Biological variation of inflammatory and iron metabolism markers in high-endurance recreational athletes; are these markers useful for athlete monitoring?

OBJECTIVES: To deliver biological variation (BV) data for serum hepcidin, soluble transferrin receptor (sTfR), erythropoietin (EPO) and interleukin 6 (IL-6) in a population of well-characterized high-endurance athletes, and to evaluate the potential influence of exercise and health-related factors on the BV. METHODS: Thirty triathletes (15 females) were sampled monthly (11 months). All samples were analyzed in duplicate and BV estimates were delivered by Bayesian and ANOVA methods. A linear mixed model was applied to study the effect of factors related to exercise, health, and sampling intervals on the BV estimates. RESULTS: Within-subject BV estimates (CVI) were for hepcidin 51.9 % (95 % credibility interval 46.9-58.1), sTfR 10.3 % (8.8-12) and EPO 27.3 % (24.8-30.3). The mean concentrations were significantly different between sex, but CVI estimates were similar and not influenced by exercise, health-related factors, or sampling intervals. The data were homogeneously distributed for EPO but not for hepcidin or sTfR. IL-6 results were mostly below the limit of detection. Factors related to exercise, health, and sampling intervals did not influence the BV estimates. CONCLUSIONS: This study provides, for the first time, BV data for EPO, derived from a cohort of well-characterized endurance athletes and indicates that EPO is a good candidate for athlete follow-up. The application of the Bayesian method to deliver BV data illustrates that for hepcidin and sTfR, BV data are heterogeneously distributed and using a mean BV estimate may not be appropriate when using BV data for laboratory and clinical applications.

The biological variation of insulin resistance markers: data from the European Biological Variation Study (EuBIVAS).

OBJECTIVES: An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI). METHODS: Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CVI) and between-subject (CVG) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal. RESULTS: The CVI of HOMA-IR was 26.7 % (95 % CI 25.5-28.3), driven largely by variability in plasma insulin and the CVI for QUICKI was 4.1 % (95 % CI 3.9-4.3), reflecting this formula's logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years. CONCLUSIONS: The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements.

Analytical performance specifications based on biological variation data - considerations, strengths and limitations.

Analytical performance specifications (APS) are typically established through one of three models: (i) outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory. When calculating APS, it is important to consider the different APS formulae, for what setting they are to be applied and if they are suitable for the intended purpose. In this opinion paper, we elucidate the background, limitations, strengths, and potential intended applications of the different BV based APS formulas. When using BV data to set APS, it is important to consider that all formulae are contingent on accurate and relevant BV estimates. During the last decade, efficient procedures have been established to obtain reliable BV estimates that are presented in the EFLM biological variation database. The database publishes detailed BV data for numerous measurands, global BV estimates derived from meta-analysis of quality-assured studies of similar study design and automatic calculation of BV based APS.

A standard to report biological variation data studies - based on an expert opinion.

There is a need for standards for generation and reporting of Biological Variation (BV) reference data. The absence of standards affects the quality and transportability of BV data, compromising important clinical applications. To address this issue, international expert groups under the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) have developed an online resource (https://tinyurl.com/bvmindmap) in the form of an interactive mind map that serves as a guideline for researchers planning, performing and reporting BV studies. The mind map addresses study design, data analysis, and reporting criteria, providing embedded links to relevant references and resources. It also incorporates a checklist approach, identifying a Minimum Data Set (MDS) to enable the transportability of BV data and incorporates the Biological Variation Data Critical Appraisal Checklist (BIVAC) to assess study quality. The mind map is open to access and is disseminated through the EFLM BV Database website, promoting accessibility and compliance to a reporting standard, thereby providing a tool to be used to ensure data quality, consistency, and comparability of BV data. Thus, comparable to the STARD initiative for diagnostic accuracy studies, the mind map introduces a Standard for Reporting Biological Variation Data Studies (STARBIV), which can enhance the reporting quality of BV studies, foster user confidence, provide better decision support, and be used as a tool for critical appraisal. Ongoing refinement is expected to adapt to emerging methodologies, ensuring a positive trajectory toward improving the validity and applicability of BV data in clinical practice.

Biological variation estimates of Alzheimer's disease plasma biomarkers in healthy individuals.

INTRODUCTION: Blood biomarkers have proven useful in Alzheimer's disease (AD) research. However, little is known about their biological variation (BV), which improves the interpretation of individual-level data. METHODS: We measured plasma amyloid beta (Aß42, Aß40), phosphorylated tau (p-tau181, p-tau217, p-tau231), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) in plasma samples collected weekly over 10 weeks from 20 participants aged 40 to 60 years from the European Biological Variation Study. We estimated within- (CVI ) and between-subject (CVG ) BV, analytical variation, and reference change values (RCV). RESULTS: Biomarkers presented considerable variability in CVI and CVG . Aß42/Aß40 had the lowest CVI (≈ 3%) and p-tau181 the highest (≈ 16%), while others ranged from 6% to 10%. Most RCVs ranged from 20% to 30% (decrease) and 25% to 40% (increase). DISCUSSION: BV estimates for AD plasma biomarkers can potentially refine their clinical and research interpretation. RCVs might be useful for detecting significant changes between serial measurements when monitoring early disease progression or interventions. Highlights Plasma amyloid beta (Aß42/Aß40) presents the lowest between- and within-subject biological variation, but also changes the least in Alzheimer's disease (AD) patients versus controls. Plasma phosphorylated tau variants significantly vary in their within-subject biological variation, but their substantial fold-changes in AD likely limits the impact of their variability. Plasma neurofilament light chain and glial fibrillary acidic protein demonstrate high between-subject variation, the impact of which will depend on clinical context. Reference change values can potentially be useful in monitoring early disease progression and the safety/efficacy of interventions on an individual level. Serial sampling revealed that unexpectedly high values in heathy individuals can be observed, which urges caution when interpreting AD plasma biomarkers based on a single test result.

Long-term within- and between-subject biological variation of 29 routine laboratory measurands in athletes.

OBJECTIVES: Within- and between-subject biological variation (BV) estimates have many applications in laboratory medicine. However, robust high-quality BV estimates are lacking for many populations, such as athletes. This study aimed to deliver BV estimates of 29 routine laboratory measurands derived from a Biological Variation Data Critical Appraisal Checklist compliant design in a population of high-endurance athletes. METHODS: Eleven samples per subject were drawn from 30 triathletes monthly, during a whole sport season. Serum samples were measured in duplicate for proteins, liver enzymes, lipids and kidney-related measurands on an Advia2400 (Siemens Healthineers). After outlier and homogeneity analysis, within-subject (CVI) and between-subject (CVG) biological variation estimates were delivered (CV-ANOVA and log-ANOVA, respectively) and a linear mixed model was applied to analyze the effect of exercise and health related variables. RESULTS: Most CVI estimates were similar or only slightly higher in athletes compared to those reported for the general population, whereas two- to three-fold increases were observed for amylase, ALT, AST and ALP. No effect of exercise and health related variables were observed on the CVI estimates. For seven measurands, data were not homogeneously distributed and BV estimates were therefore not reported. CONCLUSIONS: The observation of higher CVI estimates in athletes than what has been reported for the general population may be related to physiological stress over time caused by the continuous practice of exercise. The BV estimates derived from this study could be applied to athlete populations from disciplines in which they exercise under similar conditions of intensity and duration.

Within- and between-subject biological variation data for tumor markers based on the European Biological Variation Study.

OBJECTIVES: Reliable biological variation (BV) data are required for the clinical use of tumor markers in the diagnosis and monitoring of treatment effects in cancer. The European Biological Variation Study (EuBIVAS) was established by the EFLM Biological Variation Working Group to deliver BV data for clinically important measurands. In this study, EuBIVAS-based BV estimates are provided for cancer antigen (CA) 125, CA 15-3, CA 19-9, carcinoembryonic antigen, cytokeratin-19 fragment, alpha-fetoprotein and human epididymis protein 4. METHODS: Subjects from five European countries were enrolled in the study, and weekly samples were collected from 91 healthy individuals (53 females and 38 males; 21-69 years old) for 10 consecutive weeks. All samples were analyzed in duplicate within a single run. After excluding outliers and homogeneity analysis, the BVs of tumor markers were determined by CV-ANOVA on trend-corrected data, when relevant (Røraas method). RESULTS: Marked individuality was found for all tumor markers. CYFRA 21-1 was the measurand with the highest index of individuality (II) at 0.67, whereas CA 19-9 had the lowest II at 0.07. The CV I s of HE4, CYFRA 21-1, CA 19-9, CA 125 and CA 15-3 of pre- and postmenopausal females were significantly different from each other. CONCLUSIONS: This study provides updated BV estimates for several tumor markers, and the findings indicate that marked individuality is characteristic. The use of reference change values should be considered when monitoring treatment of patients by means of tumor markers.

The European Biological Variation Study (EuBIVAS): a summary report.

Biological variation (BV) data have many important applications in laboratory medicine. Concerns about quality of published BV data led the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference to indicate need for new studies to generate BV estimates of required quality. In response, the EFLM Working Group on BV delivered the multicenter European Biological Variation Study (EuBIVAS). This review summarises the EuBIVAS and its outcomes. Serum/plasma samples were taken from 91 ostensibly healthy individuals for 10 consecutive weeks at 6 European centres. Analysis was performed by Siemens ADVIA 2400 (clinical chemistry), Cobas Roche 8000, c702 and e801 (proteins and tumor markers/hormones respectively), ACL Top 750 (coagulation parameters), and IDS iSYS or DiaSorin Liaison (bone biomarkers). A strict preanalytical and analytical protocol was applied. To determine BV estimates with 95% CI, CV-ANOVA after analysis of outliers, homogeneity and trend analysis or a Bayesian model was applied. EuBIVAS has so far delivered BV estimates for 80 different measurands. Estimates for 10 measurands (non-HDL cholesterol, S100-ß protein, neuron-specific enolase, soluble transferrin receptor, intact fibroblast growth-factor-23, uncarboxylated-unphosphorylated matrix-Gla protein, human epididymis protein-4, free, conjugated and %free prostate-specific antigen), prior to EuBIVAS, have not been available. BV data for creatinine and troponin I were obtained using two analytical methods in each case. The EuBIVAS has delivered high-quality BV data for a wide range of measurands. The BV estimates are for many measurands lower than those previously reported, having an impact on the derived analytical performance specifications and reference change values.

Biological Variation of Cardiac Troponins in Health and Disease: A Systematic Review and Meta-analysis.

BACKGROUND: Many studies have assessed the biological variation (BV) of cardiac-specific troponins (cTn), reporting widely varying within-subject BV (CVI) estimates. The aim of this study was to provide meta-analysis-derived BV estimates for troponin I (cTnI) and troponin T (cTnT) for different sampling intervals and states of health. METHODS: Relevant studies were identified by a systematic literature search. Studies were classified according to their methodological quality by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC-compliant studies were performed after stratification by cTn isoform, exclusion of results below the limit of detection, states of health, and sampling interval to deliver reference change values (RCV), index of individuality (II) and analytical performance specifications (APS) for these settings. RESULTS: Sixteen and 15 studies were identified for cTnI and cTnT, respectively, out of which 6 received a BIVAC grade A. Five studies had applied contemporary cTnI assays, but none contemporary cTnT. High-sensitivity (hs-) cTnI and cTnT delivered similar estimates in all settings. Long-term CVI estimates (15.1; 11.3%) derived from healthy individuals were higher than short-term (4.3%; 5.3%) for hs-cTnI and hs-cTnT, respectively, although confidence intervals overlapped. Estimates derived from diseased subjects were similar to estimates in healthy individuals for all settings. CONCLUSIONS: This study provides robust estimates for hs-cTnI and hs-cTnT applicable for different clinical settings and states of health, allowing for the use of RCV both to aid in the diagnosis of myocardial injury and for prognosis. BV-based APS appear too strict for some currently available technologies.

European Biological Variation Study (EuBIVAS): Within- and Between-Subject Biological Variation Data for 15 Frequently Measured Proteins.

BACKGROUND: The European Biological Variation Study (EuBIVAS) was established to deliver rigorously determined data for biological variation (BV). Here, EuBIVAS-based BV estimates are provided for α1-acid glycoprotein, α1-antitrypsin, albumin, ß2-microglobulin, ceruloplasmin, complement component 3, complement component 4, C-reactive protein (CRP), cystatin C, haptoglobin, IgA, IgG, IgM, soluble transferrin receptor (sTfR), and transferrin (Trf), together with their associated analytical performance specifications (APSs) and reference change values (RCVs). METHOD: Serum samples from weekly blood samplings of 91 healthy study participants (38 males and 53 females, ages 21-69 years old) over 10 consecutive weeks in 6 European laboratories were stored at -80 °C before duplicate analysis on a Roche Cobas c702. Outlier and variance homogeneity analyses were performed followed by CV-ANOVA on trend-corrected data if relevant, to determine BV and analytical variation estimates with CI and the associated RCV. RESULTS: For the acute phase proteins, several participants experienced mild inflammatory episodes during the study, requiring exclusion of 7% of the 25290 results. Within-subject BV (CVI) estimates for specific proteins obtained in our study were lower than those available in the online 2014 BV database, except for Trf, whereas between-subject BV (CVG) estimates were similar. CVI and CVG estimates for sTfR, which have not previously been published, were 6.0% and 19.1%, respectively. CONCLUSIONS: In addition to new BV estimates for sTfR, this EuBIVAS substudy generated more demanding APS for frequently requested plasma specific proteins. APS for CRP should not be calculated from BV data except when CRP is used as a risk factor for cardiovascular disease.

The Biological Variation Data Critical Appraisal Checklist: A Standard for Evaluating Studies on Biological Variation.

BACKGROUND: Concern has been raised about the quality of available biological variation (BV) estimates and the effect of their application in clinical practice. A European Federation of Clinical Chemistry and Laboratory Medicine Task and Finish Group has addressed this issue. The aim of this report is to (a) describe the Biological Variation Data Critical Appraisal Checklist (BIVAC), which verifies whether publications have included all essential elements that may impact the veracity of associated BV estimates, (b) use the BIVAC to critically appraise existing BV publications on enzymes, lipids, kidney, and diabetes-related measurands, and (c) apply metaanalysis to deliver a global within-subject BV (CVI) estimate for alanine aminotransferase (ALT). METHODS: In the BIVAC, publications were rated as A, B, C, or D, indicating descending compliance for 14 BIVAC quality items, focusing on study design, methodology, and statistical handling. A D grade indicated that associated BV estimates should not be applied in clinical practice. Systematic searches were applied to identify BV studies for 28 different measurands. RESULTS: In total, 128 publications were identified, providing 935 different BV estimates. Nine percent achieved D scores. Outlier analysis and variance homogeneity testing were scored as C in >60% of 847 cases. Metaanalysis delivered a CVI estimate for ALT of 15.4%. CONCLUSIONS: Application of BIVAC to BV publications identified deficiencies in required study detail and delivery, especially for statistical analysis. Those deficiencies impact the veracity of BV estimates. BV data from BIVAC-compliant studies can be combined to deliver robust global estimates for safe clinical application.

The EuBIVAS: Within- and Between-Subject Biological Variation Data for Electrolytes, Lipids, Urea, Uric Acid, Total Protein, Total Bilirubin, Direct Bilirubin, and Glucose.

BACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined data describing biological variation (BV) of clinically important measurands. Here, EuBIVAS-based BV estimates of serum electrolytes, lipids, urea, uric acid, total protein, total bilirubin, direct bilirubin, and glucose, as well as their associated analytical performance specifications (APSs), are presented. METHOD: Samples were drawn from 91 healthy individuals (38 male, 53 female; age range, 21-69 years) for 10 consecutive weeks at 6 European laboratories. Samples were stored at -80 °C before duplicate analysis of all samples on an ADVIA 2400 (Siemens Healthineers). Outlier and homogeneity analyses were performed, followed by CV-ANOVA on trend-corrected data, when relevant, to determine BV estimates with CIs. RESULTS: The within-subject BV (CVI) estimates of all measurands, except for urea and LDL cholesterol, were lower than estimates available in an online BV database, with differences being most pronounced for HDL cholesterol, glucose, and direct bilirubin. Significant differences in CVI for men and women/women <50 years of age were evident for uric acid, triglycerides, and urea. The CVA obtained for sodium and magnesium exceeded the EuBIVAS-based APS for imprecision. CONCLUSIONS: The EuBIVAS, which is fully compliant with the recently published Biological Variation Data Critical Appraisal Checklist, has produced well-characterized, high-quality BV estimates utilizing a stringent experimental protocol. These new reference data deliver revised and more exacting APS and reference change values for commonly used clinically important measurands, thus having direct relevance to diagnostics manufacturers, service providers, clinical users, and ultimately patients.

Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects.

BACKGROUND: The complete blood count (CBC) is used to evaluate health status in the contexts of various clinical situations such as anemia, infection, inflammation, trauma, malignancies, etc. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are required. The study aim was to define the BVs of CBC parameters employing a strict protocol. METHODS: Blood samples, drawn from 30 healthy subjects (17 females, 13 males) once weekly for 10 weeks, were analyzed using a Sysmex XN 3000 instrument. The data were assessed for normality, trends, outliers and variance homogeneity prior to coefficient of variation (CV)-analysis of variance (ANOVA). Sex-stratified within-subject (CVI) and between-subjects (CVG) BV estimates were determined for 21 CBC parameters. RESULTS: For leukocyte parameters, with the exception of lymphocytes and basophils, significant differences were found between female/male CVI estimates. The mean values of all erythrocyte-, reticulocyte- and platelet parameters differed significantly between the sexes, except for mean corpuscular hemoglobin concentration, mean corpuscular volume and platelet numbers. Most CVI and CVG estimates appear to be lower than those previously published. CONCLUSIONS: Our study, based on a rigorous protocol, provides updated and more stringent BV estimates for CBC parameters. Sex stratification of data is necessary when exploring the significance of changes in consecutive results and when setting analytical performance specifications.

The EuBIVAS Project: Within- and Between-Subject Biological Variation Data for Serum Creatinine Using Enzymatic and Alkaline Picrate Methods and Implications for Monitoring.

BACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined biological variation (BV) indices. EuBIVAS determined BV for serum creatinine using the enzymatic and alkaline picrate measurement methods. METHOD: In total, 91 healthy individuals (38 males, 53 females; age range, 21-69 years) were bled for 10 consecutive weeks at 6 European laboratories. An equivalent protocol was followed at each center. Sera were stored at -80 °C before analysis. Analyses for each patient were performed in duplicate within a single run on an ADVIA 2400 system (San Raffaele Hospital, Milan). The data were subjected to outlier and homogeneity analysis before performing CV-ANOVA to determine BV and analytical variation (CVA) estimates with confidence intervals (CI). RESULTS: The within-subject BV estimates [CVI (95% CI)] were similar for enzymatic [4.4% (4.2-4.7)] and alkaline picrate [4.7% (4.4-4.9)] methods and lower than the estimate presently available online (CVI = 5.9%). No significant male/female BV differences were found. Significant differences were observed in mean creatinine values between men and women and between Turkish individuals and those of other nationalities. Between-subject BV (CVG) estimates, stratified accordingly, produced CVG values similar to historical BV data. CVA was 1.1% for the enzymatic and 4.4% for alkaline picrate methods, indicating that alkaline picrate methods fail to fulfill analytical performance specifications for imprecision (CVAPS). CONCLUSIONS: The serum creatinine CVI obtained by EuBIVAS specifies a more stringent CVAPS than previously identified. The alkaline picrate method failed to meet this CVAPS, raising questions regarding its future use.

Biological Variation Estimates Obtained from 91 Healthy Study Participants for 9 Enzymes in Serum.

BACKGROUND: We sought to develop estimates of biological variation (BV) for 9 enzymes in blood serum as part of the European Biological Variation Study. METHODS: Ninety-one healthy study participants (38 male and 53 female, 21-69 years old) were phlebotomized in each of 10 consecutive weeks at 6 European laboratories. The same preanalytical sample-handling protocol was followed at each center before transport to San Raffaele Hospital, Milan, Italy, for analysis. Sera were stored at -80 °C before analysis in duplicate within a single run on an ADVIA 2400 Clinical Chemistry System (Siemens Healthcare) following a protocol designed to minimize analytical imprecision. Assay traceability was established using frozen sera with target values assigned by reference methods. The results were subjected to outlier analysis before CV-ANOVA to deliver valid BV estimates. Results for 9 enzymes were subsequently partitioned for graphical display allowing visual assessment of the effects of country of origin, sex, and age on BV estimates. RESULTS: We found no effect of country upon the observed variation, but overall sex-related differences were evident for alanine amino transferase (ALT), γ-glutamyl transferase (GGT), and creatine kinase (CK). The following estimates for within-subject BV (CVI) and between-subject BV (CVG), respectively, were obtained: ALT: 9.3%, 28.2%; aspartate aminotransferase: 9.5%, 20.3%; GGT: 8.9%, 41.7%; alkaline phosphatase : 5.3%, 24.9%; lactate dehydrogenase: 5.2%, 12.6%; CK: 14.5%, 31.5%; amylase: 6.8%, 30.4%; pancreatic α-amylase: 6.3%, 24.9%; and lipase (LIP): 7.7%, 23.8%. CONCLUSIONS: All CVI and some CVG estimates were lower than those reported in the online BV 2014 updated database. Analytical performance specifications derived from BV can be applied internationally.

Sample collections from healthy volunteers for biological variation estimates' update: a new project undertaken by the Working Group on Biological Variation established by the European Federation of Clinical Chemistry and Laboratory Medicine.

BACKGROUND: Biological variation (BV) data have many fundamental applications in laboratory medicine. At the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) the reliability and limitations of current BV data were discussed. The EFLM Working Group on Biological Variation is working to increase the quality of BV data by developing a European project to establish a biobank of samples from healthy subjects to be used to produce high quality BV data. METHODS: The project involved six European laboratories (Milan, Italy; Bergen, Norway; Madrid, Spain; Padua, Italy; Istanbul, Turkey; Assen, The Netherlands). Blood samples were collected from 97 volunteers (44 men, aged 20-60 years; 43 women, aged 20-50 years; 10 women, aged 55-69 years). Initial subject inclusion required that participants completed an enrolment questionnaire to verify their health status. The volunteers provided blood specimens once per week for 10 weeks. A short questionnaire was completed and some laboratory tests were performed at each sampling consisting of blood collected under controlled conditions to provide serum, K2EDTA-plasma and citrated-plasma samples. RESULTS: Samples from six out of the 97 enroled subjects were discarded as a consequence of abnormal laboratory measurements. A biobank of 18,000 aliquots was established consisting of 120 aliquots of serum, 40 of EDTA-plasma, and 40 of citrated-plasma from each subject. The samples were stored at -80 °C. CONCLUSIONS: A biobank of well-characterised samples collected under controlled conditions has been established delivering a European resource to enable production of contemporary BV data.

A checklist for critical appraisal of studies of biological variation.

Data on biological variation are used for many purposes in laboratory medicine but concern exists over the validity of the data reported in some studies. A critical appraisal checklist has been produced by a working group established by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) to enable standardised assessment of existing and future publications of biological variation data. The checklist identifies key elements to be reported in studies to enable safe accurate and effective transport of biological variation data sets across healthcare systems. The checklist is mapped to the domains of a minimum data set required to enable this process.

The European biological variation study (EuBIVAS): Biological variation data for testosterone, follicle stimulating hormone, prolactin, luteinizing hormone and dehydroepiandrosterone sulfate in men.

BACKGROUND: Knowledge of biological variation (BV) of hormones is essential for interpretation of laboratory tests and for diagnostics of endocrinological and reproductive diseases. There is a lack of robust BV data for many hormones in men. METHODS: We used serum samples collected weekly over 10 weeks from the European Biological Variation Study (EuBIVAS) to determine BV of testosterone, follicle-stimulating hormone (FSH), prolactin, luteinizing hormone (LH) and dehydroepiandrosterone sulfate (DHEA-S) in 38 men. We derived within-subject (CVI) and between-subject (CVG) BV estimates by CV-ANOVA after trend, outlier, and homogeneity analysis and calculated reference change values, index of individuality (II), and analytical performance specifications. RESULTS: The CVI estimates were 10 % for testosterone, 8 % for FSH, 13 % for prolactin, 22 % for LH, and 9 % for DHEA-S, respectively. The IIs ranged between 0.14 for FSH to 0.66 for LH, indicating high individuality. CONCLUSIONS: In this study, we have used samples from the highly powered EuBIVAS study to derive BV estimates for testosterone, FSH, prolactin, LH and DHEA-S in men. Our data confirm previously published BV estimates of testosterone, FSH and LH. For prolactin and DHEA-S BV data for men are reported for the first time.

A systematic review of data on biological variation for alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transferase.

BACKGROUND: Alanine aminotransferase (ALT), aspartate aminotransferase (AST) and γ-glutamyl transferase (GGT) are enzymes measured in serum or plasma to investigate liver disease. The aim of this work is to assess the validity of published biological variation (BV) data currently available for these enzymes. METHODS: Publications containing BV data for ALT, AST and GGT were identified by searching PubMed using the following keywords: biological varia*, RCV, CV(w), CV(i), CV(b), and CV(g). The 95% confidence intervals for the within- and between-subject coefficients of variation were calculated using the analytical imprecision, the number of subjects, samples and replicates. RESULTS: The searches identified 10 publications with ALT, 14 with AST and nine with GGT data. The protocols presented in those publications as used were varied. The ranges of within-subject variation reported were: ALT: 11.1%-58.1%, AST: 3.0%-32.3% and for GGT: 3.9%-14.5%. The median values (ALT: 18.0%, AST: 11.9% and GGT: 13.8%) were similar to those listed in a BV database commonly used as a reference source. CONCLUSIONS: Published BV data for ALT, AST and GGT demonstrate a wide range of values derived from inconsistent protocols. The quality of the presentations of the data is variable. These findings raise concerns around the utility of the data currently available and highlight the need for critical appraisal of such publications. The working group on BV of the European Federation of Clinical Chemistry and Laboratory Medicine is undertaking work to develop a critical appraisal checklist for the production and publication of reliable BV data.