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).
Biological 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:
- Descriptive data (total number of subjects included, period of time covered, number of samples obtained for each subject studied, type of population studied, health status)
- Analytical data (model used by each author for calculating the analytical coefficient of variation, values of between-run and within-run analytical precision)
- Statistics (mean, standard deviation and units of measurement obtained for each population studied in each article)
- Relevant observations (fasting conditions, type of pathology affecting the subjects studied)
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 variation
The within and between-subject components of biological variation have been used for many purposes (1):
- To set analytical quality specifications
- To evaluate the significance of changes in serial results (the reference change value)
- To assess the utility of population-based reference values
- To assess the number of specimens required to estimate the homeostatic set point
- To assess the best way for reporting results
- To select the best specimen (the one with lowest variability)
- To compare available tests
- To assess the clinical utility of tests
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 routine
The 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)
2. Evaluation of laboratory performance (to assure quality of results)
1. Set up control rules:
When designing the internal quality control protocol, the first step is to define the level of quality that the laboratory wants to attain for a determined test (the analytical quality specification). The second step is to know the stable analytical performance for this test. Then, a control rule (control limits and number of controls per run) able to advise when increases from stable performance surpass the quality specified can be selected. It is important to understand that the quality specification itself should not be used as the control limit. When the proper procedure is used, the control limit ends up being a value somewhere between the quality specification and the stable performance: the wider the distance between these two characteristics, the more relaxed the control rule is; and the narrower, the more stringent.
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:
To evaluate laboratory performance, the analytical imprecision and bias (obtained from the internal quality control protocol) is compared against the quality specifications (standards) for these two components of analytical error. The analytical procedures that deviate from the standards have to be reviewed by laboratory professionals, and processes for improving performance implemented.
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.
Since 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.
- Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci 1989;27:409-437
- Kenny D, Fraser CG, Hyltoft Petersen P, Kallner A. Estrategies to set global analytical quality specifications in laboratory medicine. Consensus agreement. Scan J Clin Lab Invest 1999;59:585
- Harris EK. Statistical principles underlying analytic goal-setting in clinical chemistry. Am J Clin Pathol 1979;374:72-82
- Gowans EMS, Hyltoft Petersen P, Blaabjerg O et al. Analytical goals for acceptance of common reference intervals for laboratories throughout a geographical area. Scan J Clin Lab Invest 1988;48:757-64
- Ricós C, Baadenhuijsen H, Libeer JC, Htyltoft Petersen P, Stöckl D, Theinpont L, Fraser CG. External quality assessment: currently used criteria for evaluating performance in European countries and criteria for future harmonization. Eur J Clin Chem Clin Biochem 1996;34:159-65
Biography: Carmen Ricós, Ph.D.
Dr. Ricós graduated in Pharmacy at the University of Barcelona in 1969 and earned her Doctorate in Pharmacy at the University of Barcelona in 1973.
She was awarded a four-year grant in a biochemistry research institution. In 1975 she joined the Catalan Health Institute as a pharmacist specialized in medical analyses in two Primary Care Laboratories.
In 1979 she moved to the Biochemistry Department of Vall d'Hebron General Hospital, where she gained the position of Quality Assurance Head of a clinical laboratory processing around 3.128.000 tests per year. From January 1980 to the present she has occupied this position.
Besides her normal tasks, she has been involved in establishing external quality assessment schemes organized by the Spanish Society of Clinical Biochemistry and Molecular Pathology since 1981 and has been chairwoman of the Analytical Quality Commission of this Society since 1990. She has contributed to several European working groups concerning external quality assessment, and now participates in Technical Committee 140 (Laboratory Medicine) of the European Committee for Normalization (CEN) and in Technical Committee 212 (Clinical Laboratory and in vitro laboratory tests) of the International Standardization Organization (ISO) working group on subjects related to External Quality Assessment and Analytical quality Goals. She is also a member of the Expert Advisory Panel on Health Laboratory Services, World Health Organization (WHO) for the period 1997-2001.
She has directed two doctoral theses, and has written and lectured on a number of works related with internal and external quality control, quality systems and quality goals. She regularly imparts classes on laboratory accreditation, in connection with the ENAC (Spanish Accreditation Body)
Brief history: SEQC - Analytical Quality Commission
The Analytical Quality Commission of the Spanish Society for Clinical Chemistry (Sociedad Española de Bioquímica Clínica y Patología Molecular - SEQC) is formed by nine professionals working in Public Health primary care and hospital laboratories in different parts of Spain and is chaired by Dr. Carmen Ricós.
This Commission was created in 1988 with the aim of helping the SEQC organizers of external quality assessment schemes to evaluate their results at the end of each cycle. Since that time its task has expanded to include:
- Internal quality control of basic equipment (freezers, heaters, refrigerators, thermometers, spectrometers, pH and gases analyzers)
- Diffusion of criteria for establishing internal quality control procedures
- Research on the evaluation of commutability between control materials and human specimens, and effects of non-commutability on quality
- Studies regarding transferability of results between laboretories
- Establishment of components of biological variability in urine quantities
- Publication of recommendations for analytical quality specifications based on biological variation
The SEQC Analytic Quality Commission is a voluntary, purely scientific group, with no private funding and no links to commercial interests.