European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates for serum biointact parathyroid hormone based on weekly samplings from 91 healthy participants

The biological variation of serum 1,25-dihydroxyvitamin D and parathyroid hormone, and plasma fibroblast growth factor 23 in healthy individuals

BACKGROUND AND AIMS

Measuring 1,25-dihydroxyvitamin D (1,25(OH)2D), parathyroid hormone 1-84 (PTH 1-84) and intact FGF23 (iFGF23) is crucial for diagnosing a variety of diseases affecting bone and mineral homeostasis. Biological variability (BV) data are important for defining analytical quality specifications (APS), the usefulness of reference intervals, and the significance of variations in serial measurements in the same subject. The aim of this study was to pioneer the provision of BV estimates for 1,25(OH)2D and to improve existing BV estimates for iFGF23 and PTH 1-84.

MATERIALS AND METHODS

Serum and plasma-EDTA samples of sixteen healthy subjects have been collected for seven weeks and measured in duplicate by chemiluminescent immunoassay on the DiaSorin Liaison platform. After variance verification, within-subject (CVI) and between-subject (CVG) BV estimates were assessed by either standard ANOVA, or CV-ANOVA. The APSs were calculated according to the EFLM-BV-model.

RESULTS

We found the following CVI estimates with 95% confidence intervals:1,25(OH)2D, 22.2% (18.9-26.4); iFGF23, 16.1% (13.5-19.5); and PTH 1-84, 17.9% (14.8-21.8). The CVG were: 1,25(OH)2D, 21.2% (14.2-35.1); iFGF23, 21.1% (14.5-35.8); and PTH 1-84, 31.1% (22.1-50.8).

CONCLUSIONS

We report for the first time BV estimates for 1,25(OH)2D and enhance existing data about iFGF23-BV and PTH 1-84-BV through cutting-edge immunometric methods.

Determination of parathyroid hormone: from radioimmunoassay to LCMS/MS

Parathyroid hormone (PTH) determination is of paramount importance for the exploration of diseases related with calcium metabolism and for the follow-up of patients suffering from bone and mineral disorders associated with chronic kidney diseases (CKD-MBD). Unfortunately, the biologically active form of PTH, i.e. 1-84 PTH, circulates in the blood stream with many fragments and post-translationally modified forms, which decreases the specificity of immunoassays. The assays used to measure PTH, either from 2nd or 3rd generation, are not standardised, which may lead to interpretation errors and clinical consequences. Reference ranges for PTH have neither been always correctly established and the stability of the peptide is also a matter of concern. Fortunately, these last years, newer techniques using mass spectrometry (either high resolution or triple quadripole) coupled with liquid chromatography have been developed, which will help to standardise the different assays. Indeed, PTH assays standardisation is one of the task of the IFCC Committee for Bone Metabolism. Such standardisation will allow a better consistency in the interpretation of the results and will promote studies aiming at the establishment of correct reference ranges.

Biological variation: recent development and future challenges

Biological variation (BV) data have many applications in laboratory medicine. However, these depend on the availability of relevant and robust BV data fit for purpose. BV data can be obtained through different study designs, both by experimental studies and studies utilizing previously analysed routine results derived from laboratory databases. The different BV applications include using BV data for setting analytical performance specifications, to calculate reference change values, to define the index of individuality and to establish personalized reference intervals. In this review, major achievements in the area of BV from last decade will be presented and discussed. These range from new models and approaches to derive BV data, the delivery of high-quality BV data by the highly powered European Biological Variation Study (EuBIVAS), the Biological Variation Data Critical Appraisal Checklist (BIVAC) and other standards for deriving and reporting BV data, the EFLM Biological Variation Database and new applications of BV data including personalized reference intervals and measurement uncertainty.

Qualitative and quantitative comparison of different commercially available 1-84 parathyroid hormone proteins to the WHO international standard 95/646 using orthogonal methods

Relative quantitation methods rely on the use of reference substances to determine the content of samples. The aim of this study was to compare 1-84 parathyroid hormone (PTH) standards from different manufacturers to the WHO international standard 95/646. CE and LC with UV detection were investigated as quick and inexpensive quantitation methods, with an emphasis on selectivity between intact 1-84 PTH and its oxidized forms. Both methods were fully validated according to ICH Q2R1. Moreover, method performance was also evaluated according to guidelines defining the maximum allowable measurement uncertainty (MU) of a biological parameter from its intraindividual variation (CV_I), as well as the proportion of that MU devoted to the reference material. This study highlighted the fact that some 1-84 PTH standards have a content that is actually twice as high as the one stated on the label, which was confirmed by an amino acid analysis investigation. Our approach offers a quick and inexpensive way to estimate the content of 1-84 PTH standards.

Comparison of four indirect (data mining) approaches to derive within-subject biological variation

OBJECTIVES

Within-subject biological variation (CV _i ) is a fundamental aspect of laboratory medicine, from interpretation of serial results, partitioning of reference intervals and setting analytical performance specifications. Four indirect (data mining) approaches in determination of CV _i were directly compared.

METHODS

Paired serial laboratory results for 5,000 patients was simulated using four parameters, d the percentage difference in the means between the pathological and non-pathological populations, CV _i the within-subject coefficient of variation for non-pathological values, f the fraction of pathological values, and e the relative increase in CV _i of the pathological distribution. These parameters resulted in a total of 128 permutations. Performance of the Expected Mean Squares method (EMS), the median method, a result ratio method with Tukey's outlier exclusion method and a modified result ratio method with Tukey's outlier exclusion were compared.

RESULTS

Within the 128 permutations examined in this study, the EMS method performed the best with 101/128 permutations falling within ±0.20 fractional error of the 'true' simulated CV _i , followed by the result ratio method with Tukey's exclusion method for 78/128 permutations. The median method grossly under-estimated the CV _i . The modified result ratio with Tukey's rule performed best overall with 114/128 permutations within allowable error.

CONCLUSIONS

This simulation study demonstrates that with careful selection of the statistical approach the influence of outliers from pathological populations can be minimised, and it is possible to recover CV _i values close to the 'true' underlying non-pathological population. This finding provides further evidence for use of routine laboratory databases in derivation of biological variation components.

The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurands

OBJECTIVES

The European Biological Variation Study (EuBIVAS), which includes 91 healthy volunteers from five European countries, estimated high-quality biological variation (BV) data for several measurands. Previous EuBIVAS papers reported no significant differences among laboratories/population; however, they were focused on specific set of measurands, without a comprehensive general look. The aim of this paper is to evaluate the homogeneity of EuBIVAS data considering multivariate information applying the Principal Component Analysis (PCA), a machine learning unsupervised algorithm.

METHODS

The EuBIVAS data for 13 basic metabolic panel linked measurands (glucose, albumin, total protein, electrolytes, urea, total bilirubin, creatinine, phosphatase alkaline, aminotransferases), age, sex, menopause, body mass index (BMI), country, alcohol, smoking habits, and physical activity, have been used to generate three databases developed using the traditional univariate and the multivariate Elliptic Envelope approaches to detect outliers, and different missing-value imputations. Two matrix of data for each database, reporting both mean values, and "within-person BV" (CV_P) values for any measurand/subject, were analyzed using PCA.

RESULTS

A clear clustering between males and females mean values has been identified, where the menopausal females are closer to the males. Data interpretations for the three databases are similar. No significant differences for both mean and CV_Ps values, for countries, alcohol, smoking habits, BMI and physical activity, have been found.

CONCLUSIONS

The absence of meaningful differences among countries confirms the EuBIVAS sample homogeneity and that the obtained data are widely applicable to deliver APS. Our data suggest that the use of PCA and the multivariate approach may be used to detect outliers, although further studies are required.

Should clinical laboratories adapt to the reality of chronic kidney disease in the determination of parathyroid hormone?

Objectives

The contribution of the clinical laboratory to diagnostics is increasingly important since a great deal of clinical decisions rely on laboratory test results.

Content

Parathyroid hormone (PTH) measurement presents a considerable analytical variability due to the heterogeneity of its circulating forms and the antigenic configuration of the different assays commercially available. Such variability may have an impact on pathological conditions associated with significant increases in circulating PTH, as it is the case of chronic kidney disease (CKD).

Summary

Despite the recent identification of new molecules involved in bone and mineral disorders associated with CKD, such as klotho or the fibroblastic factor 23 (FGF23), nephrologists still base their clinical decisions on PTH concentrations. The problem is that unawareness of these analytical considerations may cause errors in the clinical interpretation of test results.

Outlook

This systematic review addresses these issues from the clinical laboratory perspective and proposes new approaches related to PTH method selection and result expression. These new strategies will help laboratory medicine specialists and nephrologist better determine the status of CKD patients.

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-β 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 estimates for serum thyroid biomarkers based on weekly samplings from 91 healthy participants

OBJECTIVES

Thyroid biomarkers are fundamental for the diagnosis of thyroid disorders and for the monitoring and treatment of patients with these diseases. The knowledge of biological variation (BV) is important to define analytical performance specifications (APS) and reference change values (RCV). The aim of this study was to deliver BV estimates for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), thyroglobulin (TG), and calcitonin (CT).

METHODS

Analyses were performed on serum samples obtained from the European Biological Variation Study population (91 healthy individuals from six European laboratories; 21-69 years) on the Roche Cobas e801 at the San Raffaele Hospital (Milan, Italy). All samples from each individual were evaluated in duplicate within a single run. The BV estimates with 95% CIs were obtained by CV-ANOVA, after analysis of variance homogeneity and outliers.

RESULTS

The within-subject (CV _I ) BV estimates were for TSH 17.7%, FT3 5.0%, FT4 4.8%, TG 10.3, and CT 13.0%, all significantly lower than those reported in the literature. No significant differences were observed for BV estimates between men and women.

CONCLUSIONS

The availability of updated, in the case of CT not previously published, BV estimates for thyroid markers based on the large scale EuBIVAS study allows for refined APS and associated RCV applicable in the diagnosis and management of thyroid and related diseases.