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Clinical Pathology: Preanalytical Variation in Preclinical Safety Assessment Studies-Effect on Predictive Value of Analyte Tests
Author(s) -
Julia H. Riley
Publication year - 1992
Publication title -
toxicologic pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.613
H-Index - 108
eISSN - 1533-1601
pISSN - 0192-6233
DOI - 10.1177/0192623392020003206
Subject(s) - analyte , predictive value , sample size determination , variation (astronomy) , medicine , sample (material) , statistics , mathematics , chemistry , chromatography , physics , astrophysics
Significant differences in concentrations of analytes in samples may be introduced before samples enter analyzers. These differences are known as preanalytical variation and are part of the overall variation in analytical data. Preanalytical variation is caused by factors that operate during animal preparation prior to sampling, sample collection, sample processing, and sample storage prior to measurement. Preanalytical variation is important because it detracts from the predictive value of analyte measurements. Preanalytical variation may permanently damage data. Because its effects are difficult to quantitate it should be minimized in safety assessment studies. Sources of preanalytical variation are actions performed on animals prior to sample collection and actions performed on the specimen prior to analysis. Preanalytical variation produces a range of artefacts in experimental data. Consequences of preanalytical variation are loss of confidence in the data, obfuscation of real test article effects, false effects, and possibly the expense of repeating a study. To limit preanalytical variation, its sources must be identified, the effects documented, and measures devised to eliminate its sources. Predictive value (likelihood of actual disease) of appropriate clinical pathology tests in toxicology is inversely dependent on preanalytical variation: uncontrolled variation produces data with low predictive values, and controlled variation produces data with high predictive values.

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