Biologic Variation Approach to Daily Laboratory

Reference change value of global longitudinal strain in clinical practice: A test-rest quality implementation project

BACKGROUND

Reference change value (RCV) is used to assess the significance of the difference between two measurements after accounting for pre-analytic, analytic, and within-subject variability. The objective of the current study was to define the RCV for global longitudinal strain (GLS) using different semi-automated software in standard clinical practice.

METHODS

Using a test-retest study design, we quantified the median coefficient of variation (CV) for GLS using AutoStrain and Automated Cardiac Motion Quantification (aCMQ) by Philips. Triplane left-ventricular ejection fraction (LVEF) was measured for comparison. Multivariable regression analysis was performed to determine factors influencing test-retest CV including image quality and the presence of segmental wall motion abnormalities (WMA). RCV was reported using a standard formula assuming two standard deviations for repeated measurements; results were also translated into Bayesian probability. Total measurement variation was described in terms of its three different components: pre-analytic (acquisition), analytic (measuring variation), and within-subject (biological) variation.

RESULT

Of the 44 individuals who were screened, 41 had adequate quality for strain quantification. The mean age of the cohort was 56.4 ± 16.8 years, 41% female, LVEF was 55.8 ± 9.8% and the median and interquartile range for LV GLS was -17.2 [-19.3 to -14.8]%. Autostrain was more time efficient (80% less analysis time) and had a lower total median CV than aCMQ (CV = 7.4% vs. 17.6%, p < .001). The total CV was higher in patients with WMA (6.4% vs. 13.2%, p = .035). In non-segmental disease, the CV translates to a RCV of 15% (corresponding to a probability of real change of 80%). Assuming a within-subject variability of 4.0%, the component analysis identified that inter-reader variability accounts for 3.7% of the CV, while acquisition variability accounts for 4.0%.

CONCLUSION

Using test-retest analysis and CVs, we find that an RCV of 15% for GLS represents an optimistic estimate in routine clinical practice. Based on our results, a higher RCV of 17%-21% is needed in order to provide a high probability of clinically meaningful change in GLS in all comers. The methodology presented here for determining measurement reproducibility and RCVs is easily translatable into clinical practice for any imaging parameter.

Practical application of European biological variation combined with Westgard Sigma Rules in internal quality control

OBJECTIVES

Westgard Sigma Rules is a statistical tool available for quality control. Biological variation (BV) can be used to set analytical performance specifications (APS). The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) regularly updates BV data. However, few studies have used robust BV data to determine quality goals and design a quality control strategy for tumor markers. The aim of this study was to derive APS for tumor markers from EFLM BV data and apply Westgard Sigma Rules to establish internal quality control (IQC) rules.

METHODS

Precision was calculated from IQC data, and bias was obtained from the relative deviation of the External quality assurance scheme (EQAS) group mean values and laboratory-measured values. Total allowable error (TEa) was derived using EFLM BV data. After calculating sigma metrics, the IQC strategy for each tumor marker was determined according to Westgard Sigma Rules.

RESULTS

Sigma metrics achieved for each analyte varied with the level of TEa. Most of these tumor markers except neuron-specific enolase reached 3σ or better based on TEa_min. With TEa_des and TEa_opt set as the quality goals, almost all analytes had sigma values below 3. Set TEa_min as quality goal, each analyte matched IQC muti rules and numbers of control measurements according to sigma values.

CONCLUSIONS

Quality goals from the EFLM BV database and Westgard Sigma Rules can be used to develop IQC strategy for tumor markers.

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 (CV_I) 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 (CV_G) 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.

Reference change value and measurement uncertainty in the evaluation of tumor markers

The use of measurement uncertainty among clinical laboratories becomes widespread. Measurement uncertainty can be reported with the result, as well as be used in certain reference change value (RCV) calculation equations. RCV is especially recommended for use in tests with a low individuality index. In our study, we calculated the measurement uncertainty of AFP, CA 125, CA 15-3, CA 19-9, CEA tumor markers with the ISO TS 20914:2019. We compared results with limits. Two Beckman Coulter DXI-800 (Minnesota, USA) autoanalysers' results were used. We calculated the RCV values using the classical Fraser method, logarithmic Lund Method, and Clinical Laboratory Standards Institute (CLSI) method as Minimal Difference (MD). We found the same permissible measurement uncertainty limit as 15.97% for all five tumor markers. The highest RCV value was found as 90% upstream for AFP test with Lund logarithmic approach, the lowest RCV value was found as 12% for CEA with MD, all other RCV results were between these two values. We do not recommend the use of MD, as values for Biological variation are not used in the MD approach. We also recommend using the logarithmic approach, although it gives higher results. There are also clinical studies on the significance of tumor markers in a follow-up that show different results. These differences may be because the studies are conducted with different systems. Therefore, each laboratory needs to calculate its own RCV values. We also recommend informing the clinicians about the tests with high measurement uncertainty.

An Improved Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Data Analysis Pipeline for the Identification of Carbapenemase-Producing Klebsiella pneumoniae

The increasing emergence of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates is a global health alarm. Rapid methods that require minimum sample preparation and rapid data analysis are urgently required. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been used by clinical laboratories for identification of antibiotic-resistant bacteria; however, discrepancies have arisen regarding biological and technical issues. The aim of this study was to standardize an operating procedure and data analysis for identification of CPK by MALDI-TOF MS. To evaluate this approach, a series of 162 K. pneumoniae isolates (112 CPK and 50 non-CPK) were processed in the MALDI BioTyper system (Bruker Daltonik, Germany) following a standard operating procedure. The study was conducted in two stages; the first is denominated the "reproducibility stage" and the second "CPK identification." The first stage was designed to evaluate the biological and technical variation associated with the entire analysis of CPK and the second stage to assess the final accuracy of MALDI-TOF MS for the identification of CPK. Therefore, we present an improved MALDI-TOF MS data analysis pipeline using neural network analysis implemented in Clover MS Data Analysis Software (Clover Biosoft, Spain) that is designed to reduce variability, guarantee interlaboratory reproducibility, and maximize the information selected from the bacterial proteome. Using the random forest (RF) algorithm, 100% of CPK isolates were correctly identified when all the peaks in the spectra were selected as input features and total ion current (TIC) normalization was applied. Thus, we have demonstrated that real-time direct tracking of CPK is possible using MALDI-TOF MS.

Identification of Protein Carbonyls (PCOs) in Canine Serum by Western Blot Technique and Preliminary Evaluation of PCO Concentration in Dogs With Systemic Inflammation

In people, serum Protein Carbonyls (PCOs) increase during oxidative stress (OS) due to oxidative damage to proteins. OS is often associated with inflammation and especially with sepsis, a condition hard to diagnose in veterinary medicine because reliable markers are lacking. The aim of this study was to assess whether PCOs in canine serum may be detected by antibody-based methods such as Western Blotting (WB), and to preliminarily investigate the possible utility of this marker in dogs with inflammation. A serum sample oxidized in vitro was used to set up the method; the coefficient of variation obtained by repeated analysis varied from 24 to 36%. In order to assess whether the technique may cover the range of PCOs concentration detectable in routine practice, PCOs were measured in 4 healthy dogs and in 15 with inflammatory diseases, in some cases potentially associated with sepsis, as suggested by the results of other inflammatory markers such as C-Reactive Protein (CRP) and the anti-oxidant enzyme Paraoxonase 1 (PON-1): the concentration of PCOs was low in dogs with normal PON-1 activity, moderately increased in the majority of dogs with low-normal PON-1 activity, and severely increased in dogs with very low PON-1 activity. In conclusion this study demonstrates that PCOs, may be detected in canine serum, using antibody-based techniques such as WB. The preliminary results in dogs with and without systemic inflammation encourage further studies on the possible role of PCOs as inflammatory markers.

Current and emerging concepts in biological and analytical variation applied in clinical practice

A single laboratory result actually represents a range of possible values, and a given laboratory result is impacted not just by the presence or absence of disease, but also by biological variation of the measurand in question and analytical variation of the equipment used to make the measurement. Biological variation refers to variability in measurand concentration or activity around a homeostatic set point. Knowledge of biological and analytical variation can be used to facilitate interpretation of patient clinicopathologic data and is particularly useful for interpreting serial patient data and data at or near reference limits or clinical decision thresholds. Understanding how biological and analytical variation impact laboratory results is of increasing importance, because veterinarians evaluate serial data from individual patients, interpret data from multiple testing sites, and use expert consensus guidelines that include decision thresholds for clinicopathologic data interpretation. The purpose of our report is to review current and emerging concepts in biological and analytical variation and discuss how biological and analytical variation data can be used to facilitate clinicopathologic data interpretation. Inclusion of veterinary clinical pathologists having expertise in laboratory quality management and biological variation on research teams and veterinary practice guideline development teams is recommended, to ensure that various considerations for clinicopathologic data interpretation are addressed.

Red Blood Cells and Platelets Conventional and Research Parameters: Stability Remarks Before Their Interpretation

OBJECTIVES

To analyze the stability of red blood cells, platelets, and reticulocytes of the research parameters, in combination with the respective conventional parameters, for each analyte; and to quantify the morphological changes in these analytes, to propose a correction factor for each.

METHODS

Ethylenediaminetetraacetic acid (EDTA) blood specimens from patients were reanalyzed in 2-hour intervals and then, the mean percentage (X¯t%) changes were calculated. To evaluate the stability of the analyzed material, we used different criteria according to within-run and between-batch analytical variation, as well as intraindividual biological variation. Next, the mean deviation percentage of the parameters that undergo time-dependent significant changes was calculated, to obtain a correction factor.

RESULTS

Several conventional and research parameters showed significant alterations in the stability at an early time after arrival at the laboratory.

CONCLUSION

Cell variations over time can be quantified and corrected by applying a multiplying factor to the signal obtained in the analyzer.

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

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

Study of the analytical performance at different concentrations of hematological parameters using Spanish EQAS data

Background External quality assessment programs are one of the currently available tools to evaluate the analytical performance of clinical laboratories, where the measurement error (ME) obtained can be compared with quality specifications to evaluate possible deviations. The objective of this work was to analyze the ME behavior over the analytical range to assess the need to establish concentration-dependent specifications. Methods A total of 389,000 results from 585 laboratories and 2628 analyzers were collected from the Spanish external quality assessment schemes (EQAS) in hematology during the years 2015-2016. The parameters evaluated included white blood cells, red blood cells, hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, platelets, prothrombin time, activated partial thromboplastin time, neutrophils, lymphocytes, monocytes, eosinophils, basophils, reticulocytes, hemoglobin A2, antithrombin, factor VIII, protein C and von Willebrand factor. The 90th percentile of ME was calculated for every concentration evaluated of each parameter. Results We found a significant variation in the analytical performance of leukocytes, platelets, neutrophils, lymphocytes, monocytes, eosinophils, basophils, prothrombin time, reticulocytes, hemoglobin A2, antithrombin and protein C. Furthermore, this ME variation may not allow complying with the same biological variability requirements within the whole analytical range studied. Conclusions Our work shows the importance of implementing concentration-dependent specifications which can help laboratories to use proper criteria for quality specifications selection and for a better external quality control results evaluation.

Multi-site performance evaluation and Sigma metrics of 20 assays on the Atellica chemistry and immunoassay analyzers

Background

The Atellica Solution comprises chemistry (CH) and immunoassay (IM) analyzers. Recently, six early adopter clinical laboratories across Europe evaluated the analytical performance of 20 CH and IM assays. To measure analytical performance quality, Sigma metrics were calculated for individual-site and pooled-site results.

Methods

Precision, detection capability, linearity, and method comparison studies were performed according to Clinical Laboratory Standards Institute protocols. Global Sigma metrics across sites were calculated from pooled data at the medical decision level using total allowable error (TEa) goals from CLIA for CH assays, and TEa goals from RiliBÄK for IM assays; and, the equation:

Sigma metrics=%TEa–%bias/%CV.

A pooled %CV was calculated by combining the imprecision obtained from individual sites. Bias calculations were performed against the ADVIA Chemistry system or ADVIA Centaur system using Deming regression analysis (Passing-Bablok regression for electrolytes) on the pooled-site data. The 103 individual-site Sigma metric calculations used individual-site imprecision and pooled-bias.

Results

The limits of blank and detection results agreed with the manufacturer’s claims. Most assays were linear across the assay range tested. Pooled Sigma metrics were good or better (>4 Sigma) for 18 of 20 assays; and, acceptable for urea nitrogen (3.1) and sodium (3.9), the latter values attributable to higher imprecision at one of five sites.

Conclusions

Sigma metrics for data generated across multiple real-world sites evaluating the Atellica Solution demonstrated good or better performance of greater than 4 Sigma for 18 of 20 assays tested. Overall, results verified the manufacturer’s claims that methods were fit for use in clinical laboratories.

Biological variation data for lipid cardiovascular risk assessment biomarkers. A systematic review applying the biological variation data critical appraisal checklist (BIVAC)

BACKGROUND

Biological variation (BV) data can be used to set analytical performance specifications (APS) for lipid assays. Poor performance will impact upon the efficacy of international guidelines for cardiovascular risk assessment (CVR) and relevant clinical decision limits. This systematic review applies the Biological Variation Data Critical Appraisal Checklist (BIVAC) to published studies of BV of CVR biomarkers enabling metanalysis of the data.

METHODS

Studies of BV of total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides and apolipoproteins A₁ and B, retrieved using a systematic literature search, were evaluated and graded using the BIVAC. Meta-analysis of CV_I and CV_G estimates were performed utilizing weightings based upon BIVAC grades and the width of the data confidence intervals.

RESULTS

Applying the BIVAC, ten publications were graded as D, 43 as C, 5 as B and 1 as A (fully compliant). A total of 196 CV_I and 87 CV_G estimates were available for the different lipid measurands. The meta-analysis-derived BV data estimates were generally concordant with those in the online 2014 BV database.

CONCLUSIONS

Application of BIVAC identifies BV data suitable for many important applications including setting APS. Additionally, this review identifies a need for new BIVAC compliant studies to deliver BV reference data in different subpopulations.

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

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

Standardization in laboratory medicine: Two years' experience from category 1 EQA programs in Spain

Introduction

Standardization is the ability to obtain interchangeable results leading to same medical interpretation. External quality assessment (EQA) is the main support of the on-going harmonization initiatives. Aim of study was to evaluate results obtained from two years category 1 EQA program experience in Spain and determine the impact of applying this type of EQA program on the analytical standardization.

Materials and methods

According to the analytical method, traceability and instrument different groups were established which results were evaluated by calculating mean, coefficient of variation and percent of deviation to the reference value. Analytical performance specifications used to the results' evaluation were derived from biological variation for bias and from the inter-laboratory coefficients of variation found in a previous pilot study.

Results

Only creatinine measured by enzymatic methods gave excellent results, although few laboratories used this method. Creatine kinase and GGT gave good precision and bias in all, but one instrument studied. For the remaining analytes (ALT, ALP, AST, bilirubin, calcium, chloride, glucose, magnesium, potassium, sodium, total protein and urate) some improvement is still necessary to achieve satisfactory standardization in our setting.

Conclusions

The two years of category 1 EQA program experience in Spain have manifested a lack of standardization of 17 most frequent biochemistry tests used in our laboratories. The impact of the information obtained on the lack of standardization is to recommend abandoning methods such as ALT, AST without exogenous pyridoxal phosphate, Jaffe method for creatinine, and do not use non-commutable calibrators, such as aqueous solutions for calcium and sodium.