Reference Change Values for Brain Natriuretic Peptides Revisited

High-sensitivity troponins in dialysis patients: variation and prognostic value

Background

Dialysis patients have a high prevalence of cardiovascular mortality but also elevated cardiac troponins (cTns) even without signs of cardiac ischaemia. The study aims to assess variation and prognostic value of high-sensitivity cTnI and cTnT in prevalent dialysis patients.

Methods

In 198 prevalent haemodialysis (HD) and 78 peritoneal dialysis (PD) patients, 4-monthly serum troponin I and T measurements were obtained. Reference change values (RCVs) were used for variability assessment and competing-risk regression models for survival analyses; maximal follow-up was 50 months.

Results

HD and PD patients had similar troponin levels [median (interquartile range) troponin I: 25 ng/L (14–43) versus 21 ng/L (11–37), troponin T: 70 ng/L (44–129) versus 67 ng/L (43–123)]. Of troponin I and T levels, 42% versus 98% were above the decision level of myocardial infarction. RCVs were +68/−41% (troponin I) and +29/−23% (troponin T). Increased variability of troponins related to higher age, male sex, protein-energy wasting and congestive heart failure, but not ischaemic heart disease or dialysis form. Elevated troponin T, but not troponin I, predicted death after adjusting for confounders.

Conclusions

A large proportion of prevalent dialysis patients without current established or ongoing cardiac events have elevated levels of high-sensitivity cTns. Mortality risk was doubled in patients with persistently high troponin T levels. The large intraindividual variation of cTns suggests that serial measurements and reference change levels may be used to improve diagnostic utility. However, evidence-based recommendations require more data from large studies of dialysis patients with cardiac events.

Analytical Performance Specifications for Lipoprotein(a), Apolipoprotein B-100, and Apolipoprotein A-I Using the Biological Variation Model in the EuBIVAS Population

BACKGROUND

With increased interest in lipoprotein(a) (Lp[a]) concentration as a target for risk reduction and growing clinical evidence of its impact on cardiovascular disease (CVD) risk, rigorous analytical performance specifications (APS) and accuracy targets for Lp(a) are required. We investigated the biological variation (BV) of Lp(a), and 2 other major biomarkers of CVD, apolipoprotein A-I (apoA-I) and apolipoprotein B-100 (apoB), in the European Biological Variation Study population.

METHOD

Serum samples were drawn from 91 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate on a Roche Cobas 8000 c702. Outlier, homogeneity, and trend analysis were performed, followed by CV-ANOVA to determine BV estimates and their 95% CIs. These estimates were used to calculate APS and reference change values. For Lp(a), BV estimates were determined on normalized concentration quintiles.

RESULTS

Within-subject BV estimates were significantly different between sexes for Lp(a) and between women aged <50 and >50 years for apoA-I and apoB. Lp(a) APS was constant across concentration quintiles and, overall, lower than APS based on currently published data, whereas results were similar for apoA-I and apoB.

CONCLUSION

Using a fully Biological Variation Data Critical Appraisal Checklist (BIVAC)-compliant protocol, our study data confirm BV estimates of Lp(a) listed in the European Federation of Clinical Chemistry and Laboratory Medicine database and reinforce concerns expressed in recent articles regarding the suitability of older APS recommendations for Lp(a) measurements. Given the heterogeneity of Lp(a), more BIVAC-compliant studies on large numbers of individuals of different ethnic groups would be desirable.

Within-subject and between-subject biological variation of first morning void urine amino acids in 12 healthy subjects

Background Urine amino acid analysis is used for the assessment of various diseases. The aim of this study was to estimate the valid biological variation (BV) components (within- and between-subjects) required for the safe clinical application of free urine amino acids. Methods First morning void urine samples were taken from 12 healthy subjects (five females, seven males) once a week for 10 consecutive weeks, and amino acid analysis was performed using an Agilent 6470 triple quadrupole tandem mass spectrometer instrument. The obtained data were subjected to normality, outlier and variance homogeneity analyses prior to coefficient of variation (CV) analysis. Within- and between-subject BV values (CVI and CVG) of 39 amino acids were determined for all subjects. In addition, the index of individuality (II), reference change value (RCV), imprecision, bias and total error were estimated using BV data obtained from our study. Results The CVI values ranged from 8.9 (histidine) to 36.8% (trans-4-hydroxyprolin), while the CVG values ranged from 25.0 (1-methyl-L-histidine) to 63.3% (phenylalanine). The II value of most amino acids was less than 0.6 and ranged between 0.21 and 0.88. The imprecision, bias and total error ranged between 4.45 and 16.6, between 7.69 and 16.6, and between 18.4 and 43.2, respectively. Conclusions This study, designed according to a rigorous protocol, has the feature of being the first to give information about BV data of urine amino acids. We believe that the reference intervals have a limitation in the evaluation of consecutive results from an individual, so the use of RCV would be more appropriate.

An Analysis of Variability in "CatWalk" Locomotor Measurements to Aid Experimental Design and Interpretation

Preclinical studies in models of neurologic injury and disease rely on behavioral outcomes to measure intervention efficacy. For spinal cord injury, the CatWalk system provides unbiased quantitative assessment of subtle aspects of locomotor function in rodents and so can powerfully detect significant differences between experimental and control groups. Although clearly of key importance, summary group-level data can obscure the variability within and between individual subjects and therefore make it difficult to understand the magnitude of effect in individual animals and the proportion of a group that may show benefit. Here, we calculate reference change intervals (RCIs) that define boundaries of normal variability for measures of rat locomotion on the CatWalk. Our results indicate that many commonly-used outcome measures are highly variable, such that differences of up to 70% from baseline value must be considered normal variation. Many CatWalk outcome variables are also highly correlated and dependent on run speed. Application of calculated RCIs to open access data (https://scicrunch.org/odc-sci) on hindlimb stride length in spinal cord-injured rats illustrates the complementarity between group-level (16 mm change; p = 0.0009) and individual-level (5/32 animals show change outside RCI boundaries) analysis between week 3 and week 6 after injury. We also conclude that interdependence among CatWalk variables implies that test “batteries” require careful composition to ensure that different aspects of defective gait are analyzed. Calculation of RCIs aids in experimental design by quantifying variability and enriches overall data analysis by providing details of change at an individual level that complement group-level analysis.

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

Background

The European Biological Variation Study (EuBIVAS) was created by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation to establish high-quality biological variation (BV) estimates for clinically important measurands. In this study, the aim was to deliver reliable BV estimates for the biointact parathyroid hormone (PTH 1-84).

Methods

Serum samples were obtained from a population of 91 healthy individuals (38 men, 43 pre-menopausal women, and 10 post-menopausal women; 21-69 years) from 5 European countries, with all samples stored at -80 °C prior to analysis. PTH 1-84 analysis was performed at the San Raffaele Hospital (Milan, Italy) on the Roche Cobas e801. All samples from each individual were analysed in duplicate within a single run. CV-ANOVA was applied, after analysis of variance homogeneity and outliers, to obtain BV estimates for PTH 1-84 with 95% CIs.

Results

The within-subject BV [CV_I (95% CI)] estimates were significantly different between men and women [13.0% (12.1-14.2%) and 15.2% (14.3-16.3%), respectively], while the between-subject estimates [CV_G (95% CI)] were similar (men: 26.8% (21.4-35.1%), pre-menopausal women: 27.8% (22.7-36.1%)], allowing for delivery of updated analytical performance specifications and reference change values.

Conclusions

Updated BV estimates for serum PTH 1-84 based on the large-scale EuBIVAS may be beneficial for the diagnosis and management of parathyroid glands and bone turnover pathologies.

Short-term biological variation of serum thyroid hormones concentrations in clinically healthy cats

Thyroid disease is common in cats, but little is known about the biologic variability of serum thyroid hormone concentrations and its impact on diagnostic utility in either healthy cats or cats with thyroid disease. The purpose of this study was to determine the biological variation, index of individuality, and reference change values for thyroid hormones and thyroid-stimulating hormone (TSH) in clinically healthy cats. Serum samples for analysis of total thyroxine (T₄), triiodothyronine (T₃), free T₄ by dialysis, and TSH were obtained weekly for 6 wk from 10 healthy cats, then frozen until single-batch analyzed. Data were evaluated for outliers, and we determined the CV within individual cats (CV_I) and between individual cats (CV_G) for each hormone and the variation between duplicates or analytical variation (CV_A). The index of individuality and reference change values for each hormone were then calculated. Serum concentrations of total T₄, free T₄, T₃, and TSH all showed greater variation between cats (CV_G) than within cats (CV_I). Total and free T₄ had an intermediate index of individuality (1.1 and 1.2, respectively), suggesting that these hormones would be best evaluated by a combination of their population-based reference intervals and reference change values. Serum TSH concentrations had high index of individuality (1.8), suggesting this hormone would be best evaluated with reference change values rather than the population-based reference interval. Total T₃ also had a high calculated index of individuality (1.8); however, T₃ had high ratio of analytical variation (CV_A) to within cat variation (CV_I), so RCV could not be accurately calculated. This study demonstrates that clinically normal cats show considerable interindividual biological variation in serum thyroid hormone and TSH concentrations, whereas the intraindividual variability in hormone concentrations is much narrower. This suggests that for all serum thyroid hormones, but especially serum TSH and T₃ concentrations, comparing individual cat's hormone results to a population-based reference interval may be misleading, especially in those with early or subclinical thyroid disease. Clinicians might improve the diagnosis of feline thyroid disease by establishing baseline concentrations of T₄, free T₄, T₃, and TSH for individual cats (ideally when healthy) and applying reference change values to subsequent measurements.

Biological variation of cardiac troponins in chronic kidney disease

Background

Patients with chronic kidney disease often have increased plasma cardiac troponin concentration in the absence of myocardial infarction. Incidence of myocardial infarction is high in this population, and diagnosis, particularly of non ST-segment elevation myocardial infarction (NSTEMI), is challenging. Knowledge of biological variation aids understanding of serial cardiac troponin measurements and could improve interpretation in clinical practice. The National Academy of Clinical Biochemistry (NACB) recommended the use of a 20% reference change value in patients with kidney failure. The aim of this study was to calculate the biological variation of cardiac troponin I and cardiac troponin T in patients with moderate chronic kidney disease (glomerular filtration rate [GFR] 30–59 mL/min/1.73 m2).

Methods and results

Plasma samples were obtained from 20 patients (median GFR 43.0 mL/min/1.73 m2) once a week for four consecutive weeks. Cardiac troponin I (Abbott ARCHITECT® i2000SR, median 4.3 ng/L, upper 99th percentile of reference population 26.2 ng/L) and cardiac troponin T (Roche Cobas® e601, median 11.8 ng/L, upper 99th percentile of reference population 14 ng/L) were measured in duplicate using high-sensitivity assays. After outlier removal and log transformation, 18 patients’ data were subject to ANOVA, and within-subject (CVI), between-subject (CVG) and analytical (CVA) variation calculated. Variation for cardiac troponin I was 15.0%, 105.6%, 8.3%, respectively, and for cardiac troponin T 7.4%, 78.4%, 3.1%, respectively. Reference change values for increasing and decreasing troponin concentrations were +60%/–38% for cardiac troponin I and +25%/–20% for cardiac troponin T.

Conclusions

The observed reference change value for cardiac troponin T is broadly compatible with the NACB recommendation, but for cardiac troponin I, larger changes are required to define significant change. The incorporation of separate RCVs for cardiac troponin I and cardiac troponin T, and separate RCVs for rising and falling concentrations of cardiac troponin, should be considered when developing guidance for interpretation of sequential cardiac troponin measurements.

Day-to-day and within-day biological variation of cell-free DNA

BACKGROUND

Numerous studies have shown that cell-free DNA (cfDNA) levels may serve as a non-invasive biomarker of a broad spectrum of acute and chronic pathologies. However, in order to make clinical decisions based on cfDNA measurements, it is essential to understand the magnitude of biological variation so this variation is not confused with a variation that actually represent a clinically relevant change. The present study was designed to evaluate the biological variation of cfDNA in healthy subjects and lung cancer patients.

METHODS

Plasma samples were collected from 33 healthy subjects and ten lung cancer patients over three days, as well as during the same day. CfDNA was quantified using droplet digital PCR. Biological variation data was estimated using mixed models.

FINDINGS

The within-subject variation was 25% and the between-subject variation was 30%. The reference change value for the healthy subjects was 70%. There was no systematic difference in cfDNA levels from day-to-day (p = 0⋅61), but there was a significant decline during the day (p<0⋅01). The within-subject variation in cancer patients was comparable to healthy subjects, whereas the between-subject variation was much larger (139%). No systematic differences from day-to-day were observed for the cancer patients (p>0⋅3).

INTERPRETATION

Our findings show that cfDNA levels fluctuate significantly during the day and exhibit considerable within-subject variation. Thus, the data presented offer a substantial contribution to the interpretation of the clinical significance of cfDNA.

FUNDING

Læge Sofus Carl Emil Friis og hustru Olga Doris Friis' Legat, Harboefonden, and Dagmar Marshalls Fond.

Revisiting the Biological Variability of Cardiac Troponin: Implications for Clinical Practice

The diagnosis of acute myocardial injury requires a rise and/or fall of cardiac troponin (cTn) on serial testing, with at least one concentration above the 99th percentile value of a normal reference population according to the recently published Fourth Universal Definition of Myocardial Infarction.1 However, the magnitude of change in cTn that constitutes a significant rise and/or fall was again not specified in detail. High-sensitivity cardiac troponin (hs-cTn) assays can measure ten-fold lower concentrations of cTn with more precision than older assays, and can accurately quantify cTn in more than 50% of healthy individuals with a coefficient of variation of less than 10% at the 99th percentile. These hs-cTn assays are also able to detect the normal variations in cTn results that are due to biological variability. Understanding and quantifying the normal variations in cTn is important as this would allow significant changes to be better defined. Numerous studies have sought to investigate the biological variability of cTn over the last ten years. Such studies are usually conducted in healthy individuals, however individuals with chronic cardiac disease or chronic renal failure have also been examined. These studies have yielded varying results in regards to significant change values for cTn. In light of the recent redefinition for myocardial infarction, the purpose of this mini-review is to revisit the biological variability of cTn. In particular, we outline concepts for determining a significant change value, review the results of previous studies on the biological variation of cTn and discuss potential considerations for clinical practice.

The effect of high-volume online haemodiafiltration on nutritional status and body composition: the ProtEin Stores prEservaTion (PESET) study

Background

Compared with conventional haemodialysis (HD), online haemodiafiltration (OL-HDF) achieves a more efficient removal of uraemic toxins and reduces inflammation, which could favourably affect nutritional status. We evaluate the effect of OL-HDF on body composition and nutritional status in prevalent high-flux HD (HF-HD) patients.

Methods

In all, 33 adults with chronic kidney disease (CKD) Stage 5 undergoing maintenance HF-HD were assigned to post-dilution OL-HDF (n = 17) or to remain on HF-HD (n = 16, control group) for 12 months. The primary outcome was the change in lean tissue mass (LTM), intracellular water (ICW) and body cell mass (BCM) assessed by multifrequency bioimpedance spectroscopy (BIS) at baseline and 4, 8 and 12 months. The rate of change in these parameters was estimated with linear mixed-effects models.

Results

Compared with OL-HDF, patients assigned to HF-HD experienced a gradual reduction in LTM, ICW and BCM. These differences reached statistical significance at Month 12, with a relative difference of 7.31 kg [95% confidence interval (CI) 2.50-12.11; P = 0.003], 2.32 L (95% CI 0.63-4.01; P = 0.008) and 5.20 kg (95% CI 1.74-8.66; P = 0.004) for LTM, ICW and BCM, respectively. The normalized protein appearance increased in the OL-HDF group compared with the HF-HD group [0.26 g/kg/day (95% CI 0.05-0.47); P = 0.002], with a relative reduction in high-sensitive C-reactive protein [-13.31 mg/dL (95% CI -24.63 to -1.98); P = 0.02] at Month 12.

Conclusions

OL-HDF for 1 year compared with HF-HD preserved muscle mass, increased protein intake and reduced the inflammatory state related to uraemia and dialysis, supporting the hypothesis that high convection volume can benefit nutritional status and prevent protein-energy wasting in HD patients.

Concentration of fibrin monomer in pregnancy and during the postpartum period

Background

D-dimer increases during pregnancy and is problematic to use in the diagnosis of venous thromboembolism. Fibrin monomer represents an alternative biomarker for venous thromboembolism. However, to be useful in pregnancy, the fibrin monomer concentration should be stable throughout pregnancy and during postpartum.

Methods

To describe the course of fibrin monomer concentration during pregnancy and the postpartum period in healthy pregnant women and to compare their within-subject biological variation (CVI) with non-pregnant women. Blood samples were obtained every fourth week during pregnancy and three samples after delivery in 20 healthy women and every fourth week during a 40-week period in 19 healthy non-pregnant women. Fibrin monomer (STA Liatest FM, Stago) was analysed in duplicates for all samples. Concentrations of fibrin monomer in pregnant and non-pregnant women were compared and the CVI for fibrin monomer was calculated.

Results

The median fibrin monomer concentration in pregnant women was 6.2 mg/L (2.5 and 97.5 percentiles 3.7–10.8 mg/L) and in non-pregnant women 4.8 mg/L (3.6–8.2) ( P < 0.01). The fibrin monomer concentration was relatively stable during pregnancy, although a few unexplained high fibrin monomer concentrations were found during pregnancy/postpartum. Fibrin monomer CVI in pregnancy and postpartum was 20.6% (95% CI 18.3, 23.5) and in non-pregnant 16.1% (13.7, 18.9).

Conclusions

For clinical purposes, fibrin monomer concentration can be considered stable during pregnancy, although it is slightly higher than in non-pregnant women. Pregnant and non-pregnant women have the same CVI. The suitability of fibrin monomer in venous thromboembolism diagnosis in pregnant women should be validated in further studies.

A Bayesian Approach to Biological Variation Analysis

BACKGROUND

Biological variation (BV) data have many applications for diagnosing and monitoring disease. The standard statistical approaches for estimating BV are sensitive to “noisy data” and assume homogeneity of within-participant CV. Prior knowledge about BV is mostly ignored. The aims of this study were to develop Bayesian models to calculate BV that (a) are robust to “noisy data,” (b) allow heterogeneity in the within-participant CVs, and (c) take advantage of prior knowledge.

METHOD

We explored Bayesian models with different degrees of robustness using adaptive Student t distributions instead of the normal distributions and when the possibility of heterogeneity of the within-participant CV was allowed. Results were compared to more standard approaches using chloride and triglyceride data from the European Biological Variation Study.

RESULTS

Using the most robust Bayesian approach on a raw data set gave results comparable to a standard approach with outlier assessments and removal. The posterior distribution of the fitted model gives access to credible intervals for all parameters that can be used to assess reliability. Reliable and relevant priors proved valuable for prediction.

CONCLUSIONS

The recommended Bayesian approach gives a clear picture of the degree of heterogeneity, and the ability to crudely estimate personal within-participant CVs can be used to explore relevant subgroups. Because BV experiments are expensive and time-consuming, prior knowledge and estimates should be considered of high value and applied accordingly. By including reliable prior knowledge, precise estimates are possible even with small data sets.

Week-to-week biological variation of methylmalonic acid and homocysteine in healthy women

Metylmalonic acid (MMA) and homocysteine (HCY) are important biomarkers in the assessment of cobalamin and folate metabolism. Correct interpretation of patient results benefit from knowledge of biological variation. The aim of the present study was to determine within-subject (CV_I) and between-subject (CV_G) biological variations of serum MMA and HCY in healthy women. We collected blood samples from 12 healthy volunteers (33-61 years) on the same weekday for 10 consecutive weeks. Samples were stored at -80 °C until analysis in duplicate in a single analytical run in random order. The CV_I and CV_G biological variations were estimated by CV-ANOVA after the data were first subjected to outlier and homogeneity analysis. The CV_I (95% CI) for MMA and HCY were 7.2% (6.1-8.5) and 7.4% (6.5-8.5), respectively. The corresponding CV_G were 21.1% (14.0-32.2) and 24.2% (16.2-36.8). The index of individuality (II) was 0.34 for MMA and 0.31 for HCY and the reference change value (RCV) was -17.7; 21.0 (% decrease; increase) for MMA and -16.2; 19.4 for HCY. We provide within- and between-subject biological variation estimates for MMA and HCY in healthy women using an updated protocol. The results will contribute to a better clinical interpretation of these biomarkers and be of aid when setting analytical performance specifications.

Harmonization initiatives in the generation, reporting and application of biological variation data

Biological variation (BV) data have many applications in laboratory medicine. However, concern has been raised that some BV estimates in use today may be irrelevant or of unacceptable quality. A number of initiatives have been launched by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) and other parties to deliver a more harmonized practice in the generation, reporting and application of BV data. Resulting from a necessary focus upon the veracity of historical BV studies, critical appraisal and meta-analysis of published BV studies is possible through application of the Biological Variation Data Critical Appraisal Checklist (BIVAC), published in 2017. The BIVAC compliant large-scale European Biological Variation Study delivers updated high-quality BV data for a wide range of measurands. Other significant developments include the publication of a Medical Subject Heading term for BV and recommendations for common terminology for reporting of BV data. In the near future, global BV estimates derived from meta-analysis of BIVAC appraised publications will be accessible in a Biological Variation Database at the EFLM website. The availability of these high-quality data, which have many applications that impact on the quality and interpretation of clinical laboratory results, will afford improved patient care.

Biological variation of cardiac markers in patients with aortic valve stenosis

Objective

Cardiac biomarkers hold promise for follow-up and management of aortic valve stenosis (AVS). When interpreting serial biomarker measurements of patients with AVS, it can be challenging to distinguish ‘real changes’ from ‘random fluctuation’. Hence, robust estimation of the biological variation of these biomarkers is essential. In the present study we assessed biological variation of B-type natriuretic peptide (BNP), N-terminus pro-brain natriuretic peptide (NT-proBNP), high-sensitivity troponin-T and high-sensitivity troponin-I (hs-TnT and hs-TnI), and ST2 in subjects with stable AVS.

Methods

Serial blood sampling was performed in 25 subjects with moderate AVS—confirmed by echocardiography—and all free from acute cardiovascular events in the past 6 months. Blood samples were taken on seven standardised occasions during 1 year. Analytical variation (CV_A), within-subject biological variation (CV_I), between-subject biological variation (CV_G), index of individuality (II) and reference change values were calculated for all cardiac biomarkers.

Results

CV_I was highest for BNP (62.0%, 95% CI 52.5 to 75.4) and lowest for hs-TnI (9.2%, 95% CI 2.8 to 13.8). CV_G exceeded the CV_I for all biomarkers except BNP, and ranged from 19.8% (95% CI 13.8 to 33.4) for ST2 to 57.2% (95% CI 40.4 to 97.3) for hs-TnT. NT-proBNP, hs-TnT and ST2 revealed CV_A <5%, while BNP and hs-TnI showed a higher CV_A (19.7 and 14.9, respectively). All biomarkers except BNP showed marked individuality, with II ranging from 0.21 to 0.67 (BNP 1.34).

Conclusion

This study provides the first biological variation estimates of cardiac biomarkers in patients with stable AVS. These estimates allow a more evidence-based interpretation of biomarker changes in the follow-up and management of patients with AVS.

Trial registration number

NCT02510482

Estimates of Within-Subject Biological Variation Derived from Pathology Databases: An Approach to Allow Assessment of the Effects of Age, Sex, Time between Sample Collections, and Analyte Concentration on Reference Change Values

BACKGROUND

Within-subject biological variation data (CVI) are used to establish quality requirements for assays and allow calculation of the reference change value (RCV) for quantitative clinical laboratory tests. The CVI is generally determined using a large number of samples from a small number of individuals under controlled conditions. The approach presented here is to use a small number of samples (n = 2) that have been collected for routine clinical purposes from a large number of individuals.

METHODS

Pairs of sequential results from adult patients were extracted from a routine pathology database for 29 common chemical and hematological tests. Using a statistical process to identify a central gaussian distribution in the ratios of the result pairs, the total result variation for individual results was determined for 26 tests. The CVI was then calculated by removing the effect of analytical variation.

RESULTS

This approach produced estimates of CVI that, for most of the analytes in this study, show good agreement with published values. The data demonstrated minimal effect of sex, age, or time between samples. Analyte concentration was shown to affect the distributions with first results more distant from the population mean more likely to be followed by a result closer to the mean.

DISCUSSION

The process described here has allowed rapid and simple production of CVI data. The technique requires no patient intervention and replicates the clinical environment, although it may not be universally applicable. Additionally, the effect of regression to the mean described here may allow better interpretation of sequential patient results.

Bias in analytical chemistry: A review of selected procedures for incorporating uncorrected bias into the expanded uncertainty of analytical measurements and a graphical method for evaluating the concordance of reference and test procedures

The Evaluation of measurement data - Guide to the Expression of Uncertainty in Measurement (GUM) provides the framework for evaluating measurement uncertainty. The preferred GUM approach for addressing bias assumes that all systematic errors are identified and corrected at an early stage in the measurement process. We review some procedures for treating uncorrected bias and its inclusion into an overall uncertainty statement. When bias and its uncertainty are recognised as metrological states independent of scatter in the test results, the uncertainty of the reference and uncertainty of the bias can be equated. The net standard uncertainty of a test result is the root-sum-square of the standard uncertainty of the bias and the standard uncertainty of measurements on the test. Since an incomplete and therefore potentially erroneous formula is often used for estimating bias standard uncertainty, we propose an alternative calculation. We next propose a graphical method using a simple algorithm that quantifies the discrepancy between the results of a test measurement and the corresponding reference value, in terms of the percentage overlap of two probability density functions. We propose that bias should be corrected wherever possible and we illustrate this approach using the graphical method. Even though this review is focused principally on analytical chemistry and medical laboratory applications, much of the discussion is applicable to all areas of metrology.

Development and validation of a LC-MS/MS method for the establishment of reference intervals and biological variation for five plasma steroid hormones

BACKGROUND

With liquid chromatography-tandem mass spectrometry (LC-MS/MS) increasingly being used for the quantification of steroid hormones, there is a need for studies that re-establish reference intervals and biological variation in well-defined cohorts.

METHODS

A plasma steroid hormone profiling method using LC-MS/MS for quantification of progesterone, 17-hydroxyprogesterone, androstenedione, testosterone and dihydrotestosterone was developed and validated. For reference interval assessment, 280 well-characterized healthy subjects from the LifeLines cohort were selected, including 40 women using oral contraceptive pills (OCP). The biological variation was examined in 30 healthy individuals. Samples were collected over a period of 4 months with 4 week intervals.

RESULTS

The developed method proved to be robust and sensitive. The reference interval levels in men are higher, whereas in women the levels tend to decrease with increasing age. In addition, women using OCP had lower levels of 17-OH-progesterone and androstenedione. The biological variation is generally higher in women compared to men, especially with regard to the inter-individual variation.

CONCLUSIONS

The gender-specific determination of the reference intervals, together with the observation that the biological variation demonstrated a high degree of variation, allows interpretation of data on individual and group level for improved biochemical characterization of patients in clinical practice.

Biological variation of intact fibroblast growth factor 23 measured on a fully automated chemiluminescent platform

Background

Fibroblast growth factor 23 (FGF23), a potent regulator of phosphate and vitamin D metabolism, is a new biomarker of kidney, bone and cardiovascular disorders. The aim of this study was to assess the biological variation of intact fibroblast growth factor 23 (iFGF23).

Methods

The within-subject (CVI) and between-subject (CVG) biological variations were assessed in 14 healthy volunteers in a six-week protocol (seven samples). Imprecision (CVA) was assessed by duplicate measurements and the EP15-A2 protocol. Intact FGF23 was measured using a fully automated chemiluminescent assay (Liaison XL, DiaSorin S.p.A., Saluggia, Italy). Two methods with different sensitivities to non-Gaussian distribution were used to estimate the CVI, SD ANOVA and CV ANOVA methods. We calculated the index of individuality (II) and reference change values.

Results

Depending on the statistical method used, the CVI and CVA were 14.2 and 3.7% (SD ANOVA) or 12.5 and 3.9% (CV ANOVA), respectively. The corresponding reference change values were 40.5 and 36.4%, respectively. The CVG was 13.4% (SD ANOVA was the only option), and the total imprecision (EP15-A2) was less than 7%.

Conclusions

The measurement of iFGF23 demonstrated a CVA less than 4% during the experimental estimation of biological variation. The total imprecision was less than 7% in the EP15-A2 experiment. The CVI values of iFGF23 in healthy persons were 14.2 (SD ANOVA) and 12.5% (CV ANOVA), respectively. The CVG was 13.4%, and the resulting index of individuality was 1.06. The reference change value was less than 41%. The availability of this automated assay for iFGF23 with well-characterized biological variation data delivers opportunities for improved availability and application of this assay clinically.

Uncertainty of measurement for 14 immunoassay analytes: application to laboratory result interpretation

Laboratory tests are an integral part of clinical decision making. Therefore, measurement uncertainty comes into prominence in the context of the accuracy of the laboratory result. This study aims to investigate measurement uncertainty of 14 immunoassay analytes, to compare them with different quality goals and to utilize them in the result interpretation. Measurement uncertainties of 14 immunoassay analytes were estimated by using internal and external quality control data by using Nordtest approach. Expanded uncertainties (U) were compared with allowable total error (TEa%), permissible relative deviation in the external quality assessment (PRD_EQA%) and permissible expanded uncertainty for external quality assessment (pU_EQAS%). Uncertainties were incorporated into the calculation of reference change values (RCV) and uncertainty adjusted reference intervals. RCVs of 14 analytes were calculated by three different methods reported by Harris, Clinical Laboratory Standards Institute (CLSI), and National Pathology Accreditation Advisory Council (NPAAC). Measurement uncertainties of TSH, estradiol, LH, progesterone, prolactin, and vitamin B12 were within defined allowable limits. U_{one-sided FT3} and U_{one-sided ferritin} exceeded defined TEa% but U_FT3 and U_ferritin were found below the limits of pU_EQAS%. Measurement uncertainties of FT4, cortisol, DHEAS, FSH, testosterone, and folate did not meet the specification limits. Recently defined permissible expanded uncertainty promises new targets to compare estimated measurement uncertainty. Measurement uncertainty should be applied to the laboratory result interpretation within the scope of RCV and reference interval to obviate misdiagnosis. Furthermore, we suggest that laboratories should inform clinicians about the tests with high uncertainties to assist them making the right clinical diagnosis. Abbreviations CLSI: Clinical Laboratory Standards Institute; CV: coefficient of variation; CV_A: analytic coefficient of variation; CV_G: inter-individual coefficient of variation; CV_I: intra-individual coefficient of variation; DHEAS: dehydroepiandrosterone sulfate; FSH: follicle-stimulating hormone; FT3: free triiodothyronine; FT4: free thyroxine; k: coverage factor; LH: luteinizing hormone; LRL: lower reference limit; MD: minimal difference; NPAAC: National Pathology Accreditation Advisory Council; PRD_EQA%: permissible relative deviation in the external quality assessment; pU_EQAS%: permissible expanded uncertainty for external quality assessment; RCV: reference change value; RCV': uncertainty-adjusted reference change value; TSH: thyroid-stimulating hormone; Rw: within-laboratory reproducibility; RMSbias: root mean square of biases; u(Cref): the uncertainty of nominal values; u(bias): uncertainty component for bias; u_c: combined standard uncertainty; TEa%: allowable total error; U: expanded uncertainty; U_one-sided%: one sided estimation of expanded measurement uncertainty using coverage factor "1.65"; URL: upper reference limit.

Biological variation of routine haematology and biochemistry measurands in the horse

BACKGROUND

Clinical pathology results are typically interpreted by referring to population-based reference intervals. The use of individualised (subject-based) reference intervals is more appropriate for measurands with a high degree of variation between individuals.

OBJECTIVES

To determine the biological variation of routinely analysed equine haematology and biochemistry measurands and calculate indices of individuality and reference change values which enable production of individualised reference intervals, in a group of healthy, privately owned horses.

STUDY DESIGN

In a prospective cohort study, thirty-nine privately owned horses were sampled by jugular venipuncture for analysis of haematology and biochemistry measurands at weekly intervals for 6 weeks.

METHODS

Haematology was analysed on the day of collection. Serum was frozen and biochemistry analyses performed on thawed samples. Duplicate results were obtained and the coefficient of variation was calculated for analytical variation, within-subject variation and between-subject variation. The index of individuality and reference change value were derived for each measurand.

RESULTS

Haematology (red blood cell count, mean corpuscular haemoglobin and mean cell volume) and biochemistry measurands (total protein, globulins, albumin, gamma-glutamyl transferase, aspartate aminotransferase) demonstrated high individuality, indicating that individualised reference intervals are more appropriate for evaluation of these measurands. Two haematology (mean corpuscular haemoglobin concentration and platelets) and three biochemistry measurands (chloride, glucose and sodium) had low individuality, indicating that the use of traditional population-based reference intervals is appropriate for these measurands. Remaining measurands had intermediate individuality suggesting interpretation of the reference change value should occur with consideration of the population-based reference interval.

MAIN LIMITATIONS

The use of privately owned horses, variable management and environmental factors.

CONCLUSIONS

The use of individualised reference intervals is justified for many measurands in horses, supporting the use of serial sampling, consideration of biological variation and application of reference change values for improved clinical decision making and patient management in equine practice.

Within-subject biological variation of activated partial thromboplastin time, prothrombin time, fibrinogen, factor VIII and von Willebrand factor in pregnant women

Background:

During pregnancy, interpretation of results from coagulation parameters can be difficult as the physiological changes that occur may affect the biochemical parameters. The aim of this study was to describe the normal course of five coagulation parameters in healthy pregnancies, and to estimate the within-subject biological variation (CVI).

Methods:

Blood samples were obtained every 4th week during pregnancy and three samples after delivery in 20 healthy women and every 4th week during a 40-week period in 19 healthy non-pregnant women. Activated partial thromboplastin time (APTT), prothrombin time (PT), PT International Normalized Ratio (INR), fibrinogen, factor VIII clot (FVIII:C) and von Willebrand factor antigen (vWF:Ag) were analyzed. The physiological changes during pregnancy were compensated by transformation into multiples of the median (MoM) and it is natural logarithm (lnMoM) in order to establish a kind of steady state, and CVIwas calculated from the standard deviation.

Results:

During pregnancy, APTT, PT and INR remained unchanged or decreased, depending upon the reagent used, while fibrinogen, FVIII:C and vWF:Ag increased gradually until delivery. The CVIin pregnancy were 2.2 and 3.0% for APTT, 2.3 and 2.6% for PT, 2.2 and 2.3% for INR, 7.2% for fibrinogen, 12.2% for FVIII:C and 11.3% for vWF:Ag, and corresponded with the CVIin non-pregnant women.

Conclusions:

Transformation of coagulation parameters in healthy pregnancies to MoM is a tool to establish a kind of steady state. Although there is a physiological change in these coagulation parameters during pregnancy, the CVIafter lnMoM transformation was comparable with the CVIof non-pregnant women.

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 (CV_I) 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 CV_I for men and women/women <50 years of age were evident for uric acid, triglycerides, and urea. The CV_A 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.

Natriuretic Peptides in Heart Failure: Atrial and B-type Natriuretic Peptides

The natriuretic peptides play a vital role in normal physiology and as counter-regulatory hormones in heart failure (HF). Clinical assessment of their levels (for B-type natriuretic peptide [BNP], N-terminal proBNP, and the midregion of N-terminal pro-atrial natriuretic peptide) have become valuable tools in diagnosing patients with HF as well as risk stratifying and guiding therapy. Their roles have further expanded beyond HF to other cardiovascular conditions and for risk stratification in asymptomatic individuals. Understanding the clinical use of these hormones is vital to achieving their full potential.

Valid analytical performance specifications for combined analytical bias and imprecision for the use of common reference intervals

Background Many clinical decisions are based on comparison of patient results with reference intervals. Therefore, an estimation of the analytical performance specifications for the quality that would be required to allow sharing common reference intervals is needed. The International Federation of Clinical Chemistry (IFCC) recommended a minimum of 120 reference individuals to establish reference intervals. This number implies a certain level of quality, which could then be used for defining analytical performance specifications as the maximum combination of analytical bias and imprecision required for sharing common reference intervals, the aim of this investigation. Methods Two methods were investigated for defining the maximum combination of analytical bias and imprecision that would give the same quality of common reference intervals as the IFCC recommendation. Method 1 is based on a formula for the combination of analytical bias and imprecision and Method 2 is based on the Microsoft Excel formula NORMINV including the fractional probability of reference individuals outside each limit and the Gaussian variables of mean and standard deviation. The combinations of normalized bias and imprecision are illustrated for both methods. The formulae are identical for Gaussian and log-Gaussian distributions. Results Method 2 gives the correct results with a constant percentage of 4.4% for all combinations of bias and imprecision. Conclusion The Microsoft Excel formula NORMINV is useful for the estimation of analytical performance specifications for both Gaussian and log-Gaussian distributions of reference intervals.

Estimates of Within-Subject Biological Variation of Protein C, Antithrombin, Protein S Free, Protein S Activity, and Activated Protein C Resistance in Pregnant Women

BACKGROUND

In pregnancy, interpretation of results from coagulation parameters can be difficult because of the procoagulant physiological changes. The aim of this study was to describe the course of 5 coagulation parameters (thrombophilia markers) in healthy pregnancies, and to estimate and compare the within-subject biological variation (CVI) of these parameters in healthy pregnant and nonpregnant women.

METHODS

Blood samples were obtained every 4th week during pregnancy and 3 samples after delivery in 20 healthy women and every 4th week during 40 weeks in 19 healthy nonpregnant women. Protein C (PC), antithrombin (AT), protein S free (PS free), protein S activity (PS activity), and activated protein C resistance (with factor V–depleted plasma) (APCR) were analyzed. Before the calculation of CVI, results were transformed into multiples of the median (MoM) and natural logarithm of MoM (lnMoM) to adjust for the physiological changes during pregnancy.

RESULTS

During pregnancy, PC results showed large variability, AT decreased slightly, and PS free and PS activity decreased significantly. Both activated partial thromboplastin time tests used to calculate APCR decreased, and the APCR ratio was constant. The CVI (lnMoM) in pregnancy were for PC 8.4%, for AT 3.8%, for PS free 11.5%, for PS activity 9.3%, and for APCR 0.5%, and similar to corresponding results in nonpregnant women.

CONCLUSIONS

Transformation of coagulation parameters in healthy pregnancies to lnMoM is a tool to establish a kind of steady state. Although there is a physiological change in PC, AT, and PS free and PS activity during pregnancy, the CVI was comparable with the CVI of nonpregnant women.

Diurnal and Long-term Variation in Plasma Concentrations and Renal Clearances of Circulating Markers of Kidney Proximal Tubular Secretion

BACKGROUND

The renal proximal tubule is essential for removing organic solutes and exogenous medications from the circulation. We evaluated diurnal, prandial, and long-term biological variation of 4 candidate endogenous markers of proximal tubular secretion.

METHODS

We used LC-MS to measure plasma and urine concentrations of hippurate (HA), cinnamoylglycine (CMG), indoxyl sulfate (IS), and p-cresol sulfate (PCS) in 25 healthy adults. We measured plasma concentrations of secreted solutes at 13 time points over a 24-h period, and again after 2 weeks and 14 weeks of follow-up. We further measured 24-h renal clearances of secreted solutes at baseline, 2 weeks, and 14 weeks.

RESULTS

Plasma concentrations of secreted solutes varied over the 24-h baseline period. Diurnal variation was greatest for HA, followed by CMG, IS, and PCS. Plasma concentrations of HA (P = 0.002) and IS (P = 0.02), but not CMG and PCS, increased significantly following meals. Long-term intraindividual biological variation (CV_I) in plasma concentrations of secreted solutes over 14 weeks varied from 21.8% for IS to 67.3% for PCS, and exceeded that for plasma creatinine (CV_I, 7.1%). Variation in 24-h renal clearances was similar among the secreted solutes [intraindividual variation (CV_A+I), 33.6%-47.3%] and was lower using pooled plasma samples from each study visit.

CONCLUSIONS

Plasma concentrations of HA, CMG, IS, and PCS fluctuate within individuals throughout the day and over weeks. Renal clearances of these secreted solutes, which serve as estimates of renal proximal tubule secretion, are also subject to intraindividual biological variation that can be improved by additional plasma measurements.

Biologic Variation Approach to Daily Laboratory

Biological variation gives valuable information about how the living organism regulates its constituents within and between subjects; this information on the behavior of body components allows us to derive consequences concerning reference populations and intervals. With a more pragmatic approach biological variation has three uses: setting the appropriate analytical performance specification for each analyte to limit the amount of error that laboratory could introduce in its measurements, to help distinguish health from disease, and to implement internal quality control with the automatic verification of results.

Variability of biomarkers in patients with chronic heart failure and healthy controls

Aims

Biomarkers can be used for diagnosis, risk stratification, or management of patients with heart failure (HF). Knowledge about the biological variation is needed for proper interpretation of serial measurements. Therefore, we aimed to determine and compare the biological variation of a large panel of biomarkers in healthy subjects and in patients with chronic HF.

Methods and results

The biological variability of established biomarkers [NT‐proBNP and high‐sensitivity troponin T (hsTnT)], novel biomarkers [galectin‐3, suppression of tumorigenicity 2 (ST2), and growth differentiation factor 15 (GDF‐15)], and renal/neurohormonal biomarkers (aldosterone, phosphate, parathyroid hormone, plasma renin concentration, and creatinine) was determined in 28 healthy subjects and 83 HF patients, over a period of 4 months and 6 weeks, respectively. The analytical (CV_a), intraindividual (CV_i), and interindividual (CV_g) variations were calculated, as well as the reference change value (RCV), which reflects the percentage of change that may indicate a ‘relevant’ change. All crude biomarker levels were significantly increased or decreased in HF patients compared with controls (all P < 0.01). Variation indices were comparable in healthy individuals and HF patients. CV_i was not influenced by the individual levels of the biomarker itself. NT‐proBNP and GDF‐15 had relatively high CV_i (21.8% and 16.6%) and RCV (61.7% and 64.3%), whereas ST2 (CV_i, 15.0; RCV, 42.9%), hsTnT (CV_i, 11.1; RCV, 31.4%), and galectin‐3 (CV_i, 8.1; RCV, 25.0%) had lower indices of variation.

Conclusion

Biological variation indices are comparable between healthy subjects and HF patients for a broad spectrum of biomarkers. NT‐proBNP and GDF‐15 have substantial variation, with lower variation for ST2, hsTnT, and galectin‐3. These data are instrumental in proper interpretation of biomarker levels in HF patients.

Different percentages of false-positive results obtained using five methods for the calculation of reference change values based on simulated normal and ln-normal distributions of data

Background Reference change values provide objective tools to assess the significance of a change in two consecutive results for a biomarker from an individual. The reference change value calculation is based on the assumption that within-subject biological variation has random fluctuation around a homeostatic set point that follows a normal (Gaussian) distribution. This set point (or baseline in steady-state) should be estimated from a set of previous samples, but, in practice, decisions based on reference change value are often based on only two consecutive results. The original reference change value was based on standard deviations according to the assumption of normality, but was soon changed to coefficients of variation (CV) in the formula (reference change value = ± Z ċ 2^½ ċ CV). Z is being dependent on the desired probability of significance, which also defines the percentages of false-positive results. The aim of this study was to investigate false-positive results using five different published methods for calculation of reference change value. Methods The five reference change value methods were examined using normally and ln-normally distributed simulated data. Results One method performed best in approaching the theoretical false-positive percentages on normally distributed data and another method performed best on ln-normally distributed data. The commonly used reference change value method based on two results (without use of estimated set point) performed worst both on normally distributed and ln-normally distributed data. Conclusions The optimal choice of method to calculate reference change value limits requires knowledge of the distribution of data (normal or ln-normal) and, if possible, knowledge of the homeostatic set point.

Analytical performance specifications for changes in assay bias (Δbias) for data with logarithmic distributions as assessed by effects on reference change values

Background

The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CVA): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian.

Methods

The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CVA based on log-Gaussian distributions of CVI as natural logarithms. The model was tested using plasma prolactin and glucose as examples.

Results

Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions.

Conclusion

The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CVI and CVA, is generally useful.

Reference change values in concentrations of urinary and salivary biomarkers of exposure and mouth level exposure in individuals participating in an ambulatory smoking study

Background

Modified-risk tobacco products (MRTPs) are being developed that may contribute to tobacco harm reduction. To support reduced exposure or risk claims, a scientific framework needs to be developed to assess the validity of claims and monitor consumers after product launch. We calculated reference change values (RCVs) for biomarker of exposure (BoE): salivary cotinine and hydroxycotinine; and urinary total nicotine equivalents, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and creatinine. Mouth-level exposure (MLE) to nicotine and tar were also recorded in an ambulatory setting to characterise variation among smokers in their everyday environment.

Methods

This non-residential, observational study was conducted over 3.5 years across 10 sites in Germany. Smokers of the same commercial 10 mg ISO tar product were included in the study (N=1011). Urine samples, questionnaires and cigarette filters were collected every 6 months for a total of seven timepoints.

Results

Greater variability in BoEs was observed compared with confined clinical studies. Gaussian distributed data showed 2-sided values over 100%, which are uninformative for decreases. The proportion of significant changes increased slightly among switchers, probably as a result of additional variability due to the range of products used post-switching. Overall proportions of changes remained small, consistent with literature reporting that when switching to a different tar yield cigarette, smokers partially compensate by changing their smoking behaviour.

Conclusion

Variability estimates and RCVs can be useful for monitoring subjects' BoE and MLE endpoints in longitudinal smoking studies where subjects are followed in their own environment and to aid sample size calculation of studies involving these endpoints.

Biological Variation: The Effect of Different Distributions on Estimated Within-Person Variation and Reference Change Values

BACKGROUND

Good estimates of within-person biological variation, CVI, are essential for diagnosing and monitoring patients and for setting analytical performance specifications. The aim of the present study was to use computer simulations to evaluate the impact of various measurement distributions on different methods for estimating CVI and reference change value (RCV).

METHOD

Data were simulated on the basis of 3 models for distributions of the within-person effect. We evaluated 3 different methods for estimating CVI: standard ANOVA, ln-ANOVA, and CV-ANOVA, and 3 different methods for calculating RCV: classic, ln-RCV, and a nonparametric method. We estimated CVI and RCV with the different methods and compared the results with the true values.

RESULTS

The performance of the methods varied, depending on both the size of the CVI and the type of distributions. The CV-ANOVA model performed well for the estimation of CVI with all simulated data. The ln-RCV method performed best if data were ln-normal distributed or CVI was less than approximately 12%. The nonparametric RCV method performed well for all simulated data but was less precise.

CONCLUSIONS

The CV-ANOVA model is recommended for both calculation of CVI and the step-by-step approach of checking for outliers and homogeneity in replicates and samples. The standard method for calculation of RCV should not be used when using CVs.

Biological Variation of Plasma and Urinary Markers of Acute Kidney Injury in Patients with Chronic Kidney Disease

BACKGROUND

Identification of acute kidney injury (AKI) is predominantly based on changes in plasma creatinine concentration, an insensitive marker. Alternative biomarkers have been proposed. The reference change value (RCV), the point at which biomarker change can be inferred to have occurred with statistical certainty, provides an objective assessment of change in serial tests results in an individual.

METHODS

In 80 patients with chronic kidney disease, weekly measurements of blood and urinary biomarker concentrations were undertaken over 6 weeks. Variability was determined and compared before and after adjustment for urinary creatinine and across subgroups stratified by level of kidney function, proteinuria, and presence or absence of diabetes.

RESULTS

RCVs were determined for whole blood, plasma, and urinary neutrophil gelatinase-associated lipocalin (111%, 59%, and 693%, respectively), plasma cystatin C (14%), creatinine (17%), and urinary kidney injury molecule 1 (497%), tissue inhibitor of metalloproteinases 2 (454%), N-acetyl-β-d-glucosaminidase (361%), interleukin-18 (819%), albumin (430%), and α1-microglobulin (216%). Blood biomarkers exhibited lower variability than urinary biomarkers. Generally, adjusting urinary biomarker concentrations for creatinine reduced (P < 0.05) within-subject biological variability (CVI). For some markers, variation differed (P < 0.05) between subgroups.

CONCLUSIONS

These data can form a basis for application of these tests in clinical practice and research studies and are applicable across different levels of kidney function and proteinuria and in the presence or absence of diabetes. Most of the studied biomarkers have relatively high CVI (noise) but also have reported large concentration changes in response to renal insult (signal); thus progressive change should be detectable (high signal-to-noise ratio) when baseline data are available.

Performance criteria based on true and false classification and clinical outcomes. Influence of analytical performance on diagnostic outcome using a single clinical component

BACKGROUND

In the general classical model for diagnoses based on a single analytic component, distributions of healthy and diseased are compared and several investigations of varying analytical performance on the percentage of misclassifications have been published. A new concept based on an alternative type of diagnosing, based on sharp decision limits has been introduced in diagnostic guidelines, but only a few publications on investigation of analytical performance have been seen.

METHODS

The two diagnostic models (bimodal and unimodal) based on natural logarithmic Gaussian distributions are simulated.

RESULTS

In the bimodal model it is possible to evaluate the influence of prevalence of disease in combination with varying analytical performances. In the unimodal model the prevalence is pre-decided by the chosen decision limit. In this model the influence of analytical performance is investigated for diagnosing diabetes using haemoglobin A1c (HbA1c), and for patients with high and low risk for coronary heart disease defined by serum-cholesterol concentrations.

CONCLUSIONS

For HbA1c the guidelines and recommendations define a maximum inter-laboratory coefficient of variation of 3.5%, but this is in DCCT units (without a true zero-point), so after transformation to IFCC units (which are proportional) it was 5.2%, which allows for analytical bias as high as approximately ±9%. Consequently, analytical quality specifications should be separated as maximum bias and imprecision.

Short- and Long-term Biologic Variability of Galectin-3 and Other Cardiac Biomarkers in Patients with Stable Heart Failure and Healthy Adults

BACKGROUND

Galectin-3 (Gal-3) has been suggested as a prognostic biomarker in heart failure (HF) patients that may better reflect disease progression than traditional markers, including B-type natriuretic peptide (BNP) and cardiac troponins. To fully establish the utility of any biomarker in HF, its biologic variability must be characterized.

METHODS

To assess biologic variability, 59 patients were prospectively recruited, including 23 male and 16 female patients with stable HF and 10 male and 10 female healthy individuals. Gal-3, BNP, and high-sensitivity cardiac troponin I (hs-cTnI) were assayed at 5 time points within a 3-week period to assess short-term biologic variability. Long-term (3-month) biologic variability was assessed with samples collected at enrollment and after 4, 8, and 12 weeks.

RESULTS

Among healthy individuals, mean short-term biologic variability, expressed as intraindividual CV (CVI), was 4.5% for Gal-3, 29.0% for BNP, and 14.5% for hs-cTnI; long-term biologic variability was 5.5% for Gal-3, 34.7% for BNP, and 14.7% for hs-cTnI. In stable HF patients, mean short-term biologic variability was 7.1% for Gal-3, 22.5% for BNP, and 8.5% for hs-cTnI, and mean long-term biologic variability was 7.7% for Gal-3, 27.6% for BNP, and 9.6% for hs-cTnI.

CONCLUSIONS

The finding that Gal-3 has minimal intraindividual biological variability adds to its potential as a useful biomarker in HF patients.

Will sacubitril-valsartan diminish the clinical utility of B-type natriuretic peptide testing in acute cardiac care?

Since the approval of sacubitril-valsartan for the treatment of chronic heart failure with reduced ejection fraction, a commonly raised suspicion is that a wider clinical use of this new drug may diminish the clinical utility of B-type natriuretic peptide testing as sacubitril may interfere with B-type natriuretic peptide clearance. In this education paper we critically assess this hypothesis based on the pathophysiology of the natriuretic peptide system and the limited published data on the effects of neprilysin inhibition on natriuretic peptide plasma concentrations in humans. As the main clinical application of B-type natriuretic peptide testing in acute cardiac care is and will be the rapid rule-out of suspected acute heart failure there is no significant impairment to be expected for B-type natriuretic peptide testing in the acute setting. However, monitoring of chronic heart failure patients on sacubitril-valsartan treatment with B-type natriuretic peptide testing may be impaired. In contrast to N-terminal-proBNP, the current concept that the lower the B-type natriuretic peptide result in chronic heart failure patients, the better the prognosis during treatment monitoring, may no longer be true.

Long-term biological variability of galectin-3 after heart transplantation

BACKGROUND

Galectin-3 is an emerging biomarker of heart failure and of myocardial fibrosis risk. Monitoring of galectin-3 is essential during treatment with galectin-3 inhibitors. The aim of our study was to assess long-term biological variability in a specific group of unhealthy subjects.

METHODS

The biological variability of galectin-3 was measured in a group of 44 patients after heart transplantation (HTx). Six samples were taken from each patient during a 12-month period. Galectin-3 was measured with an Abbott Architect automated immunoassay.

RESULTS

Intraindividual (CVi) and interindividual (CVg) variabilities were calculated together with the reference change value (RCV), the log-normal RCV for increase (RCV+), and the log-normal RCV for decrease (RCV-). The CVi, CVg, RCV, RCV+, and RCV- were 28.2%, 35.6%, 78.6%, 116%, and -53.7%, respectively. The index of individuality was 0.79.

CONCLUSIONS

The concentrations of galectin-3 in patients followed 12 months after HTx fluctuated around the homeostatic point, with CVi of approximately 28%. RCVs of +116% (log-normal increase) and -54% (log-normal decrease) mean that the concentration of galectin-3 would need to approximately double or decrease by half to indicate a new process.

Monitoring performance of progression assessment criteria for cancer antigen 125 among patients with ovarian cancer compared by computer simulation

BACKGROUND

Cancer antigen 125 (CA125) is used to monitor tumor burden among patients with advanced serous epithelial ovarian cancer. The purpose is to compare the monitoring performance of seven previously proposed criteria.

MATERIALS & METHODS

The CA125 assessment criteria were applied to simulated datasets. We investigated the ability to provide information on CA125 increments as well as their robustness against false positive signals.

RESULTS

For baseline concentrations above cut-off, the best performing criterion was based on a confirmed increment ≥2.5-times the nadir concentration. For baseline concentrations below cut-off, the best performing criterion was based on a confirmed increment from ≤ cut-off to >two-times cut-off.

DISCUSSION

Computer simulation models may be useful for a preclinical validation of criteria to be investigated in clinical trials.

Biological variation of cardiac troponin in stable haemodialysis patients

Background

Patients with end-stage renal failure exhibit a chronic elevation of serum cardiac troponin (cTn) concentration. In order to facilitate the diagnosis of myocardial infarction in these patients, it is necessary to distinguish an increased cTn concentration due to an acute event, from that being a manifestation of chronic elevation. The aim of this study was to gather biological variation data relating to two serum cTn assays, one, a hs-cTnT assay, the other a contemporary sensitive cTnI assay, among stable haemodialysis patients. It was hoped that this might inform as to the best way to use cTn assays to assist in the diagnosis of myocardial infarction in patients with end-stage renal failure.

Methods

Eighteen stable haemodialysis patients were recruited, of whom 16 completed the study. Predialysis blood samples were collected weekly for 10 weeks during the second dialysis session of the week. Analytical CV (CVA), within-subject biological variation (CVI), between-subject biological variation (CVG), reference change value (RCV) and index of individuality (II) were determined for both assays.

Results

All samples had a serum hs-cTnT concentration above the 99th percentile for a healthy population compared to 29.4% for cTnI. For hs-cTnT, the long-term CVA was 2.1%, CVI 10.5%, CVG 64.2%, RCV 28.1% and log-normal RCV (rise/fall) 34.4%/–25.6%. The corresponding values for cTnI were 7.1, 20.2, 100.5 and 79.8%/–44.4%. The II was 0.17 and 0.2 for hs-cTnT and cTnI, respectively.

Conclusion

Long-term biological variation of cTn in stable haemodialysis patients is similar to that in healthy individuals and in patients with stable coronary arterial disease. The low II for cTnI and hs-cTnT in stable haemodialysis patients indicates that population-based decision points are of limited value. Serial measurements are required to detect significant changes in cTn concentrations and support diagnosis of myocardial infarction in these patients.

Study of FibroTest and hyaluronic acid biological variation in healthy volunteers and comparison of serum hyaluronic acid biological variation between chronic liver diseases of different etiology and fibrotic stage using confidence intervals

OBJECTIVES

Personalized ranges of liver fibrosis serum biomarkers such as FibroTest or hyaluronic acid could be used for early detection of fibrotic changes in patients with progressive chronic liver disease. Our aim was to generate reliable biological variation estimates for these two biomarkers with confidence intervals for within-subject biological variation and reference change value.

DESIGN AND METHODS

Nine fasting healthy volunteers and 66 chronic liver disease patients were included. Biological variation estimates were calculated for FibroTest in healthy volunteers, and for hyaluronic acid in healthy volunteers and chronic liver disease patients stratified by etiology and liver fibrosis stage.

RESULTS

In healthy volunteers, within-subject biological coefficient of variation (with 95% confidence intervals) and index of individuality were 20% (16%-28%) and 0.6 for FibroTest and 34% (27%-47%) and 0.79 for hyaluronic acid, respectively. Overall hyaluronic acid within-subject biological coefficient of variation was similar among non-alcoholic fatty liver disease and chronic hepatitis C with 41% (34%-52%) and 45% (39%-55%), respectively, in contrast to chronic hepatitis B with 170% (140%-215%). Hyaluronic acid within-subject biological coefficients of variation were similar between F0-F1, F2 and F3 liver fibrosis stages in non-alcoholic fatty liver disease with 34% (25%-49%), 41% (31%-59%) and 34% (23%-62%), respectively, and in chronic hepatitis C with 34% (27%-47%), 33% (26%-45%) and 38% (27%-65%), respectively. However, corresponding hyaluronic acid indexes of individuality were lower in the higher fibrosis stages.

CONCLUSION

Non-overlapping confidence intervals of biological variation estimates allowed us to detect significant differences regarding hyaluronic acid biological variation between chronic liver disease subgroups.