Changes In Serial Results Research Articles

BIOLOGICAL VARIATIONS OF URINARY MELATONIN LEVELS IN PATIENTS WITH CHRONIC HEPATITIS B

Objective: Biological variation-(BV) data of analytes have been used to evaluate the significant changes in serial results of healthy individuals in clinical laboratories. The aim of this study was to calculate within-(CVw)-(within-individual BV) and between-individual (CVg)-BV, index of individuality,and RCV of urine Melatonin analyte in patients with Chronic Hepatitis B(CHB). 
 Material and Methods: 20-CHB patients and 20 healthy individuals as control were involved in this study. Index of individuality and reference change value were calculated from within-subject and between-subject variations. Melatonin levels in human urines was measured with commercial a kit by-ELISA.ANOVA test was used to calculate the variations. 
 Results: Melatonin were significantly higher in patients with CHB compared to healthy subjects. Also,RCV of Melatonin analyte in CHB patients was relatively higher, because of high within-subject variation,resulting in a higher RCV.
 Conclusion: RCV concept for predicting the clinical status in CHB patients represents an optimization of laboratory reporting and could be a valuable tool for clinical decision.

Clinical application of biological variation data to facilitate interpretation of canine and feline laboratory results.

Interpretation of laboratory results is based on comparison of the patient's own results against established decision thresholds or reference intervals in the context of the clinical presentation and history. Blood measurand analysis has pre-analytical, analytical and physiological sources of variation, which may complicate interpretation of results. Biological variation describes the physiological random fluctuation of blood measurands around a homeostatic set point, which varies within and between individuals. This article reviews the practical applications of biological variation in the everyday clinical setting. Examples are offered to highlight how biological variation can be used to: (1) assess the usefulness of subject-based reference intervals, (2) determine measurand homeostatic set points, (3) interpret single or serial results for diagnosis of disease and (4) evaluate changes in serial results during monitoring.

Biological Variations of Lupus Anticoagulant, Antithrombin, Protein C, Protein S, and von Willebrand Factor Assays.

The results of lupus anticoagulant (LA), antithrombin (AT), protein C (PC), and protein S (PS) testing, and the values of von Willebrand factor antigen (VWF:Ag) are important in diagnosis and therapeutic monitoring of thrombosis and hemostasis diseases. Till now, no published study has focused on the biological variations in LA testing, and only a few studies have examined the biological variations of AT, PC, PS, and VWF:Ag. With the latest fully automated instruments and improved reagents, the analytical, within-subject, and between-subject biological variations were estimated for these five coagulant parameters in a cohort of 25 apparently healthy subjects. Blood specimens were collected at 8:00 am, 12:00 pm, and 4:00 pm on days 1, 3, and 5. The analytical biological variation (CV(A)) values of all the parameters were less than 3%. The within-subject biological variation (CV(W)) and between-subject biological variation (CV(G)) values of the LA normalized ratio were 4.64 and 6.83%, respectively. No significant differences were observed in the intraday and interday biological variations of LA tests, or in AT, PC, PS, and VWF:Ag values. Additionally, the utility of the conventional population-based reference intervals of the five coagulation parameters was evaluated by the index of individuality, and data on CV(W) and CV(A) were used to calculate the reference change value to identify the significance of changes in serial results from the same individual.

Evaluation of method performance for oxidative stress biomarkers in urine and biological variations in urine of patients with type 2 diabetes mellitus and diabetic nephropathy.

BackgroundOxidative stress biomarkers such as superoxide dismutase (CuZnSOD), catalase (CAT) and malondialdehyde (MDA) play an important role in the pathogenesis or progression of numerous diseases. Data regarding the biological variation and analytical quality specifications (imprecision, bias and total error) for judging the acceptability of method performance for oxidative stress biomarkers in urine are conspicuously lacking in the literature. Such data are important in setting analytical quality specifications, assessing the utility of population reference intervals (index of individuality) and assessing the significance of changes in serial results from an individual (reference change value; RCV).Materials and methods20 patients with type 2 diabetes mellitus (T2DM), 20 patients with diabetic nephropathy (DN) and 14 healthy individuals as control were involved in this study. Timed first morning urine samples were taken from patients and healthy groups on the zero, 1st, 3rd, 5th, 7th, 15th and 30th days. Index of individuality and reference change value were calculated from within-subject and between-subject variations. Methods of oxidative stress biomarkers in human blood were adopted in human urine and markers were measured as spectrophotometrically. Also, analytical quality specifications for evaluation of the method performance were established for oxidative stress biomarkers in urine.ResultsWithin-subject variations of oxidative stress biomarkers were significantly higher in patients with DN and T2DM compared to healthy subjects. MDA showed low individuality, and within-subject variances of MDA were larger than between-subject variances in all groups. However, CAT and CuZnSOD showed strong individuality, but within-subject variances of them were smaller than between-subject variances in all groups. RCVs of all analytes in diabetic patients were relatively higher, because of high within-subject variation, resulting in a higher RCV. Also, the described methodology achieves these goals, with analytical CVs of < 3.5% for all analytes. Goals for bias and total error were 6.0-7.9% and 12.5-23.3%, respectively.ConclusionsRCVs concept for predicting the clinical status in diabetic patients represents an optimization of laboratory reporting and could be a valuable tool for clinical decision. Furthermore, for oxidative stress biomarkers’ measurements in urine, the desirable imprecision goals based on biological variation are obtainable by current methodologies.

Biological variation remains relevant

Generation of numerical estimates of the within- and between-subject components of random biological variation has been studied for over four decades. These estimates are applied to set analytical performance goals for imprecision, bias and total analytical error, examine the utility of conventional population-based reference values through investigation of individuality, and assess the significance of changes in serial results from an individual using reference change values. The number of publications still appearing on newly- and well-studied analytes shows the ongoing interest in biological variation. Moreover, the classic works continue to be well cited. New concepts appear regularly. Applications of numerical data are facilitated by the availability of a database ( www.westgard.com/biodatabase-2014-update.htm ) that is updated every two years. However, there have been criticisms over recent times regarding the validity of these data, particularly the heterogeneity of estimates of the components of variation published for a single analyte. This has led to recent publication of the methodology used to generate the database and a plea for harmonisation and standardisation of terms and symbols. A Working Group of EFLM aims to improve the performance of studies by dissemination of a check-list that will stimulate better execution and documentation. Biological variation does remain relevant.

Biological Variations of Some Analytes in Renal Posttransplant Patients: A Different Way to Assess Routine Parameters

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. 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. 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. 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.

Laboratuvar sonuçlarının değerlendirilmesinde analitlerin biyolojik varyasyon verilerinin önemi

Clinical laboratories should minimize all the sources of variations (preanalytical, analitical and biological variations) and manage them during the entire process leading to the laboratory report. Biological variation data of analytes has been widely used in for many purposes, such as evaluating the significance of changes in serial results which is known as reference change values. Conventional population based reference values do have serious intrinsic problems and thus, there is a need for revisiting practical applications of these values for getting more useful laboratory data. This paper explains the magnitude of within- and between subject biological variation of analytes and details the reference change value applications of biological variation data.

Subject‐based reference values: biological variation, individuality, and reference change values

Subject-based reference values have been largely overlooked in veterinary medicine. These values represent longitudinal data rather than the cross-sectional data represented by standard population-based reference values. As such they provide information about biological and analytical variation. Inherent random variation of analytes around a homeostatic set point is referred to as biological variation; data on biological variation are underutilized in veterinary medicine and have multiple applications that include setting analytical goals, predicting the utility of population-based reference intervals (RIs), assessing the value of partitioning reference values, and evaluating the significance of changes in serial results. To generate these data, relatively few individuals are sampled for a short period of time. Given the difficulty of obtaining specimens from large number of healthy individuals to establish a cross-sectional RI for many veterinary species, especially exotic species, use of subject-based RIs is a practical alternative approach for the veterinary diagnostician. Furthermore, for the majority of biochemical analytes and even many hemostatic variables, population-based reference values are less sensitive than subject-based reference values for detecting pathologic changes in an individual. The focus of this review is the clinical usefulness of subject-based reference values and diagnostic implications for their use. Implementation of the concepts of biological variation, individuality, and reference change value (RCV) may allow large diagnostic laboratories to offer more sensitive reference values to assess health and detect disease.

Analytical quality goals for 25‐vitamin D based on biological variation

Measurement of 25-hydroxyvitamin D, (25D) is central in the investigation of pathologies of bone and mineral ion metabolism and in determining a patient's vitamin D status. More recently much research interest has lead to investigating the role it can play in decreasing the risk of many chronic illnesses, including common cancers, autoimmune diseases, infectious diseases, and cardiovascular disease. Knowledge of the biological variation of an analyte forms an essential part of evaluating a new analyte enabling the objective assessment of the changes in serial results, the utility of reference intervals as well as establishing laboratory quality specifications. This study determined the biological variation of 25D in 20 healthy individuals that was calculated according to the familiar methods outlined by Fraser and Harris. The within-subject variation was 12.1% and the between subject variation was 40.3%. The critical difference for sequential values significant at P<0.05 was calculated as 38.4%. The within-subject variation forms a relatively small part of the reference interval shown by the low index of individuality of 0.3. Objective analytical quality goals have also been established which have shown achievable minimum performance for imprecision of ∼6%. The desirable analytical bias goal was ∼10%. This study has objectively shown that the analytical precision of current instruments is being achieved contrary to the known problems surrounding the analytical bias for 25D assays. The limitations of using reference intervals for 25D, both in diagnoses and monitoring are shown.

Biological variation in the plasma concentrations of polyunsaturated long chain fatty acids (PUFA) in older adults

Within‐ and between‐subject biological variation is often used to set analytical quality specifications and to evaluate the significance of changes in serial results. A placebo‐controlled PUFA intervention trial allowed estimation of intra‐ (CVi) and inter‐ (CVg) subject coefficients of variation of plasma concentrations of four n‐3 and six n‐6 PUFA in older adults (&gt; 60 years old) all of whom were being supplemented with lutein and zeaxanthin for macular degeneration. Fasting blood samples were collected from 40 subjects at month 0 and from 20 subjects at months 1, 2, 3, 6, and 9 (placebo group). PUFA concentrations (umol/L) were quantitated using negative ion chemical ionization GC‐MS (Mol Gen Metab 2001;73: 38) with some modification. Analytical imprecision (CVa), calculated using inter‐assay CV for three quality control samples measured in duplicate over 20 assays, ranged from 12‐20%. CVg were calculated from the baseline blood draw (n=40). CVi were calculated using data from baseline and 5 subsequent blood draws (n=20). CVg was largest for eicosapentaenoic acid (72%) and smallest for linoleic acid (22%). CVi was largest for eicosapentaenoic acid (33%) and smallest for arachidonic acid (11%). To our knowledge there is little information available about the biological variation of absolute PUFA concentrations, independent of total fatty acid composition, either in older persons or the general population.

Analytical quality goals for parathyroid hormone based on biological variation

Measurement of parathyroid hormone (PTH) is central in the investigation of pathologies of bone and mineral ion metabolism. Knowledge of the biological variation of an analyte forms an essential part of evaluating a new analyte, enabling the objective assessment of changes in serial results and the utility of reference intervals, as well as establishing laboratory quality specifications. This study determined the biological variation of PTH in 20 healthy individuals, which was calculated according to the familiar methods outlined by Fraser and Harris. The within-subject variation was 25.3% and the between-subject variation was 43.4%. The critical difference for sequential values significant at p<0.05 was calculated as 72%. The within-subject variation forms a relatively small part of the reference interval, shown by the low index of individuality of 0.58. Objective analytical quality goals have also been established, revealing achievable optimum performance for imprecision of approximately 6%. The desirable analytical bias goal was approximately 12%. This study has objectively shown that the analytical precision of current instruments is being achieved contrary to the known problems surrounding the analytical bias for PTH assays. The limitations of using reference intervals for PTH, both in diagnoses and monitoring, are shown.

Biological variation and reference change values of CA 19‐9, CEA, AFP in serum of healthy individuals

Objective. The use of tumour markers in diagnosis and monitoring is very common. Tumour marker results vary – preanalytical sources of variation, total random analytical error (CVa), and within‐subject (intraindividual) normal biological variation. There are not so many studies evaluating the biological variations and reference change values (RCV) of these parameters. The aim of our study was to assess: (i) the average inherent intra‐ and inter‐individual biological variation (CVi and CVg) for CA 19‐9, CEA, AFP in a group of healthy individuals; (ii) the significance of changes in serial results of each marker; and (iii) the index of individuality. Material and methods. The study group comprised 49 healthy volunteers ranging in age between 18 and 60 years (25 M and 24 F). Four blood samples were obtained from each subject; one at each 14‐day interval. Each sample from one individual was assayed in duplicate. CA 19‐9, CEA, AFP levels were measured by an immunoluminometric assay on a random‐access analyser (Architect i2000; Abbott Diagnostics Division). The intra‐ (CVi) and inter‐individual (CVg) biological variations were estimated from the data generated. Reference change value (RCV) was calculated. Results. The intra‐individual/inter‐individual biological variations (CVs) for CA 19‐9, CEA, AFP were 27.2/64.24 %, 30.87/37.14 % and 26.67/43.65 %, respectively. The critical differences (RCVs) of CA 19‐9, CEA, AFP were 64.71 %, 72.57 % and 62.62 %, respectively (Z = 1.65 for unidirectional changes; p<0.05). Conclusions. Intra‐individual biological variation contributes to the variation in serial results and should therefore be included in the criteria for serum tumour marker assessment.

Between-examiner reproducibility in manual differential leukocyte counting

In manual–visual differential leukocyte counts, the counting itself may be different depending on the examiner. We estimated the between-examiner (B-E) reproducibility in differential leukocyte counting. During 2 months, daily, after performing manual–visual differential leukocyte counts, two slides with blood films were retained. Next day these two blood films were re-examined by different examiners. For each type of leukocyte the B-E reproducibility was estimated from the 58 pairs of data obtained by four technicians. The B-E coefficient of variation for each type of leukocyte was: basophilocytes, 263.2%; eosinophilocytes, 68.8%; lymphocytes, 32.5%; metamyelocytes, 69.6%; monocytes, 55.0%; myelocytes, 132.5%; and neutrophilocytes, 6.6%. For each type of leukocyte the coefficient of variation is the sought estimate of the average reproducibility due to the “human factor” as a whole, without regard to any examiner in particular. Knowledge of this component of day-to-day imprecision, and its follow-up, may be used to decide corrective actions (training of the examiner, etc.) and to set critical differences to interpret the significance of changes in serial results.

Within-subject biological variation in disease: collated data and clinical consequences

Quantitative data on the components of biological variation (BV) are used for several purposes, including calculating the reference change value (RCV) required for the assessment of the significance of changes in serial results in an individual. Pathology may modify the set point in diseased patients and, more importantly, the variation around that set-point. Our aim was to collate all published BV data in situations other than health. We report the within-subject coefficient of variation (CV(I)) for 66 quantities in 34 disease states. We compared the results with the CV(I) determined in healthy individuals and examined whether the data derived in specific diseases could be useful for clinical applications. For the majority of quantities studied, CV(I) values are of the same order in disease and health: thus the use of RCV derived from healthy subjects for monitoring patients would be reasonable. However, for a small number of quantities considered to be disease specific markers, the CV(I) differed from those in health. This could mean that RCV derived from healthy CV(I) may be inappropriate for monitoring patients in certain diseases. Hence, disease-specific RCVs may be clinically useful.

Biological variation of asymmetric dimethylarginine and related arginine metabolites and analytical performance goals for their measurement in human plasma

Asymmetric dimethylarginine (ADMA) is an endogenous competitive inhibitor of nitric oxide synthase which is believed to be a cause of endothelial dysfunction and has been shown to predict the occurrence of acute coronary events. Data regarding the biological variation of arginine and its methylated derivatives are conspicuously absent from the literature. Such data are important in setting analytical quality specifications, assessing the utility of population reference intervals and assessing the significance of changes in serial results from an individual. Arginine, homoarginine, ADMA and symmetric dimethylarginine (SDMA) are measured in plasma by high performance liquid chromatography. Twelve healthy volunteers underwent weekly blood sampling for 20 weeks in order to determine the intra- and inter-individual biological variation of these analytes, from which analytical quality specifications, indices of individuality (II) and reference change values (RCV) are derived. Plasma samples from 100 healthy individuals were obtained in order to determine population reference intervals. ADMA and symmetric dimethylarginine (SDMA) exhibit low intra-individual biological variation of 7.4% and 5.8%, respectively, imposing desirable imprecision goals (CV(A)) of < or = 3.7% and 2.9% for these analytes. The described methodology achieves these goals, with analytical CVs of < 3.5% for all analytes. Goals for bias and total error were 3.1-10.1% and 7.2-16.0%, respectively. Reference intervals for ADMA and SDMA were 0.29-0.63 micromol L(-1) and 0.24-0.55 micromol L(-1), but have IIs < 1. RCVs were at least 20% for all analytes studied. Dimethylarginine concentrations are tightly controlled in health, with the result that imprecision goals for laboratory methods require to be low. Relatively large differences are required between serial results to denote a significant change. Population reference intervals for dimethylarginines are likely to be of limited value in detecting 'abnormality' in an individual from a single result.

Biological Variation of Vitamins in Blood of Healthy Individuals

Components of biological variation can be used to define objective quality specifications (imprecision, bias, and total error), to assess the usefulness of reference values [index of individuality (II)], and to evaluate significance of changes in serial results from an individual [reference change value (RCV)]. However, biological variation data on vitamins in blood are limited. The aims of the present study were to determine the intra- and interindividual biological variation of vitamins A, E, B(1), B(2), B(6), C, and K and carotenoids in plasma, whole blood, or erythrocytes from apparently healthy persons and to define quality specifications for vitamin measurements based on their biology. Fasting plasma, whole blood, and erythrocytes were collected from 14 healthy volunteers at regular weekly intervals over 22 weeks. Vitamins were measured by HPLC. From the data generated, the intra- (CV(I)) and interindividual (CV(G)) biological CVs were estimated for each vitamin. Derived quality specifications, II, and RCV were calculated from CV(I) and CV(G). CV(I) was 4.8%-38% and CV(G) was 10%-65% for the vitamins measured. The CV(I)s for vitamins A, E, B(1), and B(2) were lower (4.8%-7.6%) than for the other vitamins in blood. For all vitamins, CV(G) was higher than CV(I), with II <1.0 (range, 0.36-0.95). The RCVs for vitamins were high (15.8%-108%). Apart from vitamins A, B(1), and erythrocyte B(2), the imprecision of our methods for measurement of vitamins in blood was within the desirable goal. For most vitamin measurements in plasma, whole blood, or erythrocytes, the desirable imprecision goals based on biological variation are obtainable by current methodologies. Population reference intervals for vitamins are of limited value in demonstrating deficiency or excess.

The reference change value: a proposal to interpret laboratory reports in serial testing based on biological variation

Background: A proposal to calculate and use the reference change value (RCV) as an objective guide for interpreting the numerical results obtained in clinical laboratory serial testing is introduced in this study. Methods: A database showing the results of a compilation of 191 publications on biological variation and including information on a number of analytes provided the standardized criterion based on biology for calculating the RCVs. Results: For each of the 261 analytes included in the study, the RCV was determined using Harris's formula, replacing analytical imprecision with the desirable specification of analytical quality based on half the within‐subject biological variation at 95% probability levels. The result is a guide for a common criterion to identify clinically significant changes in serial results. Conclusions: The RCV concept is an approach that can be offered by laboratories to assess changes in serial results. The RCV data in this study are presented as a point of departure for a widely applicable objective guide to interpret changes in serial results.

Variability of post-methionine load plasma homocysteine assays

Background: Numerous variations of the methionine load test are frequently used as dynamic function tests to assess homocysteine metabolism. Lack of standardization impedes inter-laboratory comparisons. Criteria based on biological variation are suggested to standardize the methionine load test. Methods: Weekly methionine load tests ( n=5) with blood sampling at 0, 4, 6 and 8 h were performed on 15 young men. For both basal and post-methionine load homocysteine measurements, total variance ( σ S 2), within-subject variance ( σ I 2), between-subject variance ( σ G 2) and analytical variance ( σ A 2) were calculated from an appropriate analysis of variance (ANOVA). Results: Plasma homocysteine concentrations measured 6 h after methionine loading had analytical, within-subject and between-subject coefficients of variation of 5.2%, 17.5% and 9.7%, respectively. Measurements at 4 h had a higher within-subject coefficient of variation. Adjustment of post-methionine load homocysteine concentrations for basal levels resulted in considerable increases of all the measures of variation. Conclusions: Adjustment of post-methionine load plasma homocysteine concentrations for basal levels does not improve the interpretation of changes in serial results due to the higher analytical and biological variance of adjusted concentrations. It is suggested that the methionine load test is standardized to a single, unadjusted homocysteine measurement at 6 h.

Biological variation data are necessary prerequisites for objective autoverification of clinical laboratory data

The wealth of quantitative data on random biological variation has been used for setting quality specifications, assessing the utility of conventional reference values, and deciding of the significance of changes in serial laboratory results. Most analytes have marked individuality and this makes conventional population-based reference values of low utility. In consequence, reference limits are not ideal for autoverification strategies. Clinical decision limits may be better criteria for holding results for verification by laboratory professionals. Changes in serial results are significant only when the reference change value is exceeded. Such values can be generated by all laboratories and can be implemented, not only to flag reports, but also in delta checking and autoverification since these are objective rather than empirical. We have put these considerations into operation into our laboratory. Apart from special cases, our general approach is that results flagged as having changed 0.05<P<0.01, flagged as just outside the reference limits, or not flagged in any way, are autoverified and reported to the user without intervention. Only results outside pre-set clinical limits and those that have changed highly significantly P<0.01 are held for verification by clinical scientists and medical staff. This strategy allows autoverification of ca. 60% of reports.

Biological Variation: From Principles to Practice. Callum G. Fraser. Washington, DC: AACC Press, 2001, 151 pp., $38.00 ($30.00 AACC members). ISBN 1-890883-49-2.

The preface states that this book provides a simple, but comprehensive, guide on how to produce data on biologic variation, locate them in available literature, and use them in everyday laboratory practice. The book comprises six chapters: “The Nature of Biological Variation”, “Quality Specifications”, “Changes in Serial Results”, “The Utility of Population-based Reference Values”, “Other Uses of Data on Biological Variation”, and “Next Steps”. These are complemented by an index, a four-page glossary, and two supplements entitled “Data on Components of Biological Variation” and “Quality …