| Biologic Variation and Desirable Specifications for QC |
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| Written by Dr. Carmen Ricos, PhD; Virtudes Alvarez, MD; Fernando Cava, MD; | |||
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Dr. Carmen Ricos provides us with a comprehensive database of biologic variation for over 300 quantities, based on a review of over 140 articles in the scientific literature. The accompanying database includes the observed between- and within-subject biologic variation for these quantities, as well as desirable specifications for imprecision, bias and total allowable error. This is a fantastic wealth of information for those seeking more guidance on quality requirements. Analytical Quality Commission of the Spanish Society of Clinical Chemistry and Molecular Pathology (SEQC).
BackgroundBiological variation, the natural fluctuation of body fluid constituents around the homeostatic setting point, has two components: within and between-subject variation. Many articles have been published estimating the components of biological variation. The material compiled in the database presented here was obtained from published articles, books and doctoral theses provided by the authors. The information it contains covers 316 quantities and reviews 191 publications, fewer than 10 of which had to be rejected. The results presented were obtained by relating the following information from the works with the within-subject variation, an approach that has not been used in previous efforts of this type:
The within- and between-subject coefficients of variation and the desirable quality specifications for precision, bias and total error for all the quantities included are presented in Annex I (tables). Annex II shows the bibliographic references for each quantity studied. Annex III presents the articles used to elaborate the database. Use of data derived from biological variationThe within and between-subject components of biological variation have been used for many purposes (1):
In this essay the components of biological variation have been used to derive analytical quality specifications for the imprecision, bias and total error of clinical laboratory procedures. It is clear that clinical laboratory performance should satisfy medical needs (2), which include monitoring, screening, diagnosis and case finding. For monitoring a patient's condition, analytical variation has to be maintained below half the within-subject component of biological variation. This same specification has to be maintained for screening, diagnosis and case finding when a fixed cut-off point is used to define a pathological or healthy condition (3). To determine patient status for these three purposes according to population-based reference intervals, analytical bias must be maintained below a quarter of the within- plus between- subject components (4). Biological variation is a good basis for deriving analytical quality specifications that satisfy general medical needs. The within- and between-subject components of variation, expressed in coefficients of variation (CVw and CVg, respectively) and the corresponding quality specifications for analytical imprecision (I), bias (B) and total error (TE), expressed in percentages, were calculated according the following formulas: I < 0.5 CVw B < 0.25 (CVw2 + CVg2)1/2 TE < k. 0.5 CVw+ 0.25(CVw2 + CVg2)1/2 being k= 1.65 at a=0.05 After checking for sex-related differences in BV results, stratification by sex was justified for only five quantities (androstendione, estradiol, follicle stimulating hormone, luteinizing hormone and prolactin,). Two quantities (glucose and cholesterol) had to be stratified according to fasting or non-fasting state. In all these cases, the quality specifications were derived from the group with lower within-subject variation. Biological variation in pathological states was higher than in the healthy state for various quantities and, in these, quality specifications were derived only from the healthy population (most stringent). According to the database information, stratification for other reasons, (e.g. age) was not necessary. Applications of the analytical quality specifications in daily routineThe analytical quality specifications for imprecision, bias and total error can be used in daily work for two different activities: 1. Internal quality control (to set up control rules) 1. Set up control rules: Control rules can be calculated by hand or by means of specific software for this purpose, such as the Validator® program. The information presented in this essay can be used as the "analytical requirements" requested by Validator for determining control rules. If the laboratory's priority is detection of random error, the specification for imprecision shown in the database can be used to fill the corresponding analytical requirement cell. If the priority is detecting systematic errors, the bias specification should be used. If the laboratory wants to work with systematic and random error combined, the total error specification can be used. 2. Assure quality of results: Data obtained from participation in external quality assessment schemes (EQAS, also called proficiency testing), that is, the percentage deviation of each result with respect to the peer group mean, can be compared with the total error specification shown in this essay to check accuracy. Many EQAS organizers use fixed limits, which are exactly the same as the values shown in this essay as the "total error" specification, to evaluate the performance of the participating laboratories (5). We hope that the information provided in this essay and the biological variation database will be of help to laboratory professionals attempting to incorporate the analytical quality specifications derived from biological variation into their daily routine, in order to assure that laboratory results will be useful for general medical applications. NoteSince more and more information is constantly being produced on biological variation, it is the authors' wish to maintain this database open to revision and expansion. It is our idea to periodically update the information provided herein. References
Biography: Carmen Ricós, Ph.D.
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