Researchers often decide whether to average multiple results in order to produce more precise data, and clinicians often decide whether to repeat a laboratory test in order to confirm its validity or to follow a trend. Some of the major sources of variation in laboratory tests (analytical imprecision, within-subject biological variation and between-subject variation) and the effects of averaging multiple results from the same sample or from the same person over time are discussed quantitatively in this article.

This analysis leads to the surprising conclusion that the strategy of averaging multiple results is only necessary and effective in a limited range of research studies. In clinical practice, it may be important to repeat a test in order to eliminate the possibility of a rare type of error that has nothing to do analytical imprecision or within-subject variation, and for this reason, paradoxically, it may be most important to repeat tests with the highest sensitivity and/or specificity (i.e., ones that are critical for clinical decision-making). In a recent grant application to study biomarkers in vasculitis, my colleagues and I proposed assaying each sample in duplicate. We did not discuss the issue – it just seemed like the proper way to obtain high-quality data – and we received no commentary, for or against, from the reviewers, suggesting that they had made the same assumption. However, once the funds were gratefully received, we confronted the fact that making each measurement in duplicate would cut in half the number of markers or samples that we could assay and thereby limit the scope of the project. In order to make a decision on how to use our funds most effectively, I investigated the effects of averaging test results in research studies.

Jun 1, 2017 - Within-subject biological variation and examination imprecision can be used to create. Biological variation: from principles to practice. CBSE Test Papers class 12 Biology Principles of Inheritance and Variation. CBSE chapter wise practice papers with solution for class 12 Biology chapter 5 Principles of Inheritance and Variation for free download in PDF format. 12th Biology chapter Principles of Inheritance and Variation have many topics.

Because I am also a clinician, I also considered the role of repeating tests in clinical practice and was struck by the differences from the research arena. Quantitative description of the sources of variation in laboratory tests has an extensive literature in laboratory medicine [] that is, I suspect, little known to clinicians or clinical researchers. The improvement produced by averaging data obtained from replicate measurements has been described by Callum Fraser in publications aimed primarily at educating laboratory medicine professionals and the panels of experts who produce guidelines for the proper use of such tests [,].

This topic is also highly relevant, but in different ways, to those designing research studies and to practicing physicians, hence my impetus to introduce it to a more general medical audience. I will turn to C-reactive protein (CRP) repeatedly as an example, since it is being measured in my research project and is used in multiple ways in clinical medicine.

I hope that my conclusions will be useful both to researchers faced with decisions regarding distribution of resources and to clinicians who seek to optimize their use of laboratory tests to make decisions about their patients. Sources of variation Variation in the measured concentrations of analytes for a given subject derives from three sources []. Pre-analytical variation encompasses numerous factors related to the status of the individual (e.g., posture, time of day, food intake, exercise and medications) and the collection and handling of the sample (e.g., tourniquet time, transport time and storage). Identifying relevant sources of pre-analytical variation is the responsibility of anyone hoping to bring a new assay into clinical use, and minimizing pre-analytical variation once an assay is in clinical use is one of the many quality-control tasks of the clinical laboratory. Analytical variation is comprised of analytical imprecision (random error) and analytical bias, which is a systematic error defined as “the difference between the expectation of measurement results and the true value of the measured quantity” [].

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