Biological variation of serum neopterin concentrations in apparently healthy individuals.

OBJECTIVES: The aims of this study were to determine the biological variation (BV), reference change value (RCV), index of individuality (II), and quality specifications for serum neopterin concentrations; a measurand provided by clinical laboratories as an indicator of cellular immunity. METHODS: The study delivered serum samples collected for 10 consecutive weeks from 12 apparently healthy individuals (3 male, 9 female). Serum neopterin concentrations were measured using high-performance liquid chromatography with fluorometric detection. The data analysis was performed using an online statistical tool and addressed published criteria for estimation of biological variation. RESULTS: The mean neopterin concentration was 5.26 nmol/L. The within-subject biological variation (CVI) with 95 % confidence interval (CI) of neopterin serum concentrations was 11.54 % (9.98-13.59), and the between-subject biological variation (CVG) with 95 % CI was 43.27 % (30.52-73.67). The neopterin asymmetrical RCV was -24.9 %/+33.1 %, and the II was 0.27. The desirable quality specifications for neopterin were <5.77 % for precision, <11.20 % for bias, and <20.72 % for total allowable error (TEa). When analytical variation was used instead of CVI to calculate TEa, the desirable TEa was <18.39. CONCLUSIONS: This study determined BV data for neopterin, an indicator of cell-mediated immune response. Asymmetric RCV values, of 24.9 % decrease or a 33.1 % increase between consecutive measurements indicate significant change. The II of 0.27 indicates a high degree of individuality, therefore that it is appropriate to consider the use of personal reference data and significance of change rather than the reference interval as points of reference for the evaluation of neopterin serum concentrations.

Personalized reference intervals: from theory to practice.

Using laboratory test results for diagnosis and monitoring requires a reliable reference to which the results can be compared. Currently, most reference data is derived from the population, and patients in this context are considered members of a population group rather than individuals. However, such reference data has limitations when used as the reference for an individual. A patient's test results preferably should be compared with their own, individualized reference intervals (RI), i.e. a personalized RI (prRI).The prRI is based on the homeostatic model and can be calculated using an individual's previous test results obtained in a steady-state situation and estimates of analytical (CVA) and biological variation (BV). BV used to calculate the prRI can be obtained from the population (within-subject biological variation, CVI) or an individual's own data (within-person biological variation, CVP). Statistically, the prediction interval provides a useful tool to calculate the interval (i.e. prRI) for future observation based on previous measurements. With the development of information technology, the data of millions of patients is stored and processed in medical laboratories, allowing the implementation of personalized laboratory medicine. PrRI for each individual should be made available as part of the laboratory information system and should be continually updated as new test results become available.In this review, we summarize the limitations of population-based RI for the diagnosis and monitoring of disease, provide an outline of the prRI concept and different approaches to its determination, including statistical considerations for deriving prRI, and discuss aspects which must be further investigated prior to implementation of prRI in clinical practice.

The intra-individual variation of cardiac troponin I: the effects of sex, age, climatic season, and time between samples.

OBJECTIVES: Knowing the intra-individual variation (CVi), also termed within subject biological variation, of an analyte is essential to properly interpret apparent changes in concentration. While there have been many studies assessing the CVi of cardiac troponin (cTnI), they have been limited in looking at CVi in different settings, and there is no data available on whether CVi might change in different settings. METHODS: We used our large cTnI data bank to look at the CVi of cTnI in Emergency Department (ED) patients who had an acute myocardial infarction event excluded. We looked at the effects of gender, age, climatic season, and time between samples to assess whether CVi changed. To assess the effect of age, after exclusion, we collected two samples from each subject for each study which were used to calculate the CVi between those identified groups. There were 139 males and 98 females aged <65 years and 109 males and 98 females aged ≥65 years. For gender and season, there were 122 males and 94 females in the summer period and 126 males and 102 females in the winter period. To assess long term variation there were 195 males and 153 females who had further admissions after more than 12 months. RESULTS: For the four variables listed, there were no significant differences in within individual variation (CVi), but there was a significant difference in between individual variation (CVg) for men and women with regard to age. The Index of Individuality (II) was <0.20 for all conditions studied. We noted that >90% of subjects had an reference change value (RCV) <9 ng/L. CONCLUSIONS: Because troponin concentration in patients without an identified cardiac condition change so little, delta changes are potentially of great value in assessing patients in the ED. Significant delta changes in troponin can occur without the 99th percentile being exceeded.

Biological variation estimates obtained from Chinese subjects for 32 biochemical measurands in serum.

OBJECTIVES: The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) have established a program of work to make available, and to enable delivery of well characterized data describing the biological variation (BV) of clinically important measurands. Guided by the EFLM work the study presented here delivers BV estimates obtained from Chinese subjects for 32 measurands in serum. METHODS: Samples were drawn from 48 healthy volunteers (26 males, 22 females; age range, 21-45 years) for 5 consecutive weeks at Chinese laboratory. Sera were stored at -80 °C before triplicate analysis of all samples on a Cobas 8000 modular analyzer series. Outlier and homogeneity analyses were performed, followed by CV-ANOVA, to determine BV estimates with confidence intervals. RESULTS: The within-subject biological variation (CVI) estimates for 30 of the 32 measurands studied, were lower than listed on the EFLM database; the exceptions were alanine aminotransferase (ALT), lipoprotein (a) (LP(a)). Most of the between-subject biological variation (CVG) estimates were lower than the EFLM database entries. CONCLUSIONS: This study delivers BV data for a Chinese population to supplement the EFLM BV database. Population differences may have an impact on applications of BV Data.

Annual biological variation and personalized reference intervals of clinical chemistry and hematology analytes.

OBJECTIVES: A large number of people undergo annual health checkup but accurate laboratory criterion for evaluating their health status is limited. The present study determined annual biological variation (BV) and derived parameters of common laboratory analytes in order to accurately evaluate the test results of the annual healthcare population. METHODS: A total of 43 healthy individuals who had regular healthcare once a year for six consecutive years, were enrolled using physical, electrocardiogram, ultrasonography and laboratory. The annual BV data and derived parameters, such as reference change value (RCV) and index of individuality (II) were calculated and compared with weekly data. We used annual BV and homeostatic set point to calculate personalized reference intervals (RIper) which were compared with population-based reference intervals (RIpop). RESULTS: We have established the annual within-subject BV (CVI), RCV, II, RIper of 24 commonly used clinical chemistry and hematology analytes for healthy individuals. Among the 18 comparable measurands, CVI estimates of annual data for 11 measurands were significantly higher than the weekly data. Approximately 50% measurands of II were <0.6, the utility of their RIpop were limited. The distribution range of RIper for most measurands only copied small part of RIpop with reference range index for 8 measurands <0.5. CONCLUSIONS: Compared with weekly BV, for annual healthcare individuals, annual BV and related parameters can provide more accurate evaluation of laboratory results. RIper based on long-term BV data is very valuable for "personalized" diagnosis on annual health assessments.

Biological variation of cardiac myosin-binding protein C in healthy individuals.

OBJECTIVES: Cardiac myosin-binding protein C (cMyC) is a novel biomarker of myocardial injury, with a promising role in the triage and risk stratification of patients presenting with acute cardiac disease. In this study, we assess the weekly biological variation of cMyC, to examine its potential in monitoring chronic myocardial injury, and to suggest analytical quality specification for routine use of the test in clinical practice. METHODS: Thirty healthy volunteers were included. Non-fasting samples were obtained once a week for ten consecutive weeks. Samples were tested in duplicate on the Erenna® platform by EMD Millipore Corporation. Outlying measurements and subjects were identified and excluded systematically, and homogeneity of analytical and within-subject variances was achieved before calculating the biological variability (CVI and CVG), reference change values (RCV) and index of individuality (II). RESULTS: Mean age was 38 (range, 21-64) years, and 16 participants were women (53%). The biological variation, RCV and II with 95% confidence interval (CI) were: CVA (%) 19.5 (17.8-21.6), CVI (%) 17.8 (14.8-21.0), CVG (%) 66.9 (50.4-109.9), RCV (%) 106.7 (96.6-120.1)/-51.6 (-54.6 to -49.1) and II 0.42 (0.29-0.56). There was a trend for women to have lower CVG. The calculated RCVs were comparable between genders. CONCLUSIONS: cMyC exhibits acceptable RCV and low II suggesting that it could be suitable for disease monitoring, risk stratification and prognostication if measured serially. Analytical quality specifications based on biological variation are similar to those for cardiac troponin and should be achievable at clinically relevant concentrations.

Establishing biological variation for plasma D-dimer from 25 healthy individuals.

D-dimer is considered to be a reliable marker of both coagulation activation and fibrinolysis. However, data on biological variation (BV) of D-dimer is still limited, causing the use of empiric analytical performance specifications and lack of other implications related to BV. This study aimed to estimate the BV of plasma D-dimer employing a study design compliant with The Biological Variation Data Critical Appraisal Checklist. Blood samples were collected from a cohort of 25 healthy subjects (16 females, 9 males; age range, 19-61 years) from Turkey once weekly for 3 consecutive weeks. All plasma samples were analyzed in duplicate within a single run on Roche Cobas c501. The results were assessed for outliers, variance homogeneity, normal distribution, and trend, followed by nested ANOVA to determine BV and analytical variation estimates with confidence intervals (CIs). Gender stratified BV estimates were also calculated. Within-subject (CVI) and between-subject (CVG) BV estimates with 95% CIs were for D-dimer 21.2% (17.8-25.9) and 30.9% (21.3-46.2), respectively. No significant BV differences were observed between females and males. The index of individuality (II) and the reference change value (RCV) were calculated as 0.71 and 60.4%, respectively. Analytical performance specifications for desirable imprecision, bias, and total error were 10.6, 9.4, and 26.8%, respectively. This study provides well-characterized BV estimates for D-dimer, which may be helpful for setting objectively analytical performance specifications. Moreover, RCV should be preferred to decide whether a significant difference is present between serial D-dimer measurements from an individual.

Long-term biological variation estimates of 13 hematological parameters in healthy Chinese subjects.

Background The complete blood count (CBC) is a basic test routinely ordered by physicians as a part of initial diagnostic work-up on their patients. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are needed to establish analytical performance specifications. Our aim was to define the BV of CBC parameters using a rigorous protocol that is compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) provided by the European Federation of Clinical Chemistry and Laboratory Medicine. Methods Blood samples drawn from 41 healthy Chinese subjects (22 females and 19 males; 23-59 years of age) once monthly for 6 consecutive months were analyzed using an ABX Pentra 80 instrument. The instrument was precisely calibrated. All samples were analyzed in duplicate for 13 CBC parameters. The data were assessed for outliers, normality, and variance homogeneity prior to nested ANOVA. Gender-stratified within-subject (CVI) and between-subject (CVG) BV estimates were calculated. Results The number of remaining data for each subject was 442-484 after removing outliers. No significant differences existed between female/male CVI estimates. Except for leukocytes, neutrophils, and lymphocytes, the mean values of 10 parameters differed significantly between genders, rendering partitioning of CVG data between genders. No significant differences were detected between most BV estimates and recently published estimates representing a Europid population. Conclusions Most BV estimates in BIVAC-compliant studies are similar. The turnover time of blood cells and age distribution of participants should be considered in a CBC BV study. Our study will contribute to global BV estimates and future studies.

Biological variation of arginine vasopressin.

PURPOSE: There is growing interest in the measurement of plasma levels of arginine vasopressin (AVP) for the assessment of mild dehydration. However, the principles of biological variation have not been applied to the study of AVP and understanding biological variation of AVP may provide insights regarding measurement thresholds. The purpose of this investigation was to determine the biological variation of AVP in healthy euhydrated individuals to understand the potential for establishing both static and/or change thresholds of importance. METHODS: We studied 29 healthy volunteers (24 men and 5 women) while controlling for hydration and pre-analytical factors. All subjects completed between 2-8 trials where biological variation was determined using widely published methods. We determined the intraindividual, interindividual, and analytical coefficients of variation (CVI, CVG, and CVA, respectively) and subsequently the index of individuality and heterogeneity (II and IH, respectively). RESULTS: AVP did not reach the IH threshold required to be considered useful in the dynamic assessment of physiological deviations from normal. AVP levels approached the II threshold required to be considered useful in the static assessment of physiological deviations from normal. CONCLUSIONS: This analysis demonstrates that AVP assessment is unlikely to yield useful information about hydration status.

Delta Checks in the clinical laboratory.

International standards and practice guidelines recommend the use of delta check alerts for laboratory test result interpretation and quality control. The value of contemporary applications of simple univariate delta checks determined as an absolute change, percentage change, or rate of change to recognize specimen misidentification or other laboratory errors has not received much study. This review addresses these three modes of calculation, but in line with the majority of published work, most attention is focused on the identification of specimen misidentification errors. Investigation of delta check alerts are time-consuming and the yield of identified errors is usually small compared to the number of delta check alerts; however, measured analytes with low indices of individuality frequently perform better. While multivariate approaches to delta checks suggest improved usefulness over simple univariate delta check strategies, some of these are complex and not easily applied in contemporary laboratory information systems and middleware. Nevertheless, a simple application of delta checks may hold value in identifying clinically significant changes in several clinical situations: for acute kidney injury using changes in serum creatinine, for risk of osmotic demyelination syndrome using rapid acute changes in serum sodium levels, or for early triage of chest pain patients using high sensitivity troponin assays. A careful and highly selective approach to identifying delta check analytes, calculation modes, and thresholds before putting them into practice is warranted; then follow-up with careful monitoring of performance and balancing true positives, false negatives, and false positives among delta check alerts is needed.

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 (CVI) and between-subject (CVG) 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 CVI and CVG biological variations were estimated by CV-ANOVA after the data were first subjected to outlier and homogeneity analysis. The CVI (95% CI) for MMA and HCY were 7.2% (6.1-8.5) and 7.4% (6.5-8.5), respectively. The corresponding CVG 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.

Biological variation of resting measures of ventilation and gas exchange in a large healthy cohort.

PURPOSE: Resting measures of ventilation and gas exchange are impacted by a variety of physiological stressors, such as those resulting from a research intervention or an extreme environment. However, the biological variation of these parameters, an important statistical consideration for identifying a meaningful physiological change, has not been quantified. METHODS: We performed a retrospective analysis of 21 studies completed by the U.S. Army Research Institute of Environmental Medicine (USARIEM) from 1985 to present, totaling 411 healthy volunteers. First, we determined the intraindividual, interindividual, and analytic coefficients of variation (CVI, CVG, and CVA, respectively) and subsequently the index of individuality and heterogeneity (II and IH, respectively). Second, when deemed appropriate via these outcomes, we defined the accompanying static and dynamic thresholds, beyond which a significant deviation from normal is indicated. RESULTS: End-tidal partial pressure of oxygen (PETO2) and the respiratory exchange ratio (RER) approached the II threshold required to be considered useful in the static assessment of physiological deviations from normal. PETO2 and peripheral oxygen saturation (SpO2) approached the IH threshold required to be considered useful in the dynamic assessment of physiological deviations from normal. CONCLUSIONS: This analysis identifies RER and PETO2 as parameters that might be most useful when aiming to identify a meaningful ventilatory change following a research intervention or stressor. Alternatively, other parameters of ventilation and gas exchange, such as PETCO2 and VE, may be less useful for observing an anticipated physiological change.

Biological variation of holotranscobalamin and cobalamin in healthy individuals.

Data on biological variation for cobalamin and holotranscobalamin (holoTC) are limited. The aim of this study was to determine within-subject (CVI) and between-subject (CVG) biological variations for these analytes in a healthy population. We collected blood samples from 15 healthy volunteers (12 women and three men, 22-66 years) on the same weekday for 10 consecutive weeks. Serum samples were stored at -80 °C until analysis in duplicate in a single analytical run. The CVI and CVG were estimated by nested ANOVA. The CVI (95% CI) for cobalamin and holoTC was 6.7% (5.7-7.7) and 13.0% (11.5-15.0), respectively. The corresponding CVG was 24.1% (16.4-36.0) and 24.6% (16.3-37.7). The analytical variation (CVA) (95% CI) was 3.5% (3.2-4.0) for cobalamin and 2.4% (2.1-2.6) for holoTC. The index of individuality (II) was low (<0.6) for both cobalamin and holoTC and the reference change value (RCV) was 20.1% for cobalamin and 36.6% for holoTC. Our study describes the components of biological variation of cobalamin and holoTC in a healthy population, contributing to a better clinical interpretation of these biomarkers.

Generation of data on within-subject biological variation in laboratory medicine: An update.

In recent decades, the study of biological variation of laboratory analytes has received increased attention. The reasons for this interest are related to the potential practical applications of such knowledge. Biological variation data allow the derivation of important parameters for the interpretation and use of laboratory tests, such as the index of individuality for the evaluation of the utility of population reference intervals for the test interpretation, the estimate of significant change in a timed series of results of an individual, the number of specimens required to obtain an accurate estimate of the homeostatic set point of the analyte and analytical performance specifications that assays should fulfill for their application in the clinical setting. It is, therefore, essential to experimentally derive biological variation information in an accurate and reliable way. Currently, a dated guideline for the biological variation data production and a more recent checklist to assist in the correct preparation of publications related to biological variation studies are available. Here, we update and integrate, with examples, the available guideline for biological variation data production to help researchers to comply with the recommendations of the checklist for drafting manuscripts on biological variation. Particularly, we focus on the distribution of the data, an essential aspect to be considered for the derivation of biological variation data. Indeed, the difficulty in deriving reliable estimates of biological variation for those analytes, the measured concentrations of which are not normally distributed, is more and more evident.

Biological Variation and Reference Change Value Data for Serum Neuron-Specific Enolase in a Turkish Population.

BACKGROUND: Neuron-specific enolase (NSE) is a recognized biomarker for the assessment of cerebral injury in neurological disorders. This study aims to report a definitive assessment of the biological variation (BV) components of this biomarker, including within-subject BV (CVI), between-subject BV (CVG), index of individuality (II), and reference change value (RCV), in a cohort of Turkish participants using an experimental protocol. METHODS: Six blood specimens were collected from each of the 13 apparently healthy volunteers (seven women, six men; ranging in age from 23 to 36) on the same day, every 2 weeks for 2 months. Serum specimens were stored at -20°C until analysis. Neuron-specific enolase levels were evaluated in serum samples using an electrochemiluminescence (ECLIA) immunoassay kit with a Roche Cobas e 411 auto-analyser. ANOVA test was used to calculate the variations. RESULTS: The CVI and CVG for NSE were 21.5% and 28.8%, respectively. Analytical variation (CVA) was calculated as 10.2%. Additionally, II and RCV were calculated as 0.74 and 66% (95% confident interval, CI), respectively. CONCLUSION: As the performance index (PI) was found to be less than 2 (PI = 0.95), it is concluded that the NSE measurements have a desirable performance for analytical imprecision. Since the II was found to be less than 1 (II: 0.74), the reference values will be of little use. Thus, RCV would provide better information for deciding whether a significant change has occurred.

Decision limits and the reporting of cardiac troponin: Meeting the needs of both the cardiologist and the ED physician.

Cardiac troponin is the preferred biomarker for defining the acute coronary syndrome and acute myocardial infarction. Currently, the only decision limit formally endorsed with regard to the cardiac troponins is the 99th percentile. This is a "rule-in" criterion, intended to ensure that only persons with the acute coronary syndrome are reviewed. The 99th percentile is an arbitrary cut point and there are many problems associated with its application, including defining a truly healthy population, the difficulty of standardisation of cardiac troponin assays, especially but not only cardiac troponin I, and the effects of age and sex on this parameter. The Emergency Department (ED) screens many more persons for possible acute coronary syndromes than actually have the condition and their needs are best met by a "rule-out" test that enables them to clear their busy departments of the many persons who do not actually have the condition. The needs of the ED are not optimally met using the 99th percentile. The index of individuality for the cardiac troponins is small and significant changes consistent with an acute coronary syndrome can occur without the 99th percentile being exceeded. It appears that the ED may be better served by use of delta troponin changes rather than the 99th percentile, but there are problems with this approach, particularly in persons who present late when troponin release has plateaued. In addition, there are many non-acute coronary syndrome causes for cardiac troponin release. The needs of the cardiologist and the ED physician are so different that it may be inappropriate for both groups to use the same diagnostic criteria for cardiac troponin, and it is of great importance that cardiac troponin measurement be used as only one part of the assessment of the person presenting with possible acute coronary syndrome.

Biological variation of PIVKA-II in blood serum of healthy subjects measured by automated electrochemiluminescent assay.

Background: Prothrombin/Protein Induced by Vitamin K Absence-II (PIVKA-II) is a candidate biomarker of hepatocellular cancer, recommended both for diagnostics and monitoring. The aim was to evaluate biological variation (BV) of serum PIVKA-II. Methods: Within-subject (CVI) and between-subject (CVG) BV estimates were assessed in 14 healthy volunteers in a 6-week protocol. Serum concentrations of PIVKA-II were measured by a Roche Elecsys PIVKA-II diagnostic kit (cobas e8000). Precision (CVA) was assessed from duplicate measurements of all volunteers' samples. Two methods were used for the estimation of CVI: SD-ANOVA and CV-ANOVA method. We calculated the index of individuality (II) and reference change value. The experiment was fully compliant with EFLM database checklist. Results: The CVI of PIVKA-II in healthy persons, as calculated by two statistical methods, were 8.2% (SD-ANOVA with CVA of 3.2%) and 9.4% (CV-ANOVA) with CVA of 2.7%). The CVG was 19.5% (SD-ANOVA), and respective II and RCV were 0.42 and 24.4%. Conclusions: CVI and CVG of PIVKA-II were 8.2% and 19.5%, respectively, with CVA below 4%. The low II and RCV below 25% enable the use of this biomarker both for diagnostics and monitoring. More data are needed before the introduction of PIVKA-II into clinical practice.

Biological variations of some analytes in renal posttransplant patients: a different way to assess routine parameters.

BACKGROUND: Biological variation (BV) data of analytes have been used to evaluate the significant changes in serial results (reference change value, RCV) of healthy individuals in clinical laboratories. However, BV data of healthy subjects may not be identical to the analytes of patients with ongoing clinical condition. The aim of this study was to calculate intra-(CVw) (coefficient of variation for intra-individual BV) and inter-individual (CVg) BV, index of individuality, and RCV of nine serum analytes of renal posttransplant patients. METHODS: Six serum specimens were obtained in an interval of two months in a one-year period from 70 transplant patients who had been stable for three years. Each time creatinine, uric acid, urea, sodium, potassium, calcium, inorganic phosphate, total protein, and albumin of these patients were analyzed with an integrated clinical chemistry/immunoassay auto-analyzer. ANOVA tests were used to calculate the variations. Results were compared with the data of healthy subjects obtained from BV database. RESULTS: CVw of all nine analytes of the renal transplant patients were higher than the healthy subjects. RCVs of these analytes were calculated as 14.5% for creatinine, 16.5% for urea, 13.7% for urate, 12.57% for albumin, 8.26% for total protein, 3.25% for sodium, 12.81% for potassium, 5.88% for calcium, and 21.57% for inorganic phosphate. CONCLUSION: RCV concept for predicting the clinical status in posttransplant population represents an optimization of laboratory reporting and could be a valuable tool for clinical decision.