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.

Impact of ultra-low temperature long-term storage on the preanalytical variability of twenty-one common biochemical analytes.

OBJECTIVES: Retrospective studies frequently assume analytes long-term stability at ultra-low temperatures. However, these storage conditions, common among biobanks and research, may increase the preanalytical variability, adding a potential uncertainty to the measurements. This study is aimed to evaluate long-term storage stability of different analytes at <-70 °C and to assess its impact on the reference change value formula. METHODS: Twenty-one analytes commonly measured in clinical laboratories were quantified in 60 serum samples. Samples were immediately aliquoted and frozen at <-70 °C, and reanalyzed after 11 ± 3.9 years of storage. A change in concentration after storage was considered relevant if the percent deviation from the baseline measurement was significant and higher than the analytical performance specifications. RESULTS: Preanalytical variability (CVP) due to storage, determined by the percentage deviation, showed a noticeable dispersion. Changes were relevant for alanine aminotransferase, creatinine, glucose, magnesium, potassium, sodium, total bilirubin and urate. No significant differences were found in aspartate aminotransferase, calcium, carcinoembryonic antigen, cholesterol, C-reactive protein, direct bilirubin, free thryroxine, gamma-glutamyltransferase, lactate dehydrogenase, prostate-specific antigen, triglycerides, thyrotropin, and urea. As nonnegligible, CVP must remain included in reference change value formula, which was modified to consider whether one or two samples were frozen. CONCLUSIONS: After long-term storage at ultra-low temperatures, there was a significant variation in some analytes that should be considered. We propose that reference change value formula should include the CVP when analyzing samples stored in these conditions.

Critical review and meta-analysis of biological variation estimates for tumor markers.

OBJECTIVES: Biological variation data (BV) can be used for different applications, but this depends on the availability of robust and relevant BV data. In this study, we aimed to summarize and appraise BV studies for tumor markers, to examine the influence of study population characteristics and concentrations on BV estimates and to discuss the applicability of BV data for tumor markers in clinical practice. METHODS: Studies reporting BV data for tumor markers related to gastrointestinal, prostate, breast, ovarian, haematological, lung, and dermatological cancers were identified by a systematic literature search. Relevant studies were evaluated by the Biological Variation Data Critical Appraisal Checklist (BIVAC) and meta-analyses were performed for BIVAC compliant studies to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV with 95% CI. RESULTS: The systematic review identified 49 studies delivering results for 22 tumor markers; four papers received BIVAC grade A, 3 B, 27 C and 15 D. Out of these, 29 CVI and 29 CVG estimates met the criteria to be included in the meta-analysis. Robust data are lacking to conclude on the relationship between BV and different disease states and tumor marker concentrations. CONCLUSIONS: This review identifies a lack of high-quality BV studies for many tumor markers and a need for delivery of BIVAC compliant studies, including in different disease states and tumor marker concentrations. As of yet, the state-of-the-art may still be the most appropriate model to establish analytical performance specifications for the majority of tumor markers.

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.

Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes.

OBJECTIVES: Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma; albumin, creatinine, cystatin C, chloride, potassium, sodium and urea. CONTENT: Relevant studies were identified from a historical BV database as well as by systematic literature searches. Retrieved publications were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC compliant studies with similar design were performed to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV estimates. Out of the 61 identified papers, three received a BIVAC grade A, four grade B, 48 grade C, five grade D grade and one was not appraised as it did not report numerical BV estimates. Most studies were identified for creatinine (n=48). BV estimates derived from the meta-analysis were in general lower than previously reported estimates for all analytes except urea. For some measurands, BV estimates may be influenced by age or states of health, but further data are required. SUMMARY: This review provides updated global BV estimates for kidney related measurands. For all measurands except for urea, these estimates were lower than previously reported. OUTLOOK: For the measurands analyzed in this review, there are sufficient well-designed studies available to publish a trustworthy estimate of BV. However, for a number of newly appearing kidney markers no suitable data is available and additional studies are required.

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.

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.

Biological variation estimates for prostate specific antigen from the European Biological Variation Study; consequences for diagnosis and monitoring of prostate cancer.

BACKGROUND: Prostate-specific antigen (PSA) is central in the diagnosis of prostate cancer. However, high-quality biological variation (BV) estimates for PSA are scarce. Here BV estimates from the European Biological Variation Study (EuBIVAS) for total (tPSA), free (fPSA), conjugated PSA (cPSA), and percent free PSA (%fPSA) are provided. METHOD: EuBIVAS samples were collected weekly from thirty-seven healthy males (22-59 years) for 10 weeks. All samples, stored at -80 °C, were measured in duplicate with a Roche Cobas e801. Outlier and homogeneity analysis were performed followed by CV-ANOVA to determine BV, analytical variation, analytical performance specifications (APS), reference change values (RCV) and the number of samples required to estimate the homeostatic set points. RESULTS: Within-subject BV estimates were for tPSA 6.8% (6.1-7.4); fPSA 7.1% (6.5-7.7) cPSA: 8.8% (8.0-9.7) and %fPSA 5.3% (4.8-5.8), delivering RCV for increase of 15-20% and indicating that one sample is sufficient to estimate the homeostatic set points within ±15%. BV estimates for tPSA were lower than previously published estimates. Estimates for fPSA, cPSA and %fPSA have not previously been reported in healthy subjects. CONCLUSIONS: Highly powered EuBIVAS BV estimates of tPSA, fPSA, cPSA and %fPSA provide updated APS and RCV for monitoring for prostate cancer.

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.

Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference.

This paper, prepared by the EFLM Task and Finish Group on Allocation of laboratory tests to different models for performance specifications (TFG-DM), is dealing with criteria for allocating measurands to the different models for analytical performance specifications (APS) recognized in the 1st EFLM Strategic Conference Consensus Statement. Model 1, based on the effect of APS on clinical outcome, is the model of choice for measurands that have a central role in the decision-making of a specific disease or clinical situation and where cut-off/decision limits are established for either diagnosing, screening or monitoring. Total cholesterol, glucose, HbA1c, serum albumin and cardiac troponins represent practical examples. Model 2 is based on components of biological variation and should be applied to measurands that do not have a central role in a specific disease or clinical situation, but where the concentration of the measurand is in a steady state. This is best achieved for measurands under strict homeostatic control in order to preserve their concentrations in the body fluid of interest, but it can also be applied to other measurands that are in a steady state in biological fluids. In this case, it is expected that the "noise" produced by the measurement procedure will not significantly alter the signal provided by the concentration of the measurand. This model especially applies to electrolytes and minerals in blood plasma (sodium, potassium, chloride, bicarbonate, calcium, magnesium, inorganic phosphate) and to creatinine, cystatin C, uric acid and total protein in plasma. Model 3, based on state-of-the-art of the measurement, should be used for all the measurands that cannot be included in models 1 or 2.

Clinical, operational and economic outcomes of point-of-care blood gas analysis in COPD patients.

INTRODUCTION: Arterial blood gas analysis is relevant in chronic obstructive pulmonary disease (COPD) management. The aim of this study was to evaluate whether the use of a blood gas analyzer in pulmonology departments improves the clinical, operational and economic outcomes when compared with clinical laboratory measurements. PATIENTS AND METHODS: It is an observational prospective study. 112 patients were selected. After specimen collection, the measurement was performed both in pulmonology office as point-of-care and in laboratory. We evaluated clinical outcomes (modification of the indication of long-term oxygen therapy (LTOT) according to results, changes in blood gas analysis results, relationship of the partial pressure of oxygen (PaO2) obtained in the medical visit and velocity of change of the PaO2, influence of total haemoglobin concentration and the change in PaO2), operational outcomes (turnaround time (TAT) from specimen collection to receiving the blood gas analysis report) and economic outcomes (overall cost per process of patient care). RESULTS: There were discrepancies in the indication of LTOT in 13.4% of patients. All parameters showed changes. PaO2 levels showed changes in 2 ways, though they frequently increase over time. The correlation was not good in the other two clinical outcomes. The median TATs in pulmonology office were 1 min versus 79 in laboratory, with 52 min for specimen preparation and transport and 17 min for TAT intralaboratory. The overall cost for the 112 patients in pulmonology office and laboratory was 16,769.89€ and 22,260.97€ respectively. CONCLUSIONS: The use of a blood gas analyzer in a pulmonology office improves clinical, operational and economic outcomes when compared with clinical laboratory.