Simultaneous evaluation of the imprecision and inconsistency domains of GRADE can be performed using prediction intervals.

OBJECTIVES: To explore the use of prediction interval (PI) for the simultaneous evaluation of the imprecision and inconsistency domains of Grading of Recommendations, Assessment, and Evaluation using stakeholder-provided decision thresholds. STUDY DESIGN AND SETTING: We propose transforming the PI of a meta-analysis from a relative risk scale to an absolute risk difference using an appropriate baseline risk. The transformed PI is compared to stakeholder-provided thresholds on an absolute scale. We applied this approach to a large convenience sample of meta-analyses extracted from the Cochrane Database of Systematic Reviews and compared it against the traditional approach of rating imprecision and inconsistency separately using confidence intervals and statistical measures of heterogeneity, respectively. We used empirically derived thresholds following Grading of Recommendations, Assessment, and Evaluation guidance. RESULTS: The convenience sample consisted of 2516 meta-analyses (median of 7 studies per meta-analysis; interquartile range: 5-11). The main analysis showed the percentage of meta-analyses in which both approaches had the same number of certainty levels rated down was 59%. The PI approach led to more levels of rating down (lower certainty) in 27% and to fewer levels of rating down (higher certainty) in 14%. Multiple sensitivity analyses using different thresholds showed similar results, but the PI approach had particularly increased width with a larger number of included studies and higher I2 values. CONCLUSION: Using the PI for simultaneous evaluation of imprecision and inconsistency seems feasible and logical but can lead to lower certainty ratings. The PI-based approach requires further testing in future systematic reviews and guidelines using context-specific thresholds and evidence-to-decision criteria. PLAIN LANGUAGE SUMMARY: The prediction interval (PI) addresses both the imprecision and inconsistency domains of certainty. In this study, we applied this PI approach to simultaneously judge both domains and compared this to the traditional approach of making these separate judgments. The 2 approaches had moderate agreement. The PI-based approach requires further testing in future systematic reviews and guidelines using context-specific thresholds and evidence-to-decision criteria.

Beyond the basics: Sigma scores in laboratory medicine with variable total allowable errors (TEa).

BACKGROUND: To diagnose diseases, track the effectiveness of treatments and make well-informed clinical decisions, doctors rely on results from laboratories. Accurate and precise results minimize the necessity for additional testing, saving time and money while enhancing patient satisfaction.. Internal quality control and an external quality assurance scheme(EQAS) are metrics used to evaluate a clinical laboratory's performance. One of the numerous quality indicators that can be used to gauge the amount of errors is sigma metrics. To calculate the sigma scores bias%, CV%, and Total Error Allowable (TEa) are needed. Total Error allowable(TEa) is a crucial benchmark that establishes allowed limits on the degree of deviation from the target value for a certain analyte. Nevertheless, a proper consensus for establishing a TEa goal has not been reached and the impact of this limiting factor in standard laboratory practice and sigma calculation has not been sufficiently established. Choosing the right Total Error allowable(TEa) goal is one of the greatest challenges when employing sigma metrics as depending on the source, several measurands of TEa values may exhibit alteration. MATERIAL AND METHODS: Our study aims to determine the sigma scores of 20 routine chemistry parameters using six different TEa sources: Clinical Laboratory Improvement Amendment (CLIA 88'), CLIA(Clinical Laboratory Improvement Amendment) 24, BDV (Biological Variation Desirable), RCPA(Royal College of Pathologists of Australasia), RiliBak(Guideline of the German Medical Association for Quality Assurance of Laboratory Medical Examinations), and EMC/Spain(Measurement and Control Scheme) over a 12-month period using the bias percent from the External Quality Assessment Scheme (EQAS) and coefficient of variation (CV) from the Internal Quality Control (IQC). Detection system was automated, multi-channel, selective analyzer, the Beckman Coulter AU680 which works on the principle of spectrophotometry. To compute the Sigma metrics, formula used was Sigma = (TEa - Bias%) / CV%. By comparing the sigma values from the different TEa sources, TEa variance on the evaluation of the sigma metric was ascertained after which an internal quality control plan and QGI(Quality Goal Index) for underperforming parameters were devised. RESULTS: The study discovered that the sigma values of common chemical parameters varied significantly based on the TEa sources used. Maximum parameters in the above three-sigma zone were TBil, HDL, CK, ALP, amylase and uric acid in CLIA'88 while RCPA and Biological variation were determined to be the most severe, with the highest performing parameters falling below three sigma zones. Rilibaek was the most liberal, with only sodium in the lower three sigma zones along with CLIA'88. The findings indicate that there is the substantial influence of various Total Error Allowable (TEa) sources on the sigma metric evaluation. A quality control plan was devised depending on different sigma scores of the analytes using biorad unity 2.0 software(westgard sigma multirules). The origins of errors that resulted in low sigma ratings liked enhanced cleaning of electrodes, electrode replacement, ageing of reagents, instrument maintainence were pinpointed and addressed. CONCLUSION: The study highlights the necessity of harmonizing and standardizing sigma metrics, stressing the significance of choosing suitable total error allowable goals (TEa). The creation of worldwide standards and recommendations for total error allowable (TEa) can lead to its harmonization. Establishing a consensus on the acceptable levels of error for various laboratory tests would necessitate the cooperation of specialists from many nations and organizations in order to set such guidelines and standards.

Linearity assessment: deviation from linearity and residual of linear regression approaches.

In this computer simulation study, we examine four different statistical approaches of linearity assessment, including two variants of deviation from linearity (individual (IDL) and averaged (AD)), along with detection capabilities of residuals of linear regression (individual and averaged). From the results of the simulation, the following broad suggestions are provided to laboratory practitioners when performing linearity assessment. A high imprecision can challenge linearity investigations by producing a high false positive rate or low power of detection. Therefore, the imprecision of the measurement procedure should be considered when interpreting linearity assessment results. In the presence of high imprecision, the results of linearity assessment should be interpreted with caution. Different linearity assessment approaches examined in this study performed well under different analytical scenarios. For optimal outcomes, a considered and tailored study design should be implemented. With the exception of specific scenarios, both ADL and IDL methods were suboptimal for the assessment of linearity compared. When imprecision is low (3 %), averaged residual of linear regression with triplicate measurements and a non-linearity acceptance limit of 5 % produces <5 % false positive rates and a high power for detection of non-linearity of >70 % across different types and degrees of non-linearity. Detection of departures from linearity are difficult to identify in practice and enhanced methods of detection need development.

Analytical validation of the Mindray CL1200i analyzer high sensitivity cardiac troponin I assay: MERITnI study.

OBJECTIVES: This study performed an analytical validation study of the Mindray high-sensitivity cardiac troponin I (hs-cTnI) assay addressing limit of blank (LoB), limit of detection (LoD), precision, linearity, analytical specificity and sex-specific 99th percentile upper reference limits. METHODS: LoB, LoD, precision, linearity and analytical specificity were studied according to Clinical and Laboratory Standards Institute. We used one reagent lot and one CL1200i analyzer. Skeletal troponin I and T, cardiac troponin T, troponin C, actin, tropomyosin, myosin light chain, myoglobin and creatine kinase (CK-MB) were studied for cross-reactivity. Interference with biotin was examined. Lithium heparin samples (one freeze thaw cycle) from healthy males and females were measured to determine the 99th percentiles by using the non-parametric method. Analyses were performed before and after excluding subjects with clinical conditions and/or increased surrogate biomarkers. RESULTS: The Mindray hs-cTnI assay met criteria to be considered as a hs-cTn assay. LoB and LoD was <0.1 ng/L and 0.1 ng/L, respectively. Repeatability had a coefficient of variation 1.2-3.8 %, and within-laboratory imprecision 1.7-5.0 %. The measuring interval ranged from 1.1 to 28,180 ng/L. The analytical specificity was clinically acceptable for the interferents studied. After exclusions, the 99th percentile URLs obtained were 10 ng/L overall, 5 ng/L for females and 12 ng/L for males. CONCLUSIONS: Analytical observations of the Mindray hs-cTnI assay demonstrated excellent LoB, LoD, precision, linearity and analytical specificity, that were in alignment with the manufacturer's claims and regulatory guidelines for hs-cTnI. The assay is suitable for clinical investigation for patient-oriented studies.

How to verify the analytical and clinical performance of ELISA immunoanalysis in the real laboratory practice. PCSK9 as an example.

BACKGROUND: Manufacturers and diagnostic companies often recommend on-site verification of analytical performance in the clinical laboratory. The validation process used by manufacturers is rarely described in detail, and certain information on analytical performance is missing from the product sheet, especially for immunoanalytical methods. We describe an approach to the detailed validation of an ELISA method for the measurement of proprotein convertase subtilisin/kexin type 9 (PCSK9) plasma concentrations. We compared manufacturers' claims of analytical performance with data obtained in the field laboratory using several approaches. METHODS: We used the Human Proprotein Convertase 9/PCSK9 Quantikine ELISA diagnostic kit (R&D systems, Bio-Techne Ltd., Abingdon Science Park, Abingdon, UK) and three levels of quality control solution Quantikine Immunoassay Control Group 235 (R&D systems, Bio-Techne Ltd., Abingdon Science Park, Abingdon, UK) to verify precision. We measured the concentration of PCSK9 using the DS2 ELISA Reader (Dynex Technologies GmbH, Denkendorf, Germany). We used analysis of variance (ANOVA) and the R statistical package (R core team, version 1.4.5). Statistical analysis and terminology were performed according to protocol CLSI EP15-A3, and the reference interval was checked according to CLSI/IFCC C28-A3c. RESULTS: We found a significant difference between the manufacturer's claims of analytical performance and real data measured in the routine clinical laboratory. The calculated CV (%) for repeatability (calculated by simple estimation of the mean and SD, as used by the manufacturer) was between 5.5% and 7.4%, but the manufacturer's claim was between 4.1% and 6.5%. Using ANOVA, the true repeatability was between 5.0% and 6.9%. Similarly, ANOVA revealed values of CV (%) for within-laboratory imprecision between 6.5% and 9.1%, while the manufacturer's claims were between 4.1% and 5.9%. The recovery ranged from 105.5% to 121.8%. The manufacturer's recommended reference interval was checked and we didn't find any significant difference between men and women. CONCLUSIONS: We describe a comprehensive approach to verify the analytical performance of an ELISA method using the measurement of PCSK9 plasma concentration as an example. We found differences between the results of this approach based on the CLSI EP15-A3 protocol and data provided by the manufacturer. We recommend the verification of analytical performance by more complex statistical tools in laboratory practice.

GRADE guidance 37: rating imprecision in a body of evidence on test accuracy.

OBJECTIVES: To provide guidance on rating imprecision in a body of evidence assessing the accuracy of a single test. This guide will clarify when Grading of Recommendations Assessment, Development and Evaluation (GRADE) users should consider rating down the certainty of evidence by one or more levels for imprecision in test accuracy. STUDY DESIGN AND SETTING: A project group within the GRADE working group conducted iterative discussions and presentations at GRADE working group meetings to produce this guidance. RESULTS: Before rating the certainty of evidence, GRADE users should define the target of their certainty rating. GRADE recommends setting judgment thresholds defining what they consider a very accurate, accurate, inaccurate, and very inaccurate test. These thresholds should be set after considering consequences of testing and effects on people-important outcomes. GRADE's primary criterion for judging imprecision in test accuracy evidence is considering confidence intervals (i.e., CI approach) of absolute test accuracy results (true and false, positive, and negative results in a cohort of people). Based on the CI approach, when a CI appreciably crosses the predefined judgment threshold(s), one should consider rating down certainty of evidence by one or more levels, depending on the number of thresholds crossed. When the CI does not cross judgment threshold(s), GRADE suggests considering the sample size for an adequately powered test accuracy review (optimal or review information size [optimal information size (OIS)/review information size (RIS)]) in rating imprecision. If the combined sample size of the included studies in the review is smaller than the required OIS/RIS, one should consider rating down by one or more levels for imprecision. CONCLUSION: This paper extends previous GRADE guidance for rating imprecision in single test accuracy systematic reviews and guidelines, with a focus on the circumstances in which one should consider rating down one or more levels for imprecision.

Evaluation of imprecision in the different detection methods of Zn based on 5 years of data from an external quality assessment program in China.

BACKGROUND: This study examines the imprecision of zinc (Zn) measurements across various clinical detection methods by analyzing the external quality assessment (EQA) data from 2018 to 2022. The findings of this study aim to offer recommendations for enhancing Zn measurements. METHODS: Participating laboratories were grouped into peer categories based on the detection methods. The robust mean and coefficient of variation (CV) of the samples were calculated following ISO 13528 guidelines. The evaluation criteria for optimal, desirable, and minimum allowable imprecision in Zn estimation are 2.50%, 5.05%, and 7.55%, respectively, based on biological variation. Furthermore, the study examined inter-lab CVs, inter-method bias, and the passing rate. The impact of sample concentration on CVs and the pass rate was also investigated. RESULTS: Over the past five years, 4283 laboratories participated in the EQA program, showing a high pass rate that improved as sample concentration increased. Differential pulse polarography (DPP) demonstrated stable and low CVs (0.61-1.86%). Although differential pulse stripping (DPS) was less stable than DPP, it still exhibited a low CV (0.71-3.10%). Graphite furnace atomic absorption spectrometry (GFAAS) and flame atomic absorption spectrometry (FAAS) performed similarly and displayed stable CVs (2.39-4.42%) within the acceptable range of desirable imprecision (5.05%). However, the CVs for ICP-MS were unacceptable in three out of the five years (5.28-6.20%). In 2022, the number of participating laboratories for DDP, DPS, GFAAS, FAAS and ICP-MS is 131, 35, 35, 820 and 72, respectively. CONCLUSION: This study provides reliable insights into the imprecision of Zn measurements in clinical laboratories. The findings indicate that additional efforts are required to reduce the imprecision of ICP-MS in Zn measurements.

Six SIGMA evaluation of 17 biochemistry parameters using bias calculated from internal quality control and external quality assurance data.

Background: Six Sigma is a popular quality management system that enables continuous monitoring and improvement of analytical performance in the clinical laboratory. We aimed to calculate sigma metrics and quality goal index (QGI) for 17 biochemical analytes and compare the use of bias from internal quality control (IQC) and external quality assurance (EQA) data in the calculation of sigma metrics. Methods: This retrospective study was conducted in Marmara University Pendik E&R Hospital Biochemistry Laboratory. Sigma metrics calculation was performed as (TEa-bias)/CV). CV was calculated from IQC data from June 2018 - February 2019. EQA bias was calculated as the mean of % deviation from the peer group means in the last seven surveys, and IQC bias was calculated as (laboratory control result mean-manufacturer control mean)/ manufacturer control mean) x100. In parameters where sigma metrics were <5; QGI=bias/1.5 CV) score of <0.8 indicated imprecision, >1.2 pointed inaccuracy, and 0.8-1.2 showed both imprecision and inaccuracy. Results: Creatine kinase (both levels), iron and magnesium (pathologic levels) showed an ideal performance with ≥6 sigma level for both bias determinations. Eight of the 17 parameters had different sigma levels when we compared sigma values calculated from EQA and IQC derived bias% while the rest were grouped at the same levels. Conclusions: Sigma metrics is a good quality tool to assess a laboratory's analytical performance and facilitate the comparison of the assay performances in the same manner across multiple systems. However, we might need to design a tight internal quality control protocol for analytes showing poor assay performance.

Imprecision of high-sensitivity cardiac troponin assays at the female 99th-percentile.

BACKGROUND: An analytical benchmark for high-sensitivity cardiac troponin (hs-cTn) assays is to achieve a coefficient of variation (CV) of ≤ 10.0 % at the 99th percentile upper reference limit (URL) used for the diagnosis of myocardial infarction. Few prospective multicenter studies have evaluated assay imprecision and none have determined precision at the female URL which is lower than the male URL for all cardiac troponin assays. METHODS: Human serum and plasma matrix samples were constructed to yield hs-cTn concentrations near the female URLs for the Abbott, Beckman, Roche, and Siemens hs-cTn assays. These materials were sent (on dry ice) to 35 Canadian hospital laboratories (n = 64 instruments evaluated) participating in a larger clinical trial, with instructions for storage, handling, and monthly testing over one year. The mean concentration, standard deviation, and CV for each instrument type and an overall pooled CV for each manufacturer were calculated. RESULTS: The CVs for all individual instruments and overall were ≤ 10.0 % for two manufacturers (Abbott CVpooled = 6.3 % and Beckman CVpooled = 7.0 %). One of four Siemens Atellica instruments yielded a CV > 10.0 % (CVpooled = 7.7 %), whereas 15 of 41 Roche instruments yielded CVs > 10.0 % at the female URL of 9 ng/L used worldwide (6 cobas e411, 1 cobas e601, 4 cobas e602, and 4 cobas e801) (CVpooled = 11.7 %). Four Roche instruments also yielded CVs > 10.0 % near the female URL of 14 ng/L used in the United States (CVpooled = 8.5 %). CONCLUSIONS: The number of instruments achieving a CV ≤ 10.0 % at the female 99th-percentile URL varies by manufacturer and by instrument. Monitoring assay precision at the female URL is necessary for some assays to ensure optimal use of this threshold in clinical practice.

When bias becomes part of imprecision: how to use analytical performance specifications to determine acceptability of lot-lot variation and other sources of possibly unacceptable bias.

ISO 15189 requires laboratories to estimate the uncertainty of their quantitative measurements and to maintain them within relevant performance specifications. Furthermore, it refers to ISO TS 20914 for instructions on how to estimate the uncertainty and what to take into consideration when communicating uncertainty of measurement with requesting clinicians. These instructions include the responsibility of laboratories to verify that bias is not larger than medically significant. If estimated to be larger than acceptable, such bias first needs to be eliminated or (temporarily) corrected for. In the latter case, the uncertainty of such correction becomes part of the estimation of the total measurement uncertainty. If small enough to be acceptable, bias becomes part of the long term within laboratory random variation. Sources of possible bias are (not limited to) changes in reagent or calibrator lot variation or calibration itself. In this paper we clarify how the rationale and mathematics from an EFLM WG ISO/A position paper on allowable between reagent lot variation can be applied to calculate whether bias can be accepted to become part of long-term imprecision. The central point of this rationale is to prevent the risk that requesting clinicians confuse changes in bias with changes in the steady state of their patients.

Are analytical performance specifications derived from reference intervals of any use in the veterinary clinical laboratory? A preliminary study on the empirical biological variation model.

BACKGROUND: Analytical performance specifications (APS) are vital for method evaluation and quality control validation. However, the limited availability of biological variation (BV) data, regulatory guidelines, and expert opinion (EO) may present challenges in veterinary medicine. The empirical biological variation (EBV) approach, based on population reference intervals (pRI), has emerged as an alternative method to derive APS in human medicine. OBJECTIVES: This study aimed to assess the practicality and usefulness of the EBV approach in deriving performance limits for various measurands in dogs and cats. METHODS: Eight hematology and 13 biochemistry measurands were analyzed in dogs and cats. Estimates of combined biologic variation based on traditional biological (CVB ) and EBV-derived (CVE *) formulas were calculated and assessed for evidence of correlation. Performance limits for expanded uncertainty/total error and imprecision were compared among EO, BV, and EBV. RESULTS: Strong and significant correlations were found between CVB and CVE * for both dogs (r = .86, p < .00001) and cats (r = 0.95, p < .00001). The EBV-derived APS were generally comparable to EO and BV, with a subjective criterion of 1.5% difference for imprecision and 3% for total error/expanded uncertainty. CONCLUSION: The EBV approach, using pRI, shows promise as a surrogate marker for biological variation and as a practical tool for determining performance limits in dogs and cats. Assuming accurate pRI generated on analyzers with stable analytical performance, this approach could offer benefits when expert recommendations or robust BV studies are lacking or yield conflicting results. Further research is needed to explore the applicability and advantages of the EBV in veterinary medicine.

Signal-to-noise of linear and volume measures of left ventricular and left atrial size.

BACKGROUND: Serial echocardiographic assessments are common in clinical cardiology, e.g., for timing of intervention in mitral and aortic regurgitation. When following patients with serial echocardiograms, each new measurement is a combination of true change and confounding noise. The current investigation compares linear chamber dimensions with volume estimates of chamber size. The aim is to assess which measure is best for serial echocardiograms, when the ideal parameter will be sensitive to change in chamber size and have minimal spurious variation (noise). We present a method that disentangles true change from noise. Linear regression of chamber size against elapsed time gives a slope, being the ability of the method to detect change. Noise is the scatter of individual points away from the trendline, measured as the standard error of the slope. The higher the signal-to-noise ratio (SNR), the more reliably a parameter will distinguish true change from noise. METHODS: LV and LA parasternal dimensions and apical biplane volumes were obtained from serial clinical echocardiogram reports. Change over time was assessed as the slope of the linear regression line, and noise was assessed as the standard error of the regression slope. Signal-to-noise ratio is the slope divided by its standard error. RESULTS: The median number of LV studies was 5 (4-11) for LV over a mean duration of 5.9 ± 3.0 years in 561 patients (diastole) and 386 (systole). The median number of LA studies was 5 (4-11) over a mean duration of 5.3 ± 2.0 years in 137 patients. Linear estimates of LV size had better signal-to-noise than volume estimates (p < 0.001 for diastolic and p = 0.035 for systolic). For the left atrium, the difference was not significant (p = 0.214). This may be due to sample size; the effect size was similar to that for LV systolic size. All three parameters had a numerical value of signal-to-noise that favoured linear dimensions over volumes. CONCLUSION: Linear measures of LV size have better signal-to-noise than volume measures. There was no difference in signal-to-noise between linear and volume measures of LA size, although this may be a Type II error. The use of regression lines may be better than relying on single measurements. Linear dimensions may clarify whether changes in volumes are real or spurious.

Impact of analytical imprecision and bias on patient classification.

OBJECTIVES: An increase in analytical imprecision and/or the introduction of bias can affect the interpretation of quantitative laboratory results. In this study, we explore the impact of varying assay imprecision and bias introduction on the classification of patients based on fixed thresholds. METHODS: Simple spreadsheets (Microsoft Excel) were constructed to simulate conditions of assay deterioration, expressed as coefficient of variation and bias (in percentages). The impact on patient classification was explored based on fixed interpretative limits. A combined matrix of imprecision and bias of 0%, 2%, 4%, 6%, 8%, and 10% (tool 1) as well as 0%, 2%, 5%, 10%, 15%, and 20% (tool 2) was simulated, respectively. The percentage of patients who were reclassified following the addition of simulated imprecision and bias was summarized and presented in tables and graphs. RESULTS: The percentage of patients who were reclassified increased with increasing/decreasing magnitude of imprecision and bias. The impact of imprecision lessens with increasing bias such that at high biases, the bias becomes the dominant cause for reclassification. CONCLUSIONS: The spreadsheet tools, available as Supplemental Material, allow laboratories to visualize the impact of additional analytical imprecision and bias on the classification of their patients when applied to locally extracted historical results.

Evaluation of Coefficients of Variation for Clinical Chemistry Tests Based on Internal Quality Control Data Across 5,425 Laboratories in China From 2013 to 2022.

Background: Clinical chemistry tests are most widely used in clinical laboratories, and diverse measurement systems for these analyses are available in China. We evaluated the imprecision of clinical chemistry measurement systems based on internal QC (IQC) data. Methods: IQC data for 27 general chemistry analytes were collected in February each year from 2013 to 2022. Four performance specifications were used to calculate pass rates for CVs of IQC data in 2022. Boxplots were drawn to analyze trends of CVs, and differences in CVs among different groups were assessed using the Mann-Whitney U-test or Kruskal-Wallis test. Results: The number of participating laboratories increased significantly from 1,777 in 2013 to 5,425 in 2022. CVs significantly decreased for all 27 analytes, except creatine kinase and lipase. Triglycerides, total bilirubin, direct bilirubin, iron, and γ-glutamyl transferase achieved pass rates >80% for all goals. Nine analytes with pass rates <80% based on 1/3 allowable total error were further analyzed; the results indicated that closed systems exhibited lower CVs than open systems for all analytes, except total protein. For all nine analytes, differences were significant between tertiary hospitals and non-tertiary hospitals and between accredited and non-accredited laboratories. Conclusions: The CVs of IQC data for clinical chemistry have seen a continuous overall improvement in China. However, there is ample room for imprecision improvement for several analytes, with stricter performance specifications.

Effect of storage temperature and time on measurement of serum symmetric dimethylarginine concentration using point-of-care and commercial laboratory analyzers in cats and dogs.

BACKGROUND: Stability of serum symmetric dimethylarginine (sSDMA) during short- and long-term storage has not been assessed for the immunoassay of the Point-of-Care IDEXX Catalyst DX (POC) analyzer and the Enzyme Multiplied Immunoassay Technique of IDEXX commercial laboratory (CL). Also, the agreement between both analyzers is questioned. OBJECTIVES: To determine (a) the effect of storage time and temperature on sSDMA measured by POC and CL; (b) the agreement between sSDMA measured by POC and CL; and (c) the imprecision of the POC. ANIMALS: Serum of cats (n = 17) and dogs (n = 18) with a range of SDMA concentrations (6 to >100 µg/dL). METHODS: Based on an equivalence trial with predefined equivalence range (-3.0 to +3.0 µg/dL) and using T0 as baseline, stability was evaluated after 24 hours at 22°C and 4°C (POC); after 7 days at 4°C (POC and CL) and after 10 and 24 months at -24°C and -80°C (CL). Bland-Altman plots enabled method comparison. Imprecision of the POC was assessed by duplicate sSDMA measurements at T0. RESULTS: The POC analyzer produced equivalent sSDMA measurements if samples were stored for 24 hours at 4°C (95% confidence interval [CI]: -2.5-2.0 µg/dL), but not when stored for 24 hours at room temperature (RT; 95% CI: -4.1 to 0.5 µg/dL) or after 7 days at 4°C (95% CI: -3.6-1.0 µg/dL). The CL analyzer was less affected by preanalytical variation with clinically similar results obtained when samples were stored for 7 days at 4°C (95% CI: -2.2 to 2.4 µg/dL) and for at least 24 months at -24°C (95% CI: -1.7 to 2.9 µg/dL) and -80°C (95% CI: -1.5 to 3 µg/dL). A relevant mean difference of -2.3 µg/dL between both analyzers was found. Duplicate POC measurements were equivalent (95% CI: -2.6 to 2.0 µg/dL). CONCLUSIONS: Delayed analysis may significantly change sSDMA depending on storage and measurement conditions. Interchangeable use of assays should be done with caution because analytical variation could be interpreted as clinically relevant change.

The pipetting Olympics: Propagating proper pipetting a priori in clinical LC-MS/MS analysis.

Introduction: Engaging pipetting events were developed to assess and challenge technicians' practical sample handling using matrices common to the clinical laboratory. As correct pipetting stands as a prerequisite for accurate clinical laboratory testing, this helped to understand sources of imprecision and bias attributed to the underlying step of aspirating and dispensing patient samples and internal standard in clinical LC-MS/MS assays while highlighting the importance for the clinical laboratory to evaluate this source of variability on an on-going basis and mitigate its impact. Methods: The events involved pipetting water, methanol, serum, and whole blood. Gravimetric analysis was used to determine the exact volumetric delivery of each matrix using two different techniques. Imprecision and bias were calculated based on the volume derived from the mass and density of each matrix, using literature values for each matrix type. Results: Low imprecision and bias were observed when pipetting water, as in common commercial pipetting assessment programs. Significantly increased imprecision and bias were observed in more applicable matrices (i.e., serum, whole blood, and methanol), indicating that water-based pipetting proficiency assessment leads to a false sense of technical ability. Additionally, the events within illuminated areas for training, leading to improved imprecision and bias. It was shown that pre-rinsing (aspirating and dispensing matrix three times to coat the tip) improved bias, particularly for delivery of methanol and whole blood. Conclusions: Precise and accurate pipetting within the clinical laboratory should not be taken for granted, nor implicitly inferred from proficiency assessment using aqueous solutions. The engaging and collegial events fostered training opportunities. Assay-specific patient sample delivery considerations (pipets and matrices) can inform the practicality of these events - the Pipetting Olympics - and drive improvements within the laboratory.

LC-MS/MS in clinical chemistry: Did it live up to its promise?: Consideration from the Dutch EQAS organisation.

BACKGROUND: Over the past decade the use of LC-MS/MS has increased significantly in the hospital laboratories. Clinical laboratories have switched from immunoassays to LC-MS/MS methods due to the promise of improvements in sensitivity and specificity, better standardization with often non-commutable international standards, and better between-laboratory comparison. However, it remains unclear whether routine performance of the LC-MS/MS methods have met these expectations. METHOD: This study examined the EQAS results, from the Dutch SKML, of serum cortisol, testosterone, 25OH-vitaminD and cortisol in urine and saliva over 9 surveys (2020 to first half of 2021). RESULTS: The study found a significant increase in the number of compounds and in the number of results measured in the different matrices, with LC-MS/MS over a period of eleven years. In 2021, approximately 4000 LC-MS/MS results were submitted (serum: urine: saliva = 58:31:11%) compared to only 34 in 2010. When compared to the individual immunoassays, the LC-MS/MS based methods for serum cortisol, testosterone and 25OH-vitaminD showed comparable but also higher between-laboratory CVs in different samples of the surveys. For cortisol, testosterone and 25OH-vitaminD the median CV was 6.8%, 6.1% and 4.7% respectively for the LC-MS/MS compared to 3.9-8.0%,4.5-6.7%, and 7.5-18.3% for immunoassays. However, the bias and imprecision of the LC-MS/MS was better than that of the immunoassays. CONCLUSION: Despite the expectation that LC-MS/MS methods would result in smaller between-laboratory differences, as they are relatively matrix independent and better to standardize, the results of the SKML round robins do not reflect this for some analytes and may be in part explained by the fact that in most cases laboratory developed tests were used.