Quantitative data on the components of biological variation (BV) are used for several purposes, including calculating the reference change value (RCV) required for the assessment of the significance of changes in serial results in an individual. Pathology may modify the set point in diseased patients and, more importantly, the variation around that set-point. Our aim was to collate all published BV data in situations other than health. We report the within-subject coefficient of variation (CV(I)) for 66 quantities in 34 disease states. We compared the results with the CV(I) determined in healthy individuals and examined whether the data derived in specific diseases could be useful for clinical applications. For the majority of quantities studied, CV(I) values are of the same order in disease and health: thus the use of RCV derived from healthy subjects for monitoring patients would be reasonable. However, for a small number of quantities considered to be disease specific markers, the CV(I) differed from those in health. This could mean that RCV derived from healthy CV(I) may be inappropriate for monitoring patients in certain diseases. Hence, disease-specific RCVs may be clinically useful.

The RCV concept is an approach that can be offered by laboratories to assess changes in serial results. The RCV data in this study are presented as a point of departure for a widely applicable objective guide to interpret changes in serial results.

IntroductionStandardization is the ability to obtain interchangeable results leading to same medical interpretation. External quality assessment (EQA) is the main support of the on-going harmonization initiatives. Aim of study was to evaluate results obtained from two years category 1 EQA program experience in Spain and determine the impact of applying this type of EQA program on the analytical standardization.Materials and methodsAccording to the analytical method, traceability and instrument different groups were established which results were evaluated by calculating mean, coefficient of variation and percent of deviation to the reference value. Analytical performance specifications used to the results' evaluation were derived from biological variation for bias and from the inter-laboratory coefficients of variation found in a previous pilot study.ResultsOnly creatinine measured by enzymatic methods gave excellent results, although few laboratories used this method. Creatine kinase and GGT gave good precision and bias in all, but one instrument studied. For the remaining analytes (ALT, ALP, AST, bilirubin, calcium, chloride, glucose, magnesium, potassium, sodium, total protein and urate) some improvement is still necessary to achieve satisfactory standardization in our setting.ConclusionsThe two years of category 1 EQA program experience in Spain have manifested a lack of standardization of 17 most frequent biochemistry tests used in our laboratories. The impact of the information obtained on the lack of standardization is to recommend abandoning methods such as ALT, AST without exogenous pyridoxal phosphate, Jaffe method for creatinine, and do not use non-commutable calibrators, such as aqueous solutions for calcium and sodium.

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Objectives The estimates of biological variation (BV) have traditionally been determined using direct methods, which present limitations. In response to this issue, two papers have been published addressing these limitations by employing indirect methods. Here, we present a new procedure, based on indirect methods that analyses data collected within a multicenter pilot study. Using this method, we obtain CVI estimates and calculate confidence intervals (CI), using the EFLM-BVD CVI estimates as gold standard for comparison. Methods Data were collected over a 18-month period for 7 measurands, from 3 Spanish hospitals; inclusion criteria: patients 18–75 years with more than two determinations. For each measurand, four different strategies were carried out based on the coefficient of variation ratio (rCoeV) and based on the use of the bootstrap method (OS1, RS2 and RS3). RS2 and RS3 use symmetry reference change value (RCV) to clean database. Results RS2 and RS3 had the best correlation for the CVI estimates with respect to EFLM-BVD. RS2 used the symmetric RCV value without eliminating outliers, while RS3 combined RCV and outliers. When using the rCoeV and OS1 strategies, an overestimation of the CVI value was obtained. Conclusions Our study presents a new strategy for obtaining robust CVI estimates using an indirect method together with the value of symmetric RCV to select the target population. The CVI estimates obtained show a good correlation with those published in the EFLM-BVD database. Furthermore, our strategy can resolve some of the limitations encountered when using direct methods such as calculating confidence intervals.