Biological variation: a still evolving facet of laboratory medicine.

Abstract

Numerical data on the components of random biological variation (BV) have been generated for over 40 years. These have been used for a variety of purposes in laboratory medicine, including setting analytical quality specifications, assessing the significance of the difference seen in serial results from an individual and investigating the utility of conventional populationbased reference values. The generation of such data is not easy. However, applications are facilitated through the availability of databases which give single figures for the components of BV, namely, within-subject (CVI) and between-subject (CVG). Generation of a comprehensive database of components of BV was initiated in 1997 by the Analytical Quality Commission (AQC) of the Spanish Society of Clinical Chemistry (SEQC). A scoring system was designed to evaluate the robustness of data, and this has five essential criteria for inclusion: papers must be designed to examine BV, the performance index (PI1⁄4CVA/0.5CVI) must be <2.0, where CVA is the analytical component of variation, the components must be derived by ANOVA or another recommended calculation method, the data must be from apparently healthy individuals and the median estimates of CVI and CVG must be documented. The structure of the on-line database and the criteria used for generation and update have been recently described. The database provides analytical quality specifications for imprecision, bias and total allowable error, at minimum, desirable and optimum levels of quality. It contains data on 358 measurands from 247 papers as single numbers for CVI and CVG. Where multiple studies exist for a single measurand, the incorporated numbers represent median values. The database has been updated every two years and is currently in its eighth edition. Recently, a number of demerits have become apparent. For example, for 202 measurands, the data appear in a single publication, 129 have data in two to nine publications and 27 in 510 publications. Interestingly, 55% of the measurands in the first group had the maximum scores for both the PI and the statistical methods used, which suggests that these estimates of BV are reliable: similar data exist for the other two groups. It is dogma that, in general, estimates of CVI are similar over time span of study, number of samples, health and disease and other factors. However, considerable heterogeneity of the CVI estimates across studies is a major weakness of the database. Carobene et al. showed that published BV data for alanine aminotransferase, aspartate aminotransferase and gamma glutamyl transferase demonstrated a wide range of values derived from inconsistent protocols. The quality of the presentations of the data was variable. These findings raise further concerns around the utility of the data currently available and highlight the need for critical appraisal of publications on BV. The Working Group on BV (WG-BV) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) has presented these concerns at the 1st EFLM Strategic Conference on Defining Analytical Performance Goals. The many insightful presentations are available on the Internet.