Generation and Application of Data on Biological Variation in Clinical Chemistry

Abstract

Most clinical chemical analytes vary in a random manner around a homeostatic set point. Replicate analyses of a series of specimens collected from a group of subjects allows estimation of analytical, within and between subject components of variation. The preferred experimental procedures and statistical methods for evaluation of data and analysis of variance are described; a detailed example is provided in the Appendix. The many uses of data on biological variation in clinical chemistry are reviewed, including setting analytical goals, deciding the significance of changes in serial results from an individual, evaluating the utility of conventional population-based reference values in patient management, and other applications.

Clinical utility of currently available biomarkers in inflammatory enteropathies of dogs

“…This includes preanalytic effects associated with the collection and handling (including storage) of samples and analytical variability arising from the methodology, instrumentation, and also technical skills 18, 21, 22. This aspect becomes especially important for the clinician when utilizing patient‐side (ie, in‐house) diagnostic tests 23.…”

“…Biological variability, an inherent characteristic of all biochemical analytes, is an important aspect in the interpretation of the diagnostic performance of a biomarker 18. Normal biological variability comprises within‐subject (intraindividual) and among‐subject (interindividual) variation, both of which might be similar or different between health and various disease states 18, 24…”

Biological Variability in Serum Cortisol Concentration Post‐adrenocorticotropic Hormone Stimulation in Healthy Dogs

“…The CV analytic should be <1/2 CV within and in our study, it was > CV within 4. One possible reason is that the serum samples of some dogs were lipemic, and lipemia can cause interference with the cortisol assay and decrease its precision 11.…”

“…The total variability consists of the components of within‐ and between‐individual biological variability, and the component of analytical variability 4, 5. The components of total variability determine the number of repeated measurement required for estimation of the homeostatic set point (HSP) for a diagnostic test parameter, which is the mean and confidence intervals (CI) of the test parameter.…”

“…A test parameter that has a low IoI (Fig 1, test B) would have a low within‐individual variability in comparison with its between‐individual variability. Tests with low IoI are not well suited for use in population‐based reference intervals because the individual's HSP covers only a small fraction of the population reference interval 4, 5. Therefore, a test result that is outside of an individual's HSP, but within the population reference interval, would be erroneously considered normal 4, 5.…”