Gaye Amadou, Peakman Tim, Tobin Martin D, Burton Paul R
Department of Health Sciences, University of Leicester, Leicester, UK and UK Biobank and University of Manchester, Manchester, UK.
Department of Health Sciences, University of Leicester, Leicester, UK and UK Biobank and University of Manchester, Manchester, UK
Int J Epidemiol. 2014 Oct;43(5):1633-44. doi: 10.1093/ije/dyu127. Epub 2014 Aug 1.
Errors, introduced through poor assessment of physical measurement or because of inconsistent or inappropriate standard operating procedures for collecting, processing, storing or analysing haematological and biochemistry analytes, have a negative impact on the power of association studies using the collected data. A dataset from UK Biobank was used to evaluate the impact of pre-analytical variability on the power of association studies.
First, we estimated the proportion of the variance in analyte concentration that may be attributed to delay in processing using variance component analysis. Then, we captured the proportion of heterogeneity between subjects that is due to variability in the rate of degradation of analytes, by fitting a mixed model. Finally, we evaluated the impact of delay in processing on the power of a nested case-control study using a power calculator that we developed and which takes into account uncertainty in outcome and explanatory variables measurements.
The results showed that (i) the majority of the analytes investigated in our analysis, were stable over a period of 36 h and (ii) some analytes were unstable and the resulting pre-analytical variation substantially decreased the power of the study, under the settings we investigated.
It is important to specify a limited delay in processing for analytes that are very sensitive to delayed assay. If the rate of degradation of an analyte varies between individuals, any delay introduces a bias which increases with increasing delay. If pre-analytical variation occurring due to delays in sample processing is ignored, it affects adversely the power of the studies that use the data.
由于对物理测量评估不佳,或因血液学和生物化学分析物的采集、处理、存储或分析的标准操作程序不一致或不恰当而引入的误差,会对使用所收集数据的关联研究效能产生负面影响。英国生物银行的一个数据集被用于评估分析前变异性对关联研究效能的影响。
首先,我们使用方差成分分析估计了可归因于处理延迟的分析物浓度方差比例。然后,我们通过拟合混合模型,获取了由于分析物降解速率变异性导致的个体间异质性比例。最后,我们使用我们开发的、考虑了结局和解释变量测量不确定性的效能计算器,评估了处理延迟对巢式病例对照研究效能的影响。
结果表明,(i)我们分析中所研究的大多数分析物在36小时内是稳定的,以及(ii)在我们所研究的设置下,一些分析物不稳定,由此产生的分析前变异显著降低了研究效能。
对于对检测延迟非常敏感的分析物,规定有限的处理延迟很重要。如果分析物的降解速率在个体间有所不同,任何延迟都会引入偏差,且偏差会随着延迟增加而增大。如果忽略因样本处理延迟而出现的分析前变异,会对使用这些数据的研究效能产生不利影响。