Reference Intervals Revisited: A Novel Model for Population-Based Reference Intervals, Using a Small Sample Size and Biological Variation Data.

BACKGROUND: Conventional population-based reference intervals (popRIs) are established on the ranking of single measurement results from at least 120 reference individuals. In this study, we aimed to explore a new model for popRIs, utilizing biological variation (BV) data to define the reference interval (RI) limits and compared BV-based popRI from different sample sizes with previously published conventional popRIs from the same population. METHODS: The model is based on defining the population set point (PSP) from single-measurement results of a group of reference individuals and using the total variation around the PSP, derived from the combination of BV and analytical variation, to define the RI limits. Using data from 143 reference individuals for 48 clinical chemistry and hematology measurands, BV-based popRIs were calculated for different sample sizes (n = 16, n = 30, and n = 120) and considered acceptable if they covered 90% of the population. In addition, simulation studies were performed to estimate the minimum number of required reference individuals. RESULTS: The median ratio of the BV-based to conventional RI ranges was 0.98. The BV-based popRIs calculated from the different samples were similar, and most met the coverage criterion. For 25 measurands ≤16 reference individuals and for 23 measurands >16 reference individuals were required to estimate the PSP. CONCLUSIONS: The BV-based popRI model delivered robust RIs for most of the included measurands. This new model requires a smaller group of reference individuals than the conventional popRI model and can be implemented if reliable BV data are available.

Personalized and Population-Based Reference Intervals for 48 Common Clinical Chemistry and Hematology Measurands: A Comparative Study.

BACKGROUND: Personalized reference intervals (prRIs) have the potential to improve individual patient follow-up as compared to population-based reference intervals (popRI). In this study, we estimated popRI and prRIs for 48 clinical chemistry and hematology measurands using samples from the same reference individuals and explored the effect of using group-based and individually based biological variation (BV) estimates to derive prRIs. METHODS: 143 individuals (median age 28 years) were included in the study and had fasting blood samples collected once. From this population, 41 randomly selected subjects had samples collected weekly for 5 weeks. PopRIs were estimated according to Clinical Laboratory Standards Institute EP28 and within-subject BV (CVI) were estimated by CV-ANOVA. Data were assessed for trends and outliers prior to calculation of individual prRIs, based on estimates of (a) within-person BV (CVP), (b) CVI derived in this study, and (c) publically available CVI estimates. RESULTS: For most measurands, the individual prRI ranges were smaller than the popRI range, but overall about half the study participants had a prRI wider than the popRI for 5 or more out of 48 measurands. The dispersion of prRIs based on CVP was wider than that of prRIs based on CVI. CONCLUSION: The prRIs derived in our study varied significantly between different individuals, especially if based on CVP. Our results highlight the limitations of popRIs in interpreting test results of individual patients. If sufficient data from a steady-state situation are available, using prRI based on CVP estimates will provide a RI most specific for an individual patient.

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.

Personalized reference intervals - statistical approaches and considerations.

For many measurands, physicians depend on population-based reference intervals (popRI), when assessing laboratory test results. The availability of personalized reference intervals (prRI) may provide a means to improve the interpretation of laboratory test results for an individual. prRI can be calculated using estimates of biological and analytical variation and previous test results obtained in a steady-state situation. In this study, we aim to outline statistical approaches and considerations required when establishing and implementing prRI in clinical practice. Data quality assessment, including analysis for outliers and trends, is required prior to using previous test results to estimate the homeostatic set point. To calculate the prRI limits, two different statistical models based on 'prediction intervals' can be applied. The first model utilizes estimates of 'within-person biological variation' which are based on an individual's own data. This model requires a minimum of five previous test results to generate the prRI. The second model is based on estimates of 'within-subject biological variation', which represents an average estimate for a population and can be found, for most measurands, in the EFLM Biological Variation Database. This model can be applied also when there are lower numbers of previous test results available. The prRI offers physicians the opportunity to improve interpretation of individuals' test results, though studies are required to demonstrate if using prRI leads to better clinical outcomes. We recommend that both popRIs and prRIs are included in laboratory reports to aid in evaluating laboratory test results in the follow-up of patients.

Within- and between-subject biological variation data for serum zinc, copper and selenium obtained from 68 apparently healthy Turkish subjects.

OBJECTIVES: Trace elements (TrEL) are nutritionally essential components in maintaining health and preventing diseases. There is a lack of reliable biological variation (BV) data for TrELs, required for the diagnosis and monitoring of TrEL disturbances. In this study, we aimed to provide updated within- and between-subject BV estimates for zinc (Zn), copper (Cu) and selenium (Se). METHODS: Weekly serum samples were drawn from 68 healthy subjects (36 females and 32 males) for 10 weeks and stored at -80 °C prior to analysis. Serum Zn, Cu and Se levels were measured using inductively-coupled plasma mass spectrometry (ICP-MS). Outlier and variance homogeneity analyses were performed followed by CV-ANOVA (Røraas method) to determine BV and analytical variation estimates with 95% CI and the associated reference change values (RCV) for all subjects, males and females. RESULTS: Significant differences in mean concentrations between males and females were observed, with absolute and relative (%) differences for Zn at 0.5 µmol/L (3.5%), Cu 2.0 µmol/L (14.1%) and Se 0.06 µmol/L (6.0%). The within-subject BV (CVI [95% CI]) estimates were 8.8% (8.2-9.3), 7.8% (7.3-8.3) and 7.7% (7.2-8.2) for Zn, Cu and Se, respectively. Within-subject biological variation (CVI) estimates derived for male and female subgroups were similar for all three TrELs. Marked individuality was observed for Cu and Se. CONCLUSIONS: The data of this study provides updated BV estimates for serum Zn, Cu and Se derived from a stringent protocol and state of the art methodologies. Furthermore, Cu and Se display marked individuality, highlighting that population based reference limits should not be used in the monitoring of patients.

Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation.

BACKGROUND: The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. METHODS: A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. RESULTS: Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. CONCLUSIONS: Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

A Simple Method for Quantification of Five Urinary Porphyrins, Porphobilinogen and 5-Aminolevulinic Acid, Using Liquid Chromatography Tandem Mass Spectrometry.

Analysis of porphyrins and 5-aminolevulinic acid (ALA), porphobilinogen (PBG) in physiological liquids is required for diagnosis and follow-up of porphyrias. High performance liquid chromatography (HPLC) and liquid chromatography tandem mass spectrometry (LC-MS) methods with higher specificity and sensitivity have been developed. The major disadvantage of those methods is that they require longer extraction times due to their matrix effects. The present study suggests a simple, fast, sensitive, and specific assay for determination of Coproporphyrin, 5-carboxylporphyrin, 6-carboxylporphyrin, 7-carboxylporphyrin, Uroporphyrin I and ALA, PBG in urine sample by direct injection without sample pre-treatment using LC-MS. For the purposes of the present study LC-MS device was set to multiple reaction monitoring (MRM) and positive ion mode. Porphyrins and ALA, porphobilinogen were characterized by their MS/MS product ion, spectra. ALA, PBG and 5 porphyrins were detected simultaneously. Limit of detection for Coproporphyrin, 5-carboxylporphyrin, 6-carboxylporphyrin, 7-carboxylporphyrin, Uroporphyrin I were 2 nmol/L, where it was 5 µmol/L for ALA and 2 µmol/L for porphobilinogen. The present study suggests that the present method is very effective compared to many other available methods for it does not require pre-treatment, provides simultaneous results of ALA, PBG and 5 porphyrins quantitatively in a shorter span of time, and has suitable sensitivity and selectivity. LC-MS technique was used clinically for the determination of urine porphyrin levels.

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

Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects.

BACKGROUND: The complete blood count (CBC) is used to evaluate health status in the contexts of various clinical situations such as anemia, infection, inflammation, trauma, malignancies, etc. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are required. The study aim was to define the BVs of CBC parameters employing a strict protocol. METHODS: Blood samples, drawn from 30 healthy subjects (17 females, 13 males) once weekly for 10 weeks, were analyzed using a Sysmex XN 3000 instrument. The data were assessed for normality, trends, outliers and variance homogeneity prior to coefficient of variation (CV)-analysis of variance (ANOVA). Sex-stratified within-subject (CVI) and between-subjects (CVG) BV estimates were determined for 21 CBC parameters. RESULTS: For leukocyte parameters, with the exception of lymphocytes and basophils, significant differences were found between female/male CVI estimates. The mean values of all erythrocyte-, reticulocyte- and platelet parameters differed significantly between the sexes, except for mean corpuscular hemoglobin concentration, mean corpuscular volume and platelet numbers. Most CVI and CVG estimates appear to be lower than those previously published. CONCLUSIONS: Our study, based on a rigorous protocol, provides updated and more stringent BV estimates for CBC parameters. Sex stratification of data is necessary when exploring the significance of changes in consecutive results and when setting analytical performance specifications.

Pregnancy-associated plasma protein-A (PAPP-A) levels in patients with severe allergic asthma are reduced by omalizumab.

BACKGROUND: Remodeling is a crucial feature of severe asthma and may be associated with activation of the allergic cascade by immunoglobulin E (IgE). Omalizumab, an anti-IgE monoclonal antibody, effectively targets the severe allergic asthma phenotype. Pregnancy-associated plasma protein-A (PAPP-A) is an insulin-like growth factor binding protein-4 (IGFBP-4) protease, increasing local insulin-like growth factor (IGF)-1 concentrations, which in turn initiating a cascade involved in the regulation of cell growth, differentiation, and proliferation in various tissues. In the present study, we evaluated the effects of omalizumab on serum PAPP-A, IGFBP-4, and IGF-1 levels in subjects with severe allergic asthma. METHODS: We studied 36 asthmatic subjects and 36 healthy controls. An ultrasensitive enzyme-linked immunosorbent assay (ELISA) kit was used to measure serum PAPP-A levels, and routine commercial ELISA kits were employed to assess serum levels of IGF-1, IGFBP-4 in control subjects and asthmatic subjects before therapy (baseline) and after six months of omalizumab therapy in patients with severe asthma. RESULTS: Compared to control subjects, serum PAPP-A and IGFB-4 levels were significantly higher in asthmatic subjects (both p values < 0.001). However, the serum IGF-I levels of asthmatic subjects were similar to those of control subjects (p > 0.05). In asthma subjects, 6-month omalizumab treatment significantly decreased the serum PAPP-A (p < 0.001), IGF-I (p = 0.031), and IGFB4 (p = 0.025) levels. CONCLUSION: PAPP-A level may be a useful biomarker for predicting airway remodeling in patients with severe asthma receiving omalizumab, and may also reflect the response to treatment.

The EuBIVAS Project: Within- and Between-Subject Biological Variation Data for Serum Creatinine Using Enzymatic and Alkaline Picrate Methods and Implications for Monitoring.

BACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined biological variation (BV) indices. EuBIVAS determined BV for serum creatinine using the enzymatic and alkaline picrate measurement methods. METHOD: In total, 91 healthy individuals (38 males, 53 females; age range, 21-69 years) were bled for 10 consecutive weeks at 6 European laboratories. An equivalent protocol was followed at each center. Sera were stored at -80 °C before analysis. Analyses for each patient were performed in duplicate within a single run on an ADVIA 2400 system (San Raffaele Hospital, Milan). The data were subjected to outlier and homogeneity analysis before performing CV-ANOVA to determine BV and analytical variation (CVA) estimates with confidence intervals (CI). RESULTS: The within-subject BV estimates [CVI (95% CI)] were similar for enzymatic [4.4% (4.2-4.7)] and alkaline picrate [4.7% (4.4-4.9)] methods and lower than the estimate presently available online (CVI = 5.9%). No significant male/female BV differences were found. Significant differences were observed in mean creatinine values between men and women and between Turkish individuals and those of other nationalities. Between-subject BV (CVG) estimates, stratified accordingly, produced CVG values similar to historical BV data. CVA was 1.1% for the enzymatic and 4.4% for alkaline picrate methods, indicating that alkaline picrate methods fail to fulfill analytical performance specifications for imprecision (CVAPS). CONCLUSIONS: The serum creatinine CVI obtained by EuBIVAS specifies a more stringent CVAPS than previously identified. The alkaline picrate method failed to meet this CVAPS, raising questions regarding its future use.

Biological Variation Estimates Obtained from 91 Healthy Study Participants for 9 Enzymes in Serum.

BACKGROUND: We sought to develop estimates of biological variation (BV) for 9 enzymes in blood serum as part of the European Biological Variation Study. METHODS: Ninety-one healthy study participants (38 male and 53 female, 21-69 years old) were phlebotomized in each of 10 consecutive weeks at 6 European laboratories. The same preanalytical sample-handling protocol was followed at each center before transport to San Raffaele Hospital, Milan, Italy, for analysis. Sera were stored at -80 °C before analysis in duplicate within a single run on an ADVIA 2400 Clinical Chemistry System (Siemens Healthcare) following a protocol designed to minimize analytical imprecision. Assay traceability was established using frozen sera with target values assigned by reference methods. The results were subjected to outlier analysis before CV-ANOVA to deliver valid BV estimates. Results for 9 enzymes were subsequently partitioned for graphical display allowing visual assessment of the effects of country of origin, sex, and age on BV estimates. RESULTS: We found no effect of country upon the observed variation, but overall sex-related differences were evident for alanine amino transferase (ALT), γ-glutamyl transferase (GGT), and creatine kinase (CK). The following estimates for within-subject BV (CVI) and between-subject BV (CVG), respectively, were obtained: ALT: 9.3%, 28.2%; aspartate aminotransferase: 9.5%, 20.3%; GGT: 8.9%, 41.7%; alkaline phosphatase : 5.3%, 24.9%; lactate dehydrogenase: 5.2%, 12.6%; CK: 14.5%, 31.5%; amylase: 6.8%, 30.4%; pancreatic α-amylase: 6.3%, 24.9%; and lipase (LIP): 7.7%, 23.8%. CONCLUSIONS: All CVI and some CVG estimates were lower than those reported in the online BV 2014 updated database. Analytical performance specifications derived from BV can be applied internationally.

Sample collections from healthy volunteers for biological variation estimates' update: a new project undertaken by the Working Group on Biological Variation established by the European Federation of Clinical Chemistry and Laboratory Medicine.

BACKGROUND: Biological variation (BV) data have many fundamental applications in laboratory medicine. At the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) the reliability and limitations of current BV data were discussed. The EFLM Working Group on Biological Variation is working to increase the quality of BV data by developing a European project to establish a biobank of samples from healthy subjects to be used to produce high quality BV data. METHODS: The project involved six European laboratories (Milan, Italy; Bergen, Norway; Madrid, Spain; Padua, Italy; Istanbul, Turkey; Assen, The Netherlands). Blood samples were collected from 97 volunteers (44 men, aged 20-60 years; 43 women, aged 20-50 years; 10 women, aged 55-69 years). Initial subject inclusion required that participants completed an enrolment questionnaire to verify their health status. The volunteers provided blood specimens once per week for 10 weeks. A short questionnaire was completed and some laboratory tests were performed at each sampling consisting of blood collected under controlled conditions to provide serum, K2EDTA-plasma and citrated-plasma samples. RESULTS: Samples from six out of the 97 enroled subjects were discarded as a consequence of abnormal laboratory measurements. A biobank of 18,000 aliquots was established consisting of 120 aliquots of serum, 40 of EDTA-plasma, and 40 of citrated-plasma from each subject. The samples were stored at -80 °C. CONCLUSIONS: A biobank of well-characterised samples collected under controlled conditions has been established delivering a European resource to enable production of contemporary BV data.

Perchlorate levels found in tap water collected from several cities in Turkey.

Perchlorate is an inorganic anion that inhibits iodide transport to the thyroid by sodium-iodide transporters. Because perchlorate is highly soluble, stable, and mobile in water, drinking water is a potential source of perchlorate exposure. When exposed to perchlorate, thyroid dysfunction can be observed in sensitive populations (pregnant woman, infants, and children), especially those with iodide deficiency. The aim of this study was to determine the perchlorate levels in tap water from five cities in Turkey. Perchlorate concentrations of 145 tap water samples collected from Ankara, Isparta, Istanbul, Kayseri, and Sakarya were determined by liquid chromatography-tandem mass spectrometry. Mean and median values were found to be 0.15 and 0.07 µg/L, respectively. The median values (25-75 % percentile) of Istanbul, Ankara, Sakarya, Isparta, and Kayseri were 0.08 µg/L (0.04-0.09 µg/L), 0.07 µg/L (0.07-0.21 µg/L), 0.04 µg/L (0.04-0.04 µg/L), 0.03 µg/L (0.02-0.07 µg/L), and 0.25 µg/L (0.23-0.31 µg/L), respectively. The median perchlorate level observed in Kayseri was significantly higher than those found at other cities (p < 0.05). Perchlorate concentrations in water samples were lower than the interim drinking water health advisory level (15 µg/L) determined by the US Environmental Protection Agency. This study showed that perchlorate in drinking water is not the main source of exposure in these cities. Future studies should be performed to determine perchlorate levels in other potential sources, such as food products.

Perchlorate Exposure Through Water and Milk in Istanbul.

Perchlorate is a chemical pollutant that inhibits iodide uptake and may possibly impair thyroid function. Our previous study found widespread perchlorate exposure in non-pregnant, non-lactating, healthy women residing in Istanbul. The aim of this study is to assess the relative amounts of perchlorate exposure attributable to consumption of municipal water, bottled water and boxed milk available in Istanbul. Only trace levels of perchlorate were found in treated municipal water (58 % detectable, mean = 0.13 µg/L, maximum = 0.75 µg/L) and bottled water (7.4 % detectable, mean = 

Post-translational modifications of transthyretin affect the triiodonine-binding potential.

Transthyretin (TTR) is a visceral protein, which facilitates the transport of thyroid hormones in blood and cerebrospinal fluid. The homotetrameric structure of TTR enables the simultaneous binding of two thyroid hormones per molecule. Each TTR subunit provides a single cysteine residue (Cys10 ), which is frequently affected by oxidative post-translational modifications. As Cys10 is part of the thyroid hormone-binding channel within the TTR molecule, PTM of Cys10 may influence the binding of thyroid hormones. Therefore, we analysed the effects of Cys10 modification with sulphonic acid, cysteine, cysteinylglycine and glutathione on binding of triiodothyronine (T3) by molecular modelling. Furthermore, we determined the PTM pattern of TTR in serum of patients with thyroid disease by immunoprecipitation and mass spectrometry to evaluate this association in vivo. The in silico assays demonstrated that oxidative PTM of TTR resulted in substantial reorganization of the intramolecular interactions and also affected the binding of T3 in a chemotype- and site-specific manner with S-glutathionylation as the most potent modulator of T3 binding. These findings were supported by the in vivo results, which indicated thyroid function-specific patterns of TTR with a substantial decrease in S-sulphonated, S-cysteinylglycinated and S-glutathionylated TTR in hypothyroid patients. In conclusion, this study provides evidence that oxidative modifications of Cys10 seem to affect binding of T3 to TTR probably because of the introduction of a sterical hindrance and induction of conformational changes. As oxidative modifications can be dynamically regulated, this may represent a sensitive mechanism to adjust thyroid hormone availability.

Association between serum pregnancy-associated plasma protein-A and bicarbonate in hemodialysis patients.

BACKGROUND: Acidosis is associated with protein-energy malnutrition, inflammation, and bone disease, and low bicarbonate levels have been implicated in higher mortality rates in chronic kidney disease. Recently, the concentration of serum pregnancy-associated plasma protein-A (PAPP-A) has become accepted as a prognostic marker in hemodialysis patients. This study determined the relationship between PAPP-A and bicarbonate levels in these patients. METHODS: The study enrolled 65 hemodialysis patients (41 males, 24 females) and 26 control subjects (11 males, 15 females). Serum PAPP-A, intact parathormone (iPTH), calcium, phosphorus (P), and bicarbonate levels were measured. Correlations between PAPP-A and bicarbonate, iPTH, calcium, and phosphorus were evaluated. RESULTS: Median PAPP-A levels were significantly higher in hemodialysis patients [15.1 (<0.03-158.8) ng/ml] than in control subjects [6.6 (<0.03-16.4) ng/ml] (P < 0.05). There were statistically significant correlations between serum PAPP-A and bicarbonate, iPTH, and P in hemodialysis patients but not in control subjects. CONCLUSION: Elevation of serum PAPP-A has been found in hemodialysis patients and its significant correlation with bicarbonate suggests that it may be a prognostic factor.

Biological Variation Estimates for Plasma Copeptin and Clinical Implications.

BACKGROUND: Plasma copeptin measurement is useful for the differential diagnoses of polyuria-polydipsia syndrome. It has also been proposed as a prognostic marker for cardiovascular diseases. However, limited information is available about the within- (CVI) and between-subject (CVG) biological variation (BV). This study presents BV estimates for copeptin in healthy individuals. METHODS: Samples were collected weekly from 41 healthy subjects over 5 weeks and analyzed using the BRAHMS Copeptin proAVP KRYPTOR assay after at least 8 h of food and fluid abstinence. Outlier detection, variance homogeneity, and trend analysis were performed followed by CV-ANOVA for BV and analytical variation (CVA) estimation with 95% confidence intervals. Reference change values (RCVs), index of individuality (II), and analytical performance specification (APS) were also calculated. RESULTS: The analysis included 178 results from 20 males and 202 values from 21 females. Copeptin concentrations were significantly higher in males than in females (mean 8.5 vs 5.2 pmol/L, P < 0.0001). CVI estimates were 18.0% (95% CI, 15.4%-21.6%) and 19.0% (95% CI, 16.4%-22.6%), for males and females, respectively; RCVs were -35% (decreasing value) and 54% (increasing value). There was marked individuality for copeptin. No result exceeded the diagnostic threshold (>21.4 pmol/L) for arginine vasopressin resistance. CONCLUSIONS: The availability of BV data allows for refined APS and associated II, and RCVs applicable as aids in the serial monitoring of patients with specific diseases such as heart failure. The BV estimates are only applicable in subjects who abstained from oral intake due to the rapid and marked effects of fluids on copeptin physiology.