Abstract
Background: 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.Methods: 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.Results: 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.Conclusions: 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.
Highlights
A biobank may be defined as ‘an organized collection of human biological material and associated information stored for one or more research purposes’.1,2 Most contemporary biobanks are large by design because the aetiological determinants(genes, environment and interactions) of complex diseases are typically weak and their resolution demands many subjects[3] with data that are both accurate and precise
By applying the likelihood ratio test to Model 2 (Figure 2), a comparison under scenarios 2 and 3 indicates that almost all analytes exhibited significant evidence of between-person heterogeneity of slope. This finding is entirely consistent with the equivalent finding reported by Jackson et al.[19]. They concluded that despite the statistical significance of this slope heterogeneity, it would in practice have little impact on statistical power
Standard operating procedures (SOPs) for biosample collection, processing, storage and analysis must be explored in detail and chosen with care
Summary
A biobank may be defined as ‘an organized collection of human biological material (e.g. blood, urine or extracted DNA) and associated information stored for one or more research purposes’.1,2 Most contemporary biobanks are large by design because the aetiological determinants(genes, environment and interactions) of complex diseases are typically weak (e.g. relative risks between 1.1 and 1.3) and their resolution demands many subjects[3] with data that are both accurate and precise. Errors introduced through poor assessment of physical measurement or because of inconsistent or inappropriate standard operating procedures (SOPs) for collecting, processing, storing or analysing biosamples can seriously impair data quality This can dramatically reduce the statistical power of a study, if one is studying gene-environment interactions.[3,4] Given the vast cost and effort that are needed to establish and maintain a contemporary biobank, even a small loss of power can impact substantially on the balance of costs and benefits of developing adequately powered study resources. If preanalytical variation occurring due to delays in sample processing is ignored, it affects adversely the power of the studies that use the data
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