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Biological variation (BV) data is a cornerstone in the interpretation of laboratory test results, being the basis for many of the decisions we make every day both in the laboratory and in clinical practise. Among the many applications is its use in diagnosis and monitoring of disease. Most typically this occurs when comparing a person’s level of the analyte of interest against a reference interval, based on the between-subject variation, CV G , or when comparing a change against the reference change value, based on the within-subject variation, CV I . Furthermore, BV data is probably the most commonly used approach for setting analytical quality specifications for bias, imprecision and total error for many laboratory constituents. General assumptions for the uses of BV data are that estimates are reliable, i.e., adequately collected and calculated, and that the estimates are representative for the specific population and setting for which they will be applied.
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Aarsand et al. (2015) studied this question.
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