The biological variation of insulin resistance markers: data from the European Biological Variation Study (EuBIVAS).

OBJECTIVES: An insulin resistant state is characteristic of patients with type 2 diabetes, polycystic ovary syndrome, and metabolic syndrome. Identification of insulin resistance (IR) is most readily achievable using formulae combining plasma insulin and glucose results. In this study, we have used data from the European Biological Variation Study (EuBIVAS) to examine the biological variability (BV) of IR using the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and the Quantitative Insulin sensitivity Check Index (QUICKI). METHODS: Ninety EuBIVAS non-diabetic subjects (52F, 38M) from five countries had fasting HOMA-IR and QUICKI calculated from plasma glucose and insulin samples collected concurrently on 10 weekly occasions. The within-subject (CVI) and between-subject (CVG) BV estimates with 95 % CIs were obtained by CV-ANOVA after analysis of trends, variance homogeneity and outlier removal. RESULTS: The CVI of HOMA-IR was 26.7 % (95 % CI 25.5-28.3), driven largely by variability in plasma insulin and the CVI for QUICKI was 4.1 % (95 % CI 3.9-4.3), reflecting this formula's logarithmic transformation of glucose and insulin values. No differences in values or BV components were observed between subgroups of men or women below and above 50 years. CONCLUSIONS: The EuBIVAS, by utilising a rigorous experimental protocol, has produced robust BV estimates for two of the most commonly used markers of insulin resistance in non-diabetic subjects. This has shown that HOMA-IR, in particular, is highly variable in the same individual which limits the value of single measurements.

Biological variation estimates of Alzheimer's disease plasma biomarkers in healthy individuals.

INTRODUCTION: Blood biomarkers have proven useful in Alzheimer's disease (AD) research. However, little is known about their biological variation (BV), which improves the interpretation of individual-level data. METHODS: We measured plasma amyloid beta (Aß42, Aß40), phosphorylated tau (p-tau181, p-tau217, p-tau231), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) in plasma samples collected weekly over 10 weeks from 20 participants aged 40 to 60 years from the European Biological Variation Study. We estimated within- (CVI ) and between-subject (CVG ) BV, analytical variation, and reference change values (RCV). RESULTS: Biomarkers presented considerable variability in CVI and CVG . Aß42/Aß40 had the lowest CVI (≈ 3%) and p-tau181 the highest (≈ 16%), while others ranged from 6% to 10%. Most RCVs ranged from 20% to 30% (decrease) and 25% to 40% (increase). DISCUSSION: BV estimates for AD plasma biomarkers can potentially refine their clinical and research interpretation. RCVs might be useful for detecting significant changes between serial measurements when monitoring early disease progression or interventions. Highlights Plasma amyloid beta (Aß42/Aß40) presents the lowest between- and within-subject biological variation, but also changes the least in Alzheimer's disease (AD) patients versus controls. Plasma phosphorylated tau variants significantly vary in their within-subject biological variation, but their substantial fold-changes in AD likely limits the impact of their variability. Plasma neurofilament light chain and glial fibrillary acidic protein demonstrate high between-subject variation, the impact of which will depend on clinical context. Reference change values can potentially be useful in monitoring early disease progression and the safety/efficacy of interventions on an individual level. Serial sampling revealed that unexpectedly high values in heathy individuals can be observed, which urges caution when interpreting AD plasma biomarkers based on a single test result.

Interpreting two TSH results from the same patient.

OBJECTIVES: When the patient's mean (setpoint) concentration of an analyte is unknown and the physician tries to judge the clinical condition from the analyte concentration in two separate specimens taken a time apart, we believe that the two values should be judged against a bivariate reference interval derived from clinically healthy and stable individuals, rather than using univariate reference limits and comparing the difference between the values against reference change values (RCVs). In this work we compared the two models, using s-TSH as an example. METHODS: We simulated two s-TSH measurement values for 100,000 euthyreot subjects, and plotted the second value against the first, along with a markup of the central 50, 60, 70, 80, 90, and 95 % of the bivariate distribution, in addition to the 2.5 and 97.5 percentile univariate reference limits and the 2.5 and 97.5 percentile RCVs. We also estimated the diagnostic accuracy of the combination of the 2.5 and 97.5 univariate percentile reference limits and the 2.5 and 97.5 percentile RCVs against the central 95 % of the bivariate distribution. RESULTS: Graphically, the combination of the 2.5 and 97.5 univariate reference limits and the 2.5 and 97.5 percentile RCVs did not accurately delineate the central 95 % of the bivariate distribution. Numerically, the sensitivity and specificity of the combination were 80.2 and 92.2 %, respectively. CONCLUSIONS: The concentrations of s-TSH measured in two samples taken at separate times from a clinically healthy and stable individual cannot be accurately interpreted using the combination of univariate reference limits and RCVs.

Biological variation of CA 15-3, CA 125 and HE 4 on lithium heparinate plasma in apparently healthy Caucasian volunteers.

OBJECTIVES: Tumor markers are well-known for being important tools in the support of diagnosis, monitoring of treatment efficacy and follow-up of cancers. CA 125, CA 15-3 and HE 4 have demonstrated potential efficacy in other clinical indications. The main objective was to evaluate the biological variation of these glycoproteins using two different immunoassays in an apparently healthy Caucasian population. METHODS: Nineteen healthy volunteers including 11 women and 8 men were sampled weekly for 5 consecutive weeks. Samples were analyzed in duplicate on Lumipulse® G600II (Fujirebio) and on the Cobas e602 (Roche Diagnostics) analyzers. After assessment of normality, exclusion of outliers and analysis of homogeneity of variance, analytical variation (CVA), within-subject biological variation (CVI) and between-subject biological variation (CVG) were determined using a nested ANOVA. RESULTS: CVA, CVI and CVG were determined on both analyzers and both genders. For CA 125, the CVA ranges from 1.0 to 3.4%, the CVI from 5.7 to 13.8% and the CVG from 32.2 to 42.9%. For CA 15-3, the CVA is between 1.1 and 3.4%, the CVI between 3.9 and 6.5% and the CVG between 43.7 and 196.9%. Lastly, HE 4 has CVA values between 1.4 and 2.4%, CVI between 5.1 and 10.5% and CVG between 7.1 and 12.6%. CONCLUSIONS: Our study provided updated data on the biological variation of CA 125, HE 4 and CA 15-3. These data allow to improve the clinical interpretation and thus the management of the patient.

Practical delta check limits for tumour markers in different clinical settings.

OBJECTIVES: Few studies have reported on delta checks for tumour markers, even though these markers are often evaluated serially. Therefore, this study aimed to establish a practical delta check limit in different clinical settings for five tumour markers: alpha-fetoprotein, cancer antigen 19-9, cancer antigen 125, carcinoembryonic antigen, and prostate-specific antigen. METHODS: Pairs of patients' results (current and previous) for five tumour markers between 2020 and 2021 were retrospectively collected from three university hospitals. The data were classified into three subgroups, namely: health check-up recipient (subgroup H), outpatient (subgroup O), and inpatient (subgroup I) clinics. The check limits of delta percent change (DPC), absolute DPC (absDPC), and reference change value (RCV) for each test were determined using the development set (the first 18 months, n=179,929) and then validated and simulated by applying the validation set (the last 6 months, n=66,332). RESULTS: The check limits of DPC and absDPC for most tests varied significantly among the subgroups. Likewise, the proportions of samples requiring further evaluation, calculated by excluding samples with both current and previous results within the reference intervals, were 0.2-2.9% (lower limit of DPC), 0.2-2.7% (upper limit of DPC), 0.3-5.6% (absDPC), and 0.8-35.3% (RCV99.9%). Furthermore, high negative predictive values >0.99 were observed in all subgroups in the in silico simulation. CONCLUSIONS: Using real-world data, we found that DPC was the most appropriate delta-check method for tumour markers. Moreover, Delta-check limits for tumour markers should be applied based on clinical settings.

The European Biological Variation Study (EuBIVAS): a summary report.

Biological variation (BV) data have many important applications in laboratory medicine. Concerns about quality of published BV data led the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference to indicate need for new studies to generate BV estimates of required quality. In response, the EFLM Working Group on BV delivered the multicenter European Biological Variation Study (EuBIVAS). This review summarises the EuBIVAS and its outcomes. Serum/plasma samples were taken from 91 ostensibly healthy individuals for 10 consecutive weeks at 6 European centres. Analysis was performed by Siemens ADVIA 2400 (clinical chemistry), Cobas Roche 8000, c702 and e801 (proteins and tumor markers/hormones respectively), ACL Top 750 (coagulation parameters), and IDS iSYS or DiaSorin Liaison (bone biomarkers). A strict preanalytical and analytical protocol was applied. To determine BV estimates with 95% CI, CV-ANOVA after analysis of outliers, homogeneity and trend analysis or a Bayesian model was applied. EuBIVAS has so far delivered BV estimates for 80 different measurands. Estimates for 10 measurands (non-HDL cholesterol, S100-ß protein, neuron-specific enolase, soluble transferrin receptor, intact fibroblast growth-factor-23, uncarboxylated-unphosphorylated matrix-Gla protein, human epididymis protein-4, free, conjugated and %free prostate-specific antigen), prior to EuBIVAS, have not been available. BV data for creatinine and troponin I were obtained using two analytical methods in each case. The EuBIVAS has delivered high-quality BV data for a wide range of measurands. The BV estimates are for many measurands lower than those previously reported, having an impact on the derived analytical performance specifications and reference change values.

Biological variation data for kidney function related parameter: serum beta trace protein, creatinine and cystatin C from 22 apparently healthy Turkish subjects.

OBJECTIVES: Biological variation is defined as the variation in analytical concentration between and within individuals, and being aware of this biological variation is important for understanding disease dynamics. The aim of our study is to calculate the within-subject (CVI) and between-subject (CVG) biological variations of serum creatinine, cystatin C and beta trace protein (BTP), as well as the reference change value (RCV) and individuality indexes (II), which are used to calculate the glomerular filtration rate while evaluating kidney damage. METHODS: Blood samples were collected from 22 healthy volunteers for 10 consecutive weeks and stored at -80 °C until the day of analysis. While the analysis for serum creatinine was performed colorimetrically with the kinetic jaffe method, the nephelometric method was employed for cystatin C and BTP measurements. All analyses were carried out in a single session for each test. RESULTS: Analytical coefficient of variation (CVA) for serum creatinine, cystatin C and beta trace protein was 5.56, 3.48 and 5.37%, respectively. CVI and CVG: for serum creatinine: 3.31, 14.50%, respectively, for cystatin C: 3.15, 12.24%, respectively, for BTP: 9.91, 14.36%, respectively. RCV and II were calculated as 17.94%, 0.23 for serum creatinine, 13.01%, 0.26 for cystatin C, 31.24%, 0.69 for BTP, respectively. CONCLUSIONS: According to the data obtained in our study, serum creatinine and cystatin C show high individuality, therefore we think that the use of RCV instead of reference ranges would be appropriate. Although II is found to be low for BTP, more studies are needed to support this finding.

Clinical relevance of biological variation of cardiac troponins.

The high-sensitivity immunoassays for cardiac troponin I (hs-cTnI) and cardiac troponin T (hs-cTnT) are recommended by all the most recent international guidelines as gold standard laboratory methods for the detection of myocardial injury and diagnosis of acute myocardial infarction (AMI). In this review article, the Authors aimed at discussing the relevant biochemical, physiological, and clinical issues related to biological variability of cTnI and cTnT. Cardiac troponins, measured with hs-cTn methods, show a better clinical profile than the other cardio-specific biomarkers (such as the natriuretic peptides, BNP and NT-proBNP). In particular, the hs-cTn methods are characterized by a low intra-individual index of variation (<0.6) and reduced analytical imprecision (about 5% CV) at the clinical cut-off value (i.e., the 99th percentile URL value). Moreover, recent studies have reported that differences between two hs-cTn measured values (RCV) >30% can be considered statistically significant. These favourable biological characteristics and analytical performance of hs-cTn methods significantly improved the accuracy in the diagnostic process of acute coronary syndromes (ACS) in patients admitted to emergence department. In addition, several studies have demonstrated the clinical usefulness of cardiovascular risk evaluation with hs-cTn methods in some groups of patients with clinical conditions at high cardiovascular risk (such as systemic hypertension, severe obesity, diabetes mellitus, renal insufficiency, and chronic obstructive pulmonary disease). However, screening programs in the general population with hs-cTn methods for cardiovascular risk stratification require further investigation to define the optimal target populations, timing of measurement, and preventive interventions.

Testing the limits: the diagnostic accuracy of reference change values.

Reference change values (RCVs) are used by the physician to judge whether a change in analyte concentration from one sample to the next may represent a clinically significant change. Published RCVs are usually given as fixed percentages of the analyte concentration in the first sample. The accuracy of published RCVs is not well known. We obtained public-use data from the US National Health and Nutrition Examination Survey (NHANES) 2001-2002 to study the distribution of changes in the concentration of eight commonly used analytes. Specimens were obtained on two occasions 7-47 days apart from 279 to 411 individuals with an analyte concentration within the reference interval in both samples. The analytes were albumin, calcium, cholesterol, phosphate, potassium, sodium, hemoglobin and thrombocytes. For each analyte, normal within-subject biological coefficient of variation from the EFLM Working Group on Biological Variation and the NHANES analytical coefficient of variation were used to calculate the 5 and 95 percentile RCVs. These RCVs were calculated as fixed percentages of the analyte concentrations in the first sample and compared to the empirical 5 and 95 percentiles. The sensitivity of the RCVs in detecting changes outside the empirical percentiles ranged from 0.35 for sodium to 0.80 for albumin. The specificity of the RCVs in detecting changes inside the empirical percentiles ranged from 0.85 for potassium to 0.97 for thrombocytes. Calculating RCVs as fixed percentages of the analyte concentration in the first sample lessened the diagnostic accuracy. RCVs given as a function of the first result would perform better.

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.

Short-term biological variation and Reference change values of urinary 8-oxo-7,8-dihydro-2'-deoxyguanosine and 8-oxo-7,8-dihydroguanosine.

AIM: The DNA and RNA oxidative damage products urinary 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-odGsn) and 8-oxo-7,8-dihydroguanosine (8-oGsn) have potential use in clinical practice. However, biological variation (BV) and reference change values (RCVs) have not been established. The aim of this study was to establish the short-term between-subject BV(CVG ), within-subject BV(CVI ), and RCVs for urinary 8-odGsn and 8-oGsn. METHODS: First-morning midstream urine specimens were collected from 20 apparently healthy subjects(ten males and ten females) on five consecutive days. 8-odGsn and 8-oGsn were measured using LC-MS/MS, while urine creatinine (U-Cr) was also measured to correct their results. A two-level nested ANOVA was used to estimate the CVI and CVG. RESULTS: The values of CVG for 8-odGsn, 8-odGsn/U-Cr, 8-oGsn, and 8-oGsn/U-Cr were 31.2%, 39.6%, 35.3%, and 28.8%, respectively, while CVI for them were 40.5%, 9.0%, 33.5%, and 12.1%, respectively. The RCVs for 8-odGsn, 8-odGsn/U-Cr, 8-oGsn, and 8-oGsn/U-Cr were 112.5%, 26.7%, 93.7%, and 36.5%, respectively. CONCLUSION: BV and RCVs were firstly established for 8-oxo-dGsn and 8-oGsn, and can be used in clinical practice.

Biological variation of biochemical analytes determined at 8-week intervals for 1 year in clinically healthy cats.

BACKGROUND: Biological variation helps determine whether population-based or subject-based reference intervals are more appropriate to assess changes in serial analytical values. Previous studies have investigated the biological variation of biochemical analytes weekly or with variable frequency over 5-14 weeks in cats, but none have considered biological variation at less frequent intervals over 1 year. OBJECTIVES: We aimed to evaluate the long-term biological variation of 19 biochemical analytes in clinically healthy cats. METHODS: A prospective, observational study in which 15 clinically healthy, client-owned cats were sampled for serum biochemical analyses every 8 weeks for 1 year. Frozen serum samples were single-batch analyzed. Restricted maximum likelihood estimation was used to determine the coefficients of variation (CV), describing variation within each cat, between cats, and the analytical variation. These CVs were used to determine the indices of individuality and reference change values (RCVs). RESULTS: Albumin, alkaline phosphatase, creatine kinase, and globulin had high indices of individuality, indicating that they are best evaluated by RCVs. Phosphorus, potassium, chloride, sodium, symmetric dimethylarginine, and total CO2 had low indices of individuality, indicating that population-based reference intervals are appropriate. Alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, calcium, cholesterol, creatinine, glucose, total bilirubin, and total protein had intermediate indices of individuality, indicating that RCVs may provide additional insight into the interpretation of analyte measurements beyond the population-based reference intervals. CONCLUSIONS: For many analytes, the biological variation detected was similar to that reported in prior studies. Clinicians should consider the biological variation of analytes to best interpret clinically relevant changes in serial analyte measurements.

Effects of specimen haemolysis on complete blood count results by Abbott Alinity hq System.

INTRODUCTION: The current study aimed to assess the interference of in vitro haemolysis on complete blood count (CBC) using Abbott Alinity hq system, and to determine which haemolysis levels affect the reliability of sample results. MATERIALS AND METHODS: Blood samples obtained from 25 volunteers in K3-EDTA tubes were divided into four aliquots. The first aliquot was not subjected to any intervention. The second, third and fourth aliquots were passed through a fine needle 2, 4 and 6 times, respectively. Complete blood count was performed by multi-angle polarized scatter separation technology and haemolysis index (HI) was assessed from the plasma samples separated by centrifugation. Five groups were formed according to the HI values. The percentage biases between the results of non-haemolysed and haemolysed groups were compared with the desirable bias limits from The European Federation of Clinical Chemistry and Laboratory Medicine database and reference change values (RCVs). RESULTS: In groups 1 to 4, the effects of haemolysis on CBC parameters were acceptable comparing to the analytical bias except for lymphocytes (7.26%-7.42%), MCH (2.59%), and MCHC (0.47%-2.81%). Results of group 5 (gross haemolysis) showed decreases in HCT(- 4.56%), RBC (- 4.07%) count and increase in lymphocyte (11.60%) count higher than the analytical performance specifications. Moreover, variations in MCH (4.65%) and MCHC (5.24%) were exceeding the RCVs. CONCLUSIONS: Gross haemolysis (haemoglobin concentration > 10 g/L) is likely to produce unreliable CBC results on non-pathological samples. Further studies including pathological specimens are needed.

Estimation of inter-laboratory reference change values from external quality assessment data.

INTRODUCTION: It is common for patients to switch between several healthcare providers. In this context, the long-term follow-up of medical conditions based on laboratory test results obtained from different laboratories is a challenge. The measurement uncertainty in an inter-laboratory context should also be considered in data mining research based on routine results from randomly selected laboratories. As a proof-of-concept study, we aimed at estimating the inter-laboratory reference change value (IL-RCV) for exemplary analytes from publicly available data on external quality assessment (EQA) and biological variation. MATERIALS AND METHODS: External quality assessment data of the Reference Institute for Bioanalytics (RfB, Bonn, Germany) for serum creatinine, calcium, aldosterone, PSA, and of whole blood HbA1c from campaigns sent out in 2019 were analysed. The median CVs of all EQA participants were calculated based on 8 samples from 4 EQA campaigns per analyte. Using intra-individual biological variation data from the EFLM database, positive and negative IL-RCV were estimated with a formula based on log transformation under the assumption that the analytes under examination have a skewed distribution. RESULTS: We estimated IL-RCVs for all exemplary analytes, ranging from 13.3% to 203% for the positive IL-RCV and - 11.8% to - 67.0% for the negative IL-RCV (serum calcium - serum aldosterone), respectively. CONCLUSION: External quality assessment data together with data on the biological variation - both freely available - allow the estimation of inter-laboratory RCVs. These differ substantially between different analytes and can help to assess the boundaries of interoperability in laboratory medicine.

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

BACKGROUND: The European Biological Variation Study (EuBIVAS) was created by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation to establish high-quality biological variation (BV) estimates for clinically important measurands. In this study, the aim was to deliver reliable BV estimates for the biointact parathyroid hormone (PTH 1-84). METHODS: Serum samples were obtained from a population of 91 healthy individuals (38 men, 43 pre-menopausal women, and 10 post-menopausal women; 21-69 years) from 5 European countries, with all samples stored at -80 °C prior to analysis. PTH 1-84 analysis was performed at the San Raffaele Hospital (Milan, Italy) on the Roche Cobas e801. All samples from each individual were analysed in duplicate within a single run. CV-ANOVA was applied, after analysis of variance homogeneity and outliers, to obtain BV estimates for PTH 1-84 with 95% CIs. RESULTS: The within-subject BV [CVI (95% CI)] estimates were significantly different between men and women [13.0% (12.1-14.2%) and 15.2% (14.3-16.3%), respectively], while the between-subject estimates [CVG (95% CI)] were similar (men: 26.8% (21.4-35.1%), pre-menopausal women: 27.8% (22.7-36.1%)], allowing for delivery of updated analytical performance specifications and reference change values. CONCLUSIONS: Updated BV estimates for serum PTH 1-84 based on the large-scale EuBIVAS may be beneficial for the diagnosis and management of parathyroid glands and bone turnover pathologies.

Reference change values based on uncertainty models.

BACKGROUND: Different reference change values approaches are widely accepted to interpret the change between two consecutive measured values from the same biological quantity in an individual. Nevertheless, we propose two uncertainty-based models to estimate reference change values which will include all possible variation sources. METHODS: The models consisted in 1) estimation of the uncertainty related to each measured value, 2) calculation of the change between these values and its uncertainty, and 3) performing a compatibility study to know if the values are of the same degree of equivalence. Also, results obtained using the proposed models and the classical approaches are shown. RESULTS: The primary uncertainty sources corresponded to the within-subject biological, followed by those related to the analytical or pre-analytical phase, and post-analytical, respectively. We observed higher reference change values when our models were applied than those obtained using the classical approaches. CONCLUSIONS: The estimation of reference change values using our models could be more realistic than the classical approaches because more identified variation sources were considered. We hope that this study will help and stimulate clinical laboratories to perform uncertainty and reference change values studies, and it allows a greater understanding of these concepts and its application in disease monitoring.

Biologic variation of symmetric dimethylarginine and creatinine in clinically healthy cats.

BACKGROUND: Biologic variation of biochemical analytes, both within individuals and between individuals, determines whether population-based reference intervals (RIs) are appropriate when interpreting if a particular change is clinically relevant for a specific individual. OBJECTIVES: We aimed to evaluate the biologic variation of symmetric dimethylarginine (SDMA) in clinically healthy cats. METHODS: A prospective, observational study was performed in which 10 clinically healthy, client-owned cats were sampled for serum biochemical analyses once weekly for 6 weeks. Serum samples were frozen, and then single batches were analyzed for SDMA, using both liquid chromatography-mass spectroscopy (LC-MS), and an enzyme multiplied immunoassay technique (EMIT), and creatinine by modified Jaffe method. Restricted maximum likelihood estimations were used to determine the coefficients of variation (CVs) describing variation within each cat, between cats, and the analytical variation. These CVs were used to determine the indices of individuality and reference change values (RCVs). RESULTS: SDMA had an intermediate index of individuality that could be evaluated by both RCV and population-based RIs. In contrast, creatinine had a high index of individuality best evaluated with RCVs. Serum SDMA concentrations evaluated with either the reference standard, LC-MS, or the clinically used EMIT yielded similar results. CONCLUSIONS: Clinicians should consider biologic variation when selecting the best method for interpreting changes in biochemical analytes. Specifically, establishing each cat's baseline serum creatinine and SDMA concentrations during health, and applying RCVs to subsequent measurements could improve the recognition of meaningful biologic changes.