIONS

Biases in marker MoM values can occur in many ways, inappropriate median values, kit lot change, drift in assay performance and operator effects. We present methods which allow the impact of these changes to be assessed in relation to patient-specific risks and the overall screening performance. This, in turn, will enable appropriate quality control procedures to be established to control the magnitude of reported marker MoM biases, or equivalently, the magnitude of biases associated with the calculation of patient-specific risks.

摘要

未标注

孕早期和孕中期唐氏综合征筛查方案依赖于将标志物值参照平滑中位数来生成校正后的中位数倍数(MoM)值,以便针对诸如检测方法、孕周、孕妇体重、吸烟状况等因素进行标准化。检测方法成分的变化,如试剂批次,以及对已发表的平滑中位数回归方程的不当使用,导致报告的MoM值出现偏差,在许多应用中这些偏差仍未得到校正。本文研究了这些偏差对患者特异性风险估计和筛查性能的影响,并得出结论:单个标志物10%的偏差可导致该筛查项目的假阳性率增加1%至2%。还推导了一个简单公式,可在无需模拟的情况下确定这些偏差的影响,从而更易于设计有效的统计质量控制程序来监测筛查软件算法的输出。

目的

确定MoM值偏差对唐氏综合征检测率、假阳性率和患者特异性风险的影响。

方法

我们表明MoM值偏差通过一个乘数因子影响风险,并给出一个近似值来估计该因子。然后我们展示MoM值偏差如何改变筛查试验中的有效风险阈值,因此该试验的性能特征是通过参考该试验ROC曲线上的不同点来确定的。我们的近似值基于未受影响的和T21对数MoM值具有等方差协方差结构的假设。我们通过计算机模拟和支持性理论结果证明,在实际遇到的情况下该近似值是可靠的。还讨论了该近似值在为中位数MoM建立有效质量控制规则方面的应用。

结果

常规实践中遇到的标志物MoM值偏差可能导致患者风险估计和总体筛查性能发生重大变化。特别是,使用三联检测时,单个中位数标志物MoM值10%的偏差可产生四倍范围的风险。单个标志物10%的偏差将使假阳性率变化高达2%。对假阳性率的影响大致是累加的,并且在所有标志物都偏向唐氏综合征的情况下,三联检测中所有三个标志物的偏差可使假阳性率增加一倍以上。

结论

标志物MoM值的偏差可能以多种方式出现,如不当的中位数、试剂盒批次变化、检测性能漂移和操作人员影响。我们提出了一些方法,可据此评估这些变化对患者特异性风险和总体筛查性能的影响。这反过来将有助于建立适当的质量控制程序,以控制报告的标志物MoM偏差的大小,或者等效地,控制与患者特异性风险计算相关的偏差大小。

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