Evaluating sample stability in the clinical laboratory with the help of linear and non-linear regression analysis

Abstract

Abstract As it is common practice for laboratories to store patient samples for a predefined period, allowing clinicians to request additional tests on previously collected samples, knowledge about sample stability is indispensable for the laboratorian. A common approach to estimating the maximum storage time is to use a discrete study design, measuring the analyte of interest at various time-points and then checking for significant differences with the help of a statistical test, such as Student’s t-test, Wilcoxon’s test or an analysis of variance (ANOVA) test. Because only discrete time intervals are considered, stability data can just be approximated. Alternatively, a continuous study design, as described by the Clinical and Laboratory Standards Institute (CLSI) for performing stability experiments for in vitro diagnostic reagents, can also be adopted by the clinical laboratory to evaluate the stability of biological samples. The major advantage of this approach is that it allows laboratories to define individual stability limits for different medical situations and offers more flexibility when choosing time-points for measurements. The intent of this paper is to demonstrate the evaluation of sample stability in the clinical laboratory with a continuous study design implemented with linear or non-linear regression analysis. Appropriate statistical modeling and acceptance criteria are presented, stability functions are described briefly, and checking the overall validity of the results is discussed.