The use of error and uncertainty methods in the medical laboratory

Analytical performance specifications based on biological variation data - considerations, strengths and limitations

Analytical performance specifications (APS) are typically established through one of three models: (i) outcome studies, (ii) biological variation (BV), or (iii) state-of-the-art. Presently, The APS can, for most measurands that have a stable concentration, be based on BV. BV based APS, defined for imprecision, bias, total allowable error and allowable measurement uncertainty, are applied to many different processes in the laboratory. When calculating APS, it is important to consider the different APS formulae, for what setting they are to be applied and if they are suitable for the intended purpose. In this opinion paper, we elucidate the background, limitations, strengths, and potential intended applications of the different BV based APS formulas. When using BV data to set APS, it is important to consider that all formulae are contingent on accurate and relevant BV estimates. During the last decade, efficient procedures have been established to obtain reliable BV estimates that are presented in the EFLM biological variation database. The database publishes detailed BV data for numerous measurands, global BV estimates derived from meta-analysis of quality-assured studies of similar study design and automatic calculation of BV based APS.

Uso de glucómetros durante la prueba de tolerancia oral a la glucosa en niños para el diagnóstico de prediabetes y diabetes. Estudio comparativo

Objetivos

A pesar de que las guías clínicas aún no recomiendan el uso de glucómetros en el lugar de asistencia al paciente (POCT) con fines diagnósticos, la prestación analítica de estos dispositivos ha mejorado significativamente. En este contexto, evaluamos la precisión analítica y la concordancia diagnóstica de los glucómetros POCT durante la prueba de tolerancia oral a la glucosa (PTOG), para el diagnóstico de prediabetes y diabetes en un estudio comparativo.

Métodos

En este estudio prospectivo observacional, fueron reclutados pacientes pediátricos con indicación de PTOG, derivados a la Unidad de Diabetes entre diciembre de 2020 y septiembre de 2021. Durante la prueba funcional, se midió la glucemia en sangre venosa con dos glucómetros POCT (uno con conectividad y otro sin conectividad) y en el laboratorio central.

Resultados

El estudio incluyó 98 pacientes. Observamos una elevada correlación entre los glucómetros y el laboratorio (coeficiente de Pearson=0,912 para el glucómetro sin conectividad y 0,950 para el glucómetro con conectividad). El tiempo de respuesta de la PTOG disminuyó significativamente (mediana glucómetro con conectividad: 2,02 horas [rango intercuartílico: 2,00–2,07], laboratorio: 11,63 horas [6,09–25,80]), con un coste global similar. La concordancia diagnóstica entre el glucómetro con conectividad y el laboratorio fue del 71,1 % (IC 95 % 61,5–79,2). La decisión clínica hubiera sido la misma en el 92,8 % de los casos, aunque no se habría indicado tratamiento en cuatro pacientes (4,1 %).

Conclusiones

Durante las PTOG, los glucómetros POCT muestran una elevada correlación y una concordancia diagnóstica aceptable con el laboratorio, ofreciendo además el glucómetro con conectividad una reducción significativa del tiempo de respuesta, sin incrementar los costes. No obstante, dado que en algún caso podría haber un impacto clínico grave, los glucómetros POCT aún no deben ser utilizados con fines diagnósticos.

Use of point-of-care glucometers during an oral glucose tolerance test in children for prediabetes and diabetes diagnosis: a comparison study

Objectives

Despite clinical guidelines do not recommend the use of point-of-care testing (POCT) glucometers for diagnostic purposes yet, the analytical performance is continuously improving. Thus, we evaluate the technical accuracy and clinical concordance of POCT glucometers during an oral glucose tolerance test (OGTT) in children for prediabetes and diabetes diagnosis in a comparison study.

Methods

Pediatric patients with an OGTT indication who attended the Diabetes Unit between December 2020 and September 2021 were recruited for this prospective observational study. During the functional test, glycaemia was immediately measured in venous blood using two glucometers (unconnected and connected) and sent to the central laboratory.

Results

The study included 98 patients. There was a high correlation between the glucometers and the central laboratory (Pearson correlation coefficient=0.912 and 0.950, for unconnected and connected glucometer, respectively). The median OGTT turnaround time (TAT) was significantly decreased (connected glucometer: 2.02 h [interquartile range, 2.00-2.07], central laboratory: 11.63 h [6.09-25.80]), with similar overall cost. The diagnostic concordance between connected glucometer and the central laboratory was 71.1 % (95 % confidence interval (CI) 61.5-79.2). The clinical decision would have been the same in the 92.8 % of the cases, but treatment would have not been indicated in 4 patients (4.1 %).

Conclusions

POCT glucometers have demonstrated a high correlation and an acceptable diagnostic concordance with the central laboratory during an OGTT, as well the connected device offers a significant decrease in TAT, without increasing costs. However, as severe clinical impact could happen, POCT glucometers may not be used for diagnosis yet.

Report from the HarmoSter study: different LC-MS/MS androstenedione, DHEAS and testosterone methods compare well; however, unifying calibration is a double-edged sword

OBJECTIVES

Current liquid chromatography-tandem mass spectrometry (LC-MS/MS) applications for circulating androgen measurements are technically diverse. Previously, variable results have been reported for testosterone. Data are scarce for androstenedione and absent for dehydroepiandrosterone sulfate (DHEAS). We assessed the agreement of androstenedione, DHEAS and testosterone LC-MS/MS measurements among nine European centers and explored benefits of calibration system unification.

METHODS

Androgens were measured twice by laboratory-specific procedures in 78 patient samples and in EQA materials. Results were obtained by in-house and external calibration. Intra- and inter-laboratory performances were valued.

RESULTS

Intra-laboratory CVs ranged between 4.2-13.2 % for androstenedione, 1.6-10.8 % for DHEAS, and 4.3-8.7 % and 2.6-7.1 % for female and male testosterone, respectively. Bias and trueness in EQA materials were within ±20 %. Median inter-laboratory CV with in-house vs. external calibration were 12.0 vs. 9.6 % for androstenedione (p<0.001), 7.2 vs. 4.9 % for DHEAS (p<0.001), 6.4 vs. 7.6 % for female testosterone (p<0.001) and 6.8 and 7.4 % for male testosterone (p=0.111). Median bias vs. all laboratory median with in-house and external calibration were -13.3 to 20.5 % and -4.9 to 18.7 % for androstenedione, -10.9 to 4.8 % and -3.4 to 3.5 % for DHEAS, -2.7 to 6.5 % and -11.3 to 6.6 % for testosterone in females, and -7.0 to 8.5 % and -7.5 to 11.8 % for testosterone in males, respectively.

CONCLUSIONS

Methods showed high intra-laboratory precision but variable bias and trueness. Inter-laboratory agreement was remarkably good. Calibration system unification improved agreement in androstenedione and DHEAS, but not in testosterone measurements. Multiple components, such as commutability of calibrators and EQA materials and internal standard choices, likely contribute to inter-laboratory variability.

Evaluation of five multisteroid LC‒MS/MS methods used for routine clinical analysis: comparable performance was obtained for nine analytes

OBJECTIVES

A mass spectrometry (LC‒MS/MS)-based interlaboratory comparison study was performed for nine steroid analytes with five participating laboratories. The sample set contained 40 pooled samples of human serum generated from preanalyzed leftovers. To obtain a well-balanced distribution across reference intervals of each steroid, the leftovers first underwent a targeted mixing step.

METHODS

All participants measured a sample set once using their own multianalyte protocols and calibrators. Four participants used in-house developed measurement platforms, including IVD-CE certified calibrators, which were used by three participants; the 5th lab used the whole LC‒MS kit from an IVD manufacturer. All labs reported results for 17-hydroxyprogesterone, androstenedione, cortisol, and testosterone, and four labs reported results for 11-deoxycortisol, corticosterone, cortisone, dehydroepiandrosterone sulfate (DHEAS), and progesterone.

RESULTS

Good or acceptable overall comparability was found in Bland‒Altman and Passing‒Bablok analyses. Mean bias against the overall mean remained less than ±10 % except for DHEAS, androstenedione, and progesterone at one site and for cortisol and corticosterone at two sites (max. -18.9 % for androstenedione). The main analytical problems unraveled by this study included a bias not previously identified in proficiency testing, operator errors, non-supported matrix types and higher inaccuracy and imprecision at lower ends of measuring intervals.

CONCLUSIONS

This study shows that intermethod comparison is essential for monitoring the validity of an assay and should serve as an example of how external quality assessment could work in addition to organized proficiency testing schemes.

Diagnostic, Theranostic and Prognostic Value of Thyroglobulin in Thyroid Cancer

Thyroglobulin (Tg) is an iodinated glycoprotein, which is normally stored in the follicular colloid of the thyroid, being a substrate for thyroid hormone production. Since it is produced by well-differentiated thyroid cells, it is considered a reliable tumor marker for patients with differentiated thyroid carcinoma (DTC) during their follow-up after total thyroidectomy and radioiodine ablation. It is used to monitor residual disease and to detect recurrent disease. After total thyroid ablation, unstimulated highly sensitive Tg measurements are sufficiently accurate to avoid exogenous or endogenous thyrotropin (TSH) stimulation and provide accurate diagnostic and prognostic information in the great majority of DTC patients. Adopting sophisticated statistical analysis, i.e., decision tree models, the use of Tg before radioiodine theranostic administration was demonstrated to be useful in refining conventional, pathology-based risk stratification and providing personalized adjuvant or therapeutic radioiodine administrations. The follow-up of DTC patients aims to promptly identify patients with residual or recurrent disease following primary treatment. Our review paper covers the diagnostic, theranostic and prognostic value of thyroglobulin in DTC patients.

Establishing metrological traceability for small molecule measurands in laboratory medicine

For molecules that can be well described metrologically in the sense of the definition of measurands, and which can also be recorded analytically as individual substances, reference measurement service traceability to a metrologically sound foundation is a necessity. The establishment of traceability chains must be initiated by National Metrology Institutes (NMIs) according to applicable standards; they are at the top and leading position in this concept. If NMIs are not in the position to take up this task, alternative approaches must be sought. Traceability initiatives established by in vitro device industry or academia must meet the quality standards of NMIs. Adherence to International Organization for Standardization (ISO) procedure 15193 must be a matter of course for the establishment of reference measurement procedures (RMPs). Certified reference material (CRM) characterization must be thorough, e.g., by the application of quantitative nuclear magnetic resonance measurements and by adherence to ISO 15194. Both for RMPs and CRMs Joint Committee for Traceability in Laboratory Medicine (JCTLM) listing must be the ultimate goal. Results must be shared in a transparent manner to allow other stakeholders including NMIs to reproduce and disseminate the reference measurement procedures.

A comparative analysis of Sigma metrics using conventional and alternative formulas

BACKGROUND AND AIM

The Six Sigma approach, employing Sigma Metrics (SM), is commonly used to evaluate analytical performance in clinical laboratories. However, there is ongoing debate regarding the suitability of the conventional SM formula, which incorporates total allowable error (TEa) and bias. To address this, an alternative formula based on within-subject biological variation (CVI) as the tolerance range (TR) has been proposed. The study aimed to calculate and compare SM values using both formulas.

MATERIAL AND METHODS

Twenty clinical chemistry parameters were evaluated, and SM values were calculated using conventional formula with two TEa goals and the alternative formula. Intermediate precision (CVA%) values were obtained from internal quality control data, while bias values were derived from external quality assessment reports.

RESULTS

The results showed that using the conventional formula, 11 SM values based on CLIA TEa goals and 21 SM values based on BV TEa goals were deemed unacceptable (SM < 3). Additionally, 22 SM values calculated using the alternative formula were below 3.

CONCLUSION

The choice of TR had a substantial impact on the assessed analytical performance. Laboratories should carefully consider the appropriateness of each approach based on their specific quality objectives, analyte characteristics, and laboratory operations.

Thyroglobulin and thyroglobulin antibody: an updated clinical and laboratory expert consensus

OBJECTIVE

Thyroglobulin measurement is the cornerstone of modern management of differentiated thyroid cancer, with clinical decisions on treatment and follow-up based on the results of such measurements. However, numerous factors need to be considered regarding measurement with and interpretation of thyroglobulin assay results.

DESIGN

The present document provides an integrated update to the 2013 and 2014 separate clinical position papers of our group on these issues.

METHODS

Issues concerning analytical and clinical aspects of highly-sensitive thyroglobulin measurement will be reviewed and discussed based on an extensive analysis of the available literature.

RESULTS

Thyroglobulin measurement remains a highly complex process with many pitfalls and major sources of interference, especially anti-thyroglobulin antibodies, need to be assessed, considered and, when necessary, dealt with appropriately.

CONCLUSIONS

Our expert consensus group formulated 53 practical, graded recommendations for guidance on highly-sensitive thyroglobulin and TgAb in laboratory and clinical practice, especially valuable where current guidelines do not offer sufficient guidance.

Performance specifications for sodium should not be based on biological variation

When increasing the quality in clinical laboratories by decreasing measurement uncertainty, reliable methods are needed not only to quantify the performance of measuring systems, but also to set goals for the performance. Sigma metrics used in medical laboratories for documenting and expressing levels of performance, are evidently totally dependent on the "total permissible error" used in the formulas. Although the conventional biological variation (BV) based model for calculation of the permissible (or allowable) total error is commonly used, it has been shown to be flawed. Alternative methods are proposed, mainly also based on the within-subject BV. Measurement uncertainty models might offer an alternative to total error models. Defining the limits for analytical quality still poses a challenge in both models. The aim of the present paper is to critically discuss current methods for establishing performance specifications by using the measurement of sodium concentrations in plasma or serum. Sodium can be measured with high accuracy but fails by far to meet conventional performance specifications based on BV. Since the use of sodium concentrations is well established for supporting clinical care, we question the concept that quality criteria for sodium and similar analytes that are under strict homeostatic control are best set by biology.

Report from the HarmoSter study: inter-laboratory comparison of LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone

OBJECTIVES

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) panels that include glucocorticoid-related steroids are increasingly used to characterize and diagnose adrenal cortical diseases. Limited information is currently available about reproducibility of these measurements among laboratories. The aim of the study was to compare LC-MS/MS measurements of corticosterone, 11-deoxycortisol and cortisone at eight European centers and assess the performance after unification of calibration.

METHODS

Seventy-eight patient samples and commercial calibrators were measured twice by laboratory-specific procedures. Results were obtained according to in-house and external calibration. We evaluated intra-laboratory and inter-laboratory imprecision, regression and agreement against performance specifications derived from 11-deoxycortisol biological variation.

RESULTS

Intra-laboratory CVs ranged between 3.3 and 7.7%, 3.3 and 11.8% and 2.7 and 12.8% for corticosterone, 11-deoxycortisol and cortisone, with 1, 4 and 3 laboratories often exceeding the maximum allowable imprecision (MAI), respectively. Median inter-laboratory CVs were 10.0, 10.7 and 6.2%, with 38.5, 50.7 and 2.6% cases exceeding the MAI for corticosterone, 11-deoxycortisol and cortisone, respectively. Median laboratory bias vs. all laboratory-medians ranged from -5.6 to 12.3% for corticosterone, -14.6 to 12.4% for 11-deoxycortisol and -4.0 to 6.5% for cortisone, with few cases exceeding the total allowable error. Modest deviations were found in regression equations among most laboratories. External calibration did not improve 11-deoxycortisol and worsened corticosterone and cortisone inter-laboratory comparability.

CONCLUSIONS

Method imprecision was variable. Inter-laboratory performance was reasonably good. However, cases with imprecision and total error above the acceptable limits were apparent for corticosterone and 11-deoxycortisol. Variability did not depend on calibration but apparently on imprecision, accuracy and specificity of individual methods. Tools for improving selectivity and accuracy are required to improve harmonization.

Quality control of total carbon dioxide (CO2) in serum or plasma using the Abbott Architect is affected by environmental pCO2 concentrations

Introduction: Total CO₂, or bicarbonate, is a parameter in clinical chemistry often applied to assess the metabolic status of a patient. This article discusses the observations and interventions during an episode of assay instability on an Abbott Architect routine chemistry analyser.Results: The Levey-Jennings plot of QC data showed a circadian pattern, having an overestimation of total CO₂ during periods of high personnel attendance. A qualitative analysis revealed a correlation between atmospheric CO₂ in the lab environment and the acquired total CO₂ value in a quality control sample. Assessment of total CO₂ is hence influenced by the equilibrium between atmospheric CO₂, dissolved CO₂ and bicarbonate. The effect is more pronounced on samples containing low concentrations of total CO₂. The bias related to environmental CO₂ is also noticeable on patient samples, patient means between periods with high and low atmospheric CO₂ levels differed by 2 mmol/L.Discussion: Passive ventilation of the laboratory environment is proven insufficient during weather conditions in which the lab is not exposed to wind. Consistent reduction of atmospheric CO₂ could only be guaranteed with an active ventilation infrastructure. Systematic closure of analyser lids also reduced analyser variance.Conclusion: The lab environment is an important source of parameter variance. Both environmental and infrastructural aspects must be considered when assessing the potential cause of the instability.

Redesigning the surveillance of in vitro diagnostic medical devices and of medical laboratory performance by quality control in the traceability era

IVD manufacturers have total responsibility in terms of the traceability of marketed in vitro diagnostic medical devices (IVD-MD). This includes the provision of a quality control (QC) material as a part of the measuring system, suitable for traceability verification and alignment surveillance by end-users in daily practice. This material [to be used for the internal QC (IQC) component I as described in this paper] should have unbiased target values and an acceptability range corresponding to analytical performance specifications (APS) for suitable (expanded) measurement uncertainty (MU) on clinical samples. On the other hand, medical laboratories (by the IQC component II as described in this paper) should improve the IQC process and its judging criteria to establish a direct link between their performance, estimated as MU of provided results, and APS defined according to recommended models to apply corrective actions if the performance is worsening with the risk to jeopardize the clinical validity of test results. The participation to external quality assessment (EQA) programs that meet specific metrological criteria is also central to the evaluation of performance of IVD-MDs and of medical laboratories in terms of harmonization and clinical suitability of their measurements. In addition to the use of commutable materials, in this type of EQA it is necessary to assign values to them with selected reference procedures and to define and apply maximum allowable APS to substantiate the suitability of laboratory measurements in the clinical setting.

Method evaluation in the clinical laboratory

Method evaluation is one of the critical components of the quality system that ensures the ongoing quality of a clinical laboratory. As part of implementing new methods or reviewing best practices, the peer-reviewed published literature is often searched for guidance. From the outset, Clinical Chemistry and Laboratory Medicine (CCLM) has a rich history of publishing methods relevant to clinical laboratory medicine. An insight into submissions, from editors' and reviewers' experiences, shows that authors still struggle with method evaluation, particularly the appropriate requirements for validation in clinical laboratory medicine. Here, we consider through a series of discussion points an overview of the status, challenges, and needs of method evaluation from the perspective of clinical laboratory medicine. We identify six key high-level aspects of clinical laboratory method evaluation that potentially lead to inconsistency. 1. Standardisation of terminology, 2. Selection of analytical performance specifications, 3. Experimental design of method evaluation, 4. Sample requirements of method evaluation, 5. Statistical assessment and interpretation of method evaluation data, and 6. Reporting of method evaluation data. Each of these areas requires considerable work to harmonise the practice of method evaluation in laboratory medicine, including more empirical studies to be incorporated into guidance documents that are relevant to clinical laboratories and are freely and widely available. To further close the loop, educational activities and fostering professional collaborations are essential to promote and improve the practice of method evaluation procedures.

Quality in laboratory medicine and the Journal: walking together

Quality in laboratory medicine is defined as "an unfinished journey", as the more essential the laboratory information provided, the more assured its quality should be. In the past decades, the Journal Clinical Chemistry and Laboratory Medicine has provided a valuable forum for garnering new insights into the analytical and extra-analytical phases of the testing cycle, and for debating crucial aspects of quality in clinical laboratories. The impressive number of papers published in the Journal is testimony to the efforts made by laboratory professionals, national and international scientific societies and federations in the quest to continuously improve upon the pre-, intra- and post-analytical steps of the testing cycle, thus enhancing the quality of laboratory information. The paper appearing in this special issue summarizes the most important and interesting contributions published in the Journal, thus updating our knowledge on quality in laboratory medicine and offering further stimuli to identify the most valuable measures of quality in clinical laboratories.

Unsupervised Hierarchical Classification Approach for Imprecise Data in the Breast Cancer Detection

(1) Background: in recent years, a lot of the research of statistical methods focused on the classification problem in presence of imprecise data. A particular case of imprecise data is the interval-valued data. Following this research line, in this work a new hierarchical classification technique for multivariate interval-valued data is suggested for diagnosis of the breast cancer; (2) Methods: an unsupervised hierarchical classification method for imprecise multivariate data (called HC-ID) is performed for diagnosis of breast cancer (i.e., to discriminate between benign or malignant masses) and the results have been compared with the conventional (unsupervised) hierarchical classification approach (HC); (3) Results: the application on real data shows that the HC-ID procedure performs better HC procedure in terms of accuracy (HC-ID = 0.80, HC = 0.66) and sensitivity (HC-ID = 0.61, HC = 0.08). In the results obtained by the usual procedure, there is a high degree of false-negative (i.e., benign cancer diagnosis in malignant status) affected by the high degree of variability (i.e., uncertainty) characterizing the worst data.

Measurement uncertainty for practical use

Uncertainty is an inseparable part of all kinds of measurements performed in clinical laboratories. Accreditation standards including the ISO/IEC 17025:2017 and ISO 15189:2012 require that laboratories have routines for calculating the measurement uncertainty of reported results. Various guidelines such as CLSI EP29, Nordest 537, and ISO 20914:2019 have proposed methods for this purpose. However, due to the conceived complexity of the proposed calculation methods, these guidelines have not been generally and effectively applied in clinical laboratories. High workload and measurand heterogeneity favor a pragmatic utilitarian approach. The purpose of this paper is to describe such an approach, including its advantages and disadvantages. Measurement uncertainty should include the most influential factors affecting patients' test results. Since patients' samples for the same measurand can be analyzed in one laboratory or several laboratories using different measuring systems, the measurement uncertainty should be calculated using results obtained from analyzing the same internal quality control material if commutable or patients pooled/split samples.

Report from the HarmoSter study: impact of calibration on comparability of LC-MS/MS measurement of circulating cortisol, 17OH-progesterone and aldosterone

OBJECTIVES

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is recommended for measuring circulating steroids. However, assays display technical heterogeneity. So far, reproducibility of corticosteroid LC-MS/MS measurements has received scant attention. The aim of the study was to compare LC-MS/MS measurements of cortisol, 17OH-progesterone and aldosterone from nine European centers and assess performance according to external quality assessment (EQA) materials and calibration.

METHODS

Seventy-eight patient samples, EQA materials and two commercial calibration sets were measured twice by laboratory-specific procedures. Results were obtained by in-house (CAL1) and external calibrations (CAL2 and CAL3). We evaluated intra and inter-laboratory imprecision, correlation and agreement in patient samples, and trueness, bias and commutability in EQA materials.

RESULTS

Using CAL1, intra-laboratory CVs ranged between 2.8-7.4%, 4.4-18.0% and 5.2-22.2%, for cortisol, 17OH-progesterone and aldosterone, respectively. Trueness and bias in EQA materials were mostly acceptable, however, inappropriate commutability and target value assignment were highlighted in some cases. CAL2 showed suboptimal accuracy. Median inter-laboratory CVs for cortisol, 17OH-progesterone and aldosterone were 4.9, 11.8 and 13.8% with CAL1 and 3.6, 10.3 and 8.6% with CAL3 (all p<0.001), respectively. Using CAL1, median bias vs. all laboratory-medians ranged from -6.6 to 6.9%, -17.2 to 7.8% and -12.0 to 16.8% for cortisol, 17OH-progesterone and aldosterone, respectively. Regression lines significantly deviated from the best fit for most laboratories. Using CAL3 improved cortisol and 17OH-progesterone between-method bias and correlation.

CONCLUSIONS

Intra-laboratory imprecision and performance with EQA materials were variable. Inter-laboratory performance was mostly within specifications. Although residual variability persists, adopting common traceable calibrators and RMP-determined EQA materials is beneficial for standardization of LC-MS/MS steroid measurements.

Analytical performance evaluation of sensitive and old generation reagent in routine practical use: estradiol experience

Evaluation of the analytical performance of tests in medical laboratories is important. Total Error (TE) and sigma analysis have been used as a quantitative indicator of quality for many years. The aim of this study is to evaluate the analytical performance of Beckman Coulter Access Estradiol (E2) and Sensitive E2 reagents. Analytical performance of two reagents were evaluated with TE, six sigma and measurement uncertainty values. Two Beckman Coulter Unicel DxI-800 autoanalyzers (A1 and A2) included in the study. Quality control data between December 2017 and December 2019 were used. CLIA-2019 values were used for total allowable error (TEa) limits. Uncertainty values were calculated with ISO/TS 20914. The median TE of the old generation and sensitive E2 reagent were 27.46% (between 13.49 and 48.88) and 11.16% (between 7.08 and 24.81), respectively (p < .005) The process sigma results were below 3 sigma in all months with the old reagent, whereas with the new reagents it was seen to be above 3 sigma in 11 of 12 months for both autoanalyzers. Uncertainty of old reagent is higher than new reagent. Imprecisions decrease as concentration increases with both reagents. The uncertainty values of low concentration levels are greater than high concentration levels. In conclusion, in both auto analyzers, Sensitive E2 reagent was found to have better performance than old reagent in terms of TE, process sigma and measurement uncertainty. We believe that the sensitive E2 reagent still needs further improvement for patients who have low E2 levels.

ISO/TS 20914:2019 - a critical commentary

The long-anticipated ISO/TS 20914, Medical laboratories - Practical guidance for the estimation of measurement uncertainty, became publicly available in July 2019. This ISO document is intended as a guide for the practical application of estimating uncertainty in measurement (measurement uncertainty) in a medical laboratory. In some respects, the guide does indeed meet many of its stated objectives with numerous very detailed examples. Even though it is claimed that this ISO guide is based on the Evaluation of measurement data - Guide to the expression of uncertainty in measurement (GUM), JCGM 100:2008, it is with some concern that we believe several important statements and statistical procedures are incorrect, with others potentially misleading. The aim of this report is to highlight the major concerns which we have identified. In particular, we believe the following items require further comment: (1) The use of coefficient of variation and its potential for misuse requires clarification, (2) pooled variance and measurement uncertainty across changes in measuring conditions has been oversimplified and is potentially misleading, (3) uncertainty in the results of estimated glomerular filtration rate (eGFR) do not include all known uncertainties, (4) the international normalized ratio (INR) calculation is incorrect, (5) the treatment of bias uncertainty is considered problematic, (6) the rules for evaluating combined uncertainty in functional relationships are incomplete, and (7) specific concerns with some individual statements.

Preparing Laboratories for Interconnected Health Care

In an increasingly interconnected health care system, laboratory medicine can facilitate diagnosis and treatment of patients effectively. This article describes necessary changes and points to potential challenges on a technical, content, and organizational level. As a technical precondition, electronic laboratory reports have to become machine-readable and interpretable. Terminologies such as Logical Observation Identifiers Names and Codes (LOINC), Nomenclature for Properties and Units (NPU), Unified Code for Units of Measure (UCUM), and SNOMED-CT can lead to the necessary semantic interoperability. Even if only single “atomized” results of the whole report are extracted, the necessary information for correct interpretation must be available. Therefore, interpretive comments, e.g., concerns about an increased measurement uncertainty must be electronically attached to every affected measurement result. Standardization of laboratory analyses with traceable standards and reference materials will enable knowledge transfer and safe interpretation of laboratory analyses from multiple laboratories. In an interconnected health care system, laboratories should strive to transform themselves into a data hub that not only receives samples but also extensive information about the patient. On that basis, they can return measurement results enriched with high-quality interpretive comments tailored to the individual patient and unlock the full potential of laboratory medicine.

Recommendations for the application and follow-up of quality controls in medical laboratories

This is a translation of the paper “Recommendations for the application and follow-up of quality controls in medical biology laboratories” published in French in the journal Annales de Biologie Clinique (Recommandations pour la mise en place et le suivi des contrôles de qualité dans les laboratoires de biologie médicale. Ann Biol Clin (Paris). 2019;77:577-97.). The recommendations proposed in this document are the result of work conducted jointly by the Network of Accredited Medical Laboratories (LABAC), the French Society of Medical Biology (SFBC) and the Federation of Associations for External Quality Assessment (FAEEQ). The different steps of the implementation of quality controls, based on a risk analysis, are described. The changes of reagent or internal quality control (IQC) materials batches, the action to be taken in case of non-conform IQC results, the choice of external quality assessment (EQA) scheme and interpretation of their results as well as the new issue of analyses performed on several automatic systems available in the same laboratory are discussed. Finally, the concept of measurement uncertainty, the robustness of the methods as well as the specificities of near-patient testing and rapid tests are described. These recommendations cannot apply for all cases we can find in medical laboratories. The implementation of an objective alternative strategy, supported with documented evidence, might be equally considered.

Application of the sigma metrics to evaluate the analytical performance of cystatin C and design a quality control strategy

BACKGROUND

Sigma metrics are commonly used to evaluate laboratory management. In this study, we aimed to evaluate the analytical performance of cystatin C using sigma metrics and to develop an individualized quality control scheme for cystatin C concentrations.

METHODS

Bias was calculated based on the samples used for the external quality assessment. The coefficient of variation was calculated using six months of internal quality control measurements at two levels, and desirable specification derived from biological variation was used as the quality goal. The sigma value for cystatin C was calculated using the above data. The internal quality control scheme and improvement measures were formulated according to the Westgard sigma standards for batch size and quality goal index.

RESULTS

The sigma values for cystatin C, for quality control levels 1 and 2, were 3.04 and 4.95, respectively. The 1_3s/2_2s/R_4s/4_1s/6_x multirules (n = 6, R = 1), with a batch size of 45 patient samples, were selected as the internal quality control schemes for cystatin C. With different concentrations of cystatin C, the power function graph showed a probability for error detection of 94% and 100% and a probability for false rejection of 4% and 2%, respectively. According to the quality goal index of cystatin C, its precision needs to be improved.

CONCLUSIONS

With a 'desirable' biological variation of 6.50%, the Westgard rule 1_3s/2_2s/R_4s/4_1s/6_x (n = 6, R = 1, batch size of 45) with high efficacy for determining the detection error is recommended for individualized quality control schemes of cystatin C.

Estimation of the measurement uncertainty and practical suggestion for the description of the metrological traceability in clinical laboratories

Clinicians request a large part of measurements of biological quantities that clinical laboratories perform for diagnostic, prognostic or diseases monitoring purposes. Thus, laboratories need to provide patient’s results as reliable as possible. Metrological concepts like measurement uncertainty and metrological traceability allow to know the accuracy of these results and guarantee their comparability over time and space. Such is the importance of these two parameters that the estimation of measurement uncertainty and the knowledge of metrological traceability is required for clinical laboratories accredited by ISO 15189:2012. Despite there are many publications or guidelines to estimate the measurement uncertainty in clinical laboratories, it is not entirely clear what information and which formulae they should use to calculate it. On the other hand, unfortunately, there are a small number of clinical laboratories that know and describe the metrological traceability of their results, even though they are aware of the lack of comparability that currently exists for patient’s results. Thus, to try to facilitate the task of clinical laboratories, this review aims to provide a proposal to estimate the measurement uncertainty. Also, different suggestions are shown to describe the metrological traceability. Measurement uncertainty estimation is partially based on the ISO/TS 20914:2019 guideline, and the metrological traceability described using the ISO 17511:2020. Different biological quantities routinely measured in clinical laboratories are used to exemplify the proposal and suggestions.

Measurement uncertainty as a universal concept: can it be universally applicable in routine laboratory practice?

Measurement uncertainty (MU) of results is one of the basic recommended and accepted statistical methods in laboratory medicine, with which analytical and clinical evaluation of laboratory test quality is assessed. Literature data indicate that the calculation of MU is not a simple process, but that its assessment in daily laboratory practice should be reduced to routine and simple presentation, understandable to both laboratory professionals and physicians. In order to achieve this, it is necessary to understand the purpose of the test for which MU is to be determined. Various suggestions have been given for presentation of MU as a quantitative indicator of the quality of the final measurement result in the medical laboratory. Although MU refers to the final measurement result, this metrological concept reflects the entire laboratory measurement process. The data on estimated MU is used to interpret the measured numerical result, and represents quantitatively the quality of the measurement itself, i.e. how different are the results of multiple measurements of the analyte of interest in the same sample, as well as whether the method of determination itself is subjected to significant random and systematic deviation. Initially, in the metrological concept, the MU is viewed in relation to the true value of the analyte of interest. However, the true value of the analyte measured in the biological fluid matrix of the study population cannot be known. It is therefore considered the closest value obtained by the perfect method, for which the bias and inaccuracy, as measures of systematic and random error, are equal to zero, which is practically impossible to achieve in routine laboratory practice. Although current standards require accredited medical laboratories to estimate MU, none of these guidelines provide clear guidance on how this can be achieved in daily laboratory work. This review examines literary data and documents dealing with MU issues, but also highlights what additional terms and data should be considered when interpreting MU. This paper ultimately draws attention, and once again points out, that a simpler solution is needed for this universal concept to be formally and universally applicable in routine laboratory medicine practice.

Interpol review of toxicology 2016-2019

This review paper covers the forensic-relevant literature in toxicology from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20.Papers%202019.pdf.

The internal quality control in the traceability era

To be accurate and equivalent, laboratory results should be traceable to higher-order references. Furthermore, their quality should fulfill acceptable measurement uncertainty (MU) as defined to fit the intended clinical use. With this aim, in vitro diagnostics (IVD) manufacturers should define a calibration hierarchy to assign traceable values to their system calibrators. Medical laboratories should know and verify how manufacturers have implemented the traceability of their calibrators and estimate the corresponding MU on clinical samples. Accordingly, the internal quality control (IQC) program should be redesigned to permit IVD traceability surveillance through the verification by medical laboratories that control materials, provided by the manufacturer as a part of measuring systems, are in the clinically suitable validation range (IQC component I). Separately, laboratories should also monitor the reliability of employed IVD measuring systems through the IQC component II, devoted to estimation of MU due to random effects and to obtaining MU of provided results, in order to apply prompt corrective actions if the performance is worsening when compared to appropriate analytical specifications, thus jeopardizing the clinical validity of test results.

Evaluating sample stability in the clinical laboratory with the help of linear and non-linear regression analysis

As it is common practice for laboratories to store patient samples for a predefined period, allowing clinicians to request additional tests on previously collected samples, knowledge about sample stability is indispensable for the laboratorian. A common approach to estimating the maximum storage time is to use a discrete study design, measuring the analyte of interest at various time-points and then checking for significant differences with the help of a statistical test, such as Student's t-test, Wilcoxon's test or an analysis of variance (ANOVA) test. Because only discrete time intervals are considered, stability data can just be approximated. Alternatively, a continuous study design, as described by the Clinical and Laboratory Standards Institute (CLSI) for performing stability experiments for in vitro diagnostic reagents, can also be adopted by the clinical laboratory to evaluate the stability of biological samples. The major advantage of this approach is that it allows laboratories to define individual stability limits for different medical situations and offers more flexibility when choosing time-points for measurements. The intent of this paper is to demonstrate the evaluation of sample stability in the clinical laboratory with a continuous study design implemented with linear or non-linear regression analysis. Appropriate statistical modeling and acceptance criteria are presented, stability functions are described briefly, and checking the overall validity of the results is discussed.

Measurement repeatability profiles of eight frequently requested measurands in clinical chemistry determined by duplicate measurements of patient samples

Measurement uncertainties in clinical chemistry are commonly regarded as heteroscedastic - having a constant relative standard deviation irrespective of the concentration of the measurand. The uncertainty is usually determined at two concentrations using stabilized control materials and assumed to represent the analytical goal. The purpose of the present study was to use duplicates of unselected patient samples to calculate the absolute and relative repeatability component of the intra-laboratory measurement uncertainty from duplicates, using the Dahlberg formula and analysis of variance components. Estimates were made at five different concentration intervals of ALT, AST, Calcium, Cholesterol, Creatinine, CRP, Triglycerides and TSH covering the entire concentration interval of the patient cohort. This partioning allows detailing their repeatability profiles. The calculations of the profiles were based on randomly selected results from sets of duplicates ranging from 12,000 to 65,000 pairs. The repeatability of the measurands showed substantial variability within the measuring interval. Therefore, characterizing imprecision profiles as purely homo- or heteroscedastic or by a single number may not be optimal for the intended use. The present data make a case for nuancing the evaluation of analytical goals and minimal differences of measurement results by establishing uncertainty profiles under repeatability conditions, using natural patient samples.

Assessing the measurement uncertainty of qualitative analysis in the clinical laboratory

Measurement uncertainty is a parameter that is associated with the dispersion of measurements. Assessment of the measurement uncertainty is recommended in qualitative analyses in clinical laboratories; however, the measurement uncertainty of qualitative tests has been neglected despite the introduction of many adequate methods. We herein provide an overview of three reasonable statistical methods for quantifying the measurement uncertainties of qualitative assays, namely Bayes’ theorem, the normal distribution method, and the information theoretic approach. Unlike in quantitative analysis, the measurement uncertainty of qualitative analysis is expressed using a conditional probability, likelihood ratio, and entropy. With the necessary theoretical background, the practical applications for clinical laboratories are also provided using statistical calculations. Using statistical approaches, we hope that our review will contribute to the use of measurement uncertainty in qualitative analyses in the clinical laboratory environment.

Performance characteristics of automated clinical chemistry analyzers using commercial assay reagents contributing to quality assurance and clinical decision in a hospital laboratory

Background: Clinical laboratories provide essential diagnostic services that are essential in clinical decision making, contributing to the quality of healthcare. The performance of two Siemens ADVIA 1800 analyzers was characterized in a hospital Biochemistry laboratory in order to evaluate the analytical characteristics of such automated analyzer systems using nonoriginal assay reagents attempting to support laboratory quality service and crucial clinical decision making. Methods: We independently completed performance validation studies including trueness, precision, sensitivity as well as measurement of uncertainty and sigma metrics calculation for 25 biochemical parameters. Results: Trueness expressed as bias was less than 20% for both ADVIA 1800 analyzers. Within run and total precisions expressed as CV% were ≤9.85% on both analyzers for most parameters studied with few exceptions (Mg, TB, DB, Cl, HDL and UA) observed either in low or in high level samples and between the two analyzers. LoB, LoD and LoQ values produced by the two analyzers were comparable except Cl. Uncertainty values produced by the two analyzers were comparable with no significant differences. Quality performance of reagent assays was studied using the sigma metrics system. The sigma values were plotted on normalized method decision charts for graphical representation of assay performances for each analyzer. Conclusions: The two ADVIA systems, independently evaluated, showed consistent performance characteristics with certain discrepancies by several reagents. Sigma analysis was helpful for revealing the quality performance of non-original reagents supporting the need for strict assessment of quality assurance and in some instances optimization/improvement of assay methods.

Recommended changes of the current version of the German Rili-BAEK

A number of improvement proposals and corrections of the German Rili-BAEK (Guideline of the German Medical Association on Quality Assurance in Medical Laboratory Examinations) are discussed with special focus on the internal and external quality assurance (IQA/EQA) as well as reference intervals for quantitative results. Particular attention is paid to reconsider the retrospective analysis of control measurements. Such an analysis can be very useful to monitor establishing errors of measurement even before they become critical. The present method “Quadratischer Mittelwert der Messabweichung (QMMA)” has proved to be ineffective. Furthermore, the current idea of a common limit for single control measures and the retrospective statistics must be revised. As a more sophisticated concept, the novel Adaptive Retrospective Monitoring (ARM) has been developed. ARM is recommended as the new minimum requirement for the entire internal quality assurance. Further proposals to enhance clarity are given concerning the release decisions of medical devices and the EQA. Individualized medicine begins with a patient-specific interpretation of analytic results. This requires standardized subgroup-specific reference intervals with smooth age-related adaptations. Only large laboratories are able to ensure the desired specificity and a sufficient statistical significance of self-developed in-laboratory reference intervals. Hence, the need of a central database for harmonized reference intervals is discussed and recommended. Suitable and consistent reference intervals are also an essential prerequisite for unitless laboratory values like the zlog value.

Uncertainty in measurement and total error: different roads to the same quality destination?

The debate comparing the benefits of measurement uncertainty (uncertainty in measurement, MU) with total error (TE) for the assessment of laboratory performance continues. The summary recently provided in this journal by members of the Task and Finish Group on Total Error (TFG-TE) of the EFLM put the arguments into clear perspective. Even though there is generally strong support for TE in many laboratories, some of the arguments proposed for its on-going support require further comment. In a recent opinion which focused directly on the TFG-TE summary, several potentially confusing statements regarding ISO15189 and the Evaluation of measurement data - Guide to the expression of uncertainty in measurement (GUM) were again promulgated to promote TE methods for assessing uncertainty in laboratory measurement. In this opinion, we present an alternative view of the key issues and outline our views with regard to the relationship between ISO15189, uncertainty in measurement and the GUM.

Determination of sigma score based on biological variation for haemostasis assays: fit-for-purpose for daily practice?

Background

Internal quality control (QC) rules for laboratory tests can be derived from analytical performance specifications (APS) using the six-sigma method. We tested the applicability of this paradigm to routine haemostasis measurements.

Methods

Three laboratories using different instruments and reagents calculated sigma scores for their prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen and antithrombin (AT) measurements. Sigma scores were calculated using biological variation (BV) data from the literature in combination with internal and external QC data.

Results

Wide ranges in sigma scores for the PT (0.1–6.8), APTT (0.0–4.3), fibrinogen (1.5–8.3) and AT (0.1–2.4) were observed when QC data was combined with the minimum, median and maximum value of BV data, due in particular to a large variation in within-subject and between-subjects coefficients of variation. When the median BV values were applied, most sigma scores were below 3.0, for internal QC data; 75% and for external QC data; 92%.

Conclusions

Our findings demonstrate that: (1) The sigma scores for common haemostasis parameters are relatively low, and (2) The application of the six-sigma method to BV-derived APS is hampered by the large variation in published BV data. As the six-sigma concept is based on requirements for monitoring, and many haemostasis tests are only designed for diagnostic purposes, a fit-for-purpose APS is needed to achieve clinically relevant quality goals.

Extra-analytical sources of uncertainty: which ones really matter?

Since the endorsement by ISO15189:2012 of measurement uncertainty (MU) for the estimation of error in measurement procedures, the debate has been ongoing with questions concerning which method should be used for estimating MU and the benefits of using MU over other error methods. However, only limited attention has been given to extra-analytical sources of uncertainty and, currently, a clear standpoint is still missing. This opinion paper aims to evaluate whether extra-analytical variables could be included in MU. Considering coagulation tests as an example, the possible sources of preanalytical variations are evaluated by using a fishbone diagram. After excluding preanalytical errors, additional sources of uncertainty are divided into amenable to standardization/harmonization and/or possible random sources, which are not standardizable nor harmonizable. Finally, sources of uncertainty are evaluated for a possible inclusion into MU. In addition, postanalytical uncertainty is discussed, particularly considering the laboratory results calculated through a mathematical equation, derived from one or more quantities affected by their specific uncertainty.

Measurement uncertainty and metrological traceability of whole blood cyclosporin A mass concentration results obtained by UHPLC-MS/MS

BACKGROUND

Traceable and accurate results of cyclosporine A (CsA) mass concentrations in whole blood are required to ensure the monitoring of immunosuppressive therapy in transplant recipients. Metrological traceability and measurement uncertainty can allow ensuring reliability and comparability of these results over time and space. In this study, we provide a practical and detailed example of how the traceability and uncertainty of mass concentration of CsA results, obtained using an ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) procedure, can be described and estimated.

METHODS

Traceability was described mainly according to ISO 17511 and information obtained from certificates facilitated with the manufacturer's calibrators. Uncertainty estimation was performed using the bottom-up and top-down approaches. For the bottom-up approach, the most relevant sources of uncertainty were identified and later used to estimate the standard, combined and expanded uncertainties. For the top-down approach, expanded uncertainty was estimated directly using intralab quality control data mainly.

RESULTS

Mass concentration of CsA results was traceable to the manufacturer's product calibrators used to calibrate the UHPLC-MS/MS procedure. The expanded uncertainties estimated by the bottom-up and top-down approaches were 7.4% and 7.2%, respectively.

CONCLUSIONS

After performing the bottom-up and top-down approaches, we observed that their results were quite similar. This fact would confirm that the top-down approach could be sufficient for estimating uncertainty of CsA mass concentrations in whole blood results in clinical laboratories. Finally, we hope that this study can help and motivate clinical laboratories to describe metrological traceability and to perform measurement uncertainty studies based on the simpler top-down approach.

Sources and solutions for spurious test results in coagulation

In the coagulation laboratory, much emphasis has been placed on rapid and accurate testing; however, spurious results that are inaccurate and do not reflect the actual status of the patient can potentially lead to an incorrect diagnosis and altered intervention. Errors in coagulation results and interpretation can occur at any point of the process from obtaining the specimen to interpretation and use of the result by the clinician. The main sources of error include the patient's biological and preanalytical variation, analytical testing, and postanalytical use of the reported result(s). This article reviews various sources of error leading to spurious results, providing methods to recognize these aberrant results and presenting solutions for minimizing their occurrence.

Analytical Sigma metrics: A review of Six Sigma implementation tools for medical laboratories

Sigma metrics have become a useful tool for all parts of the quality control (QC) design process. Through the allowable total error model of laboratory testing, analytical assay performance can be judged on the Six Sigma scale. This not only allows benchmarking the performance of methods and instruments on a universal scale, it allows laboratories to easily visualize performance, optimize the QC rules and numbers of control measurements they implement, and now even schedule the frequency of running those controls.

Comparison between Sigma metrics in four accredited Egyptian medical laboratories in some biochemical tests: an initiative towards sigma calculation harmonization

Introduction

Analytical quality is an essential requirement for best practice in any medical laboratory. Lack of a harmonized approach for sigma calculation is considered an obstacle in the objective comparability of analytical performance among laboratories adopting sigma metrics. It is urgently needed that all laboratory professionals interested in the analytical quality to work hard towards harmonization protocol for sigma calculation in order to properly select their analytical goals. This study aims at harmonization of Sigma metrics calculation in four accredited Egyptian laboratories.

Materials and methods

This observational cross sectional study compared the sigma levels for certain biochemical parameters in the four participating laboratories.

Results

Coefficient of variation (CV) and bias were determined for some biochemical analytes, data assayed by different automated analysers in the four different accredited laboratories. The sigma level for the four medical laboratories was calculated for each biomedical parameter with changed sigma level after total allowable error (Tea) unification among participating laboratories.

Conclusion

Each laboratory should select the TEa goal based on clear standardized criteria of selection without any subjective preferences as either under or over estimation of Sigma metrics will affect the patient centred care negatively if laboratories use quality control procedures wrongly based on incorrect Sigma metrics calculation with subsequent misleading medical decisions.

Bias in analytical chemistry: A review of selected procedures for incorporating uncorrected bias into the expanded uncertainty of analytical measurements and a graphical method for evaluating the concordance of reference and test procedures

The Evaluation of measurement data - Guide to the Expression of Uncertainty in Measurement (GUM) provides the framework for evaluating measurement uncertainty. The preferred GUM approach for addressing bias assumes that all systematic errors are identified and corrected at an early stage in the measurement process. We review some procedures for treating uncorrected bias and its inclusion into an overall uncertainty statement. When bias and its uncertainty are recognised as metrological states independent of scatter in the test results, the uncertainty of the reference and uncertainty of the bias can be equated. The net standard uncertainty of a test result is the root-sum-square of the standard uncertainty of the bias and the standard uncertainty of measurements on the test. Since an incomplete and therefore potentially erroneous formula is often used for estimating bias standard uncertainty, we propose an alternative calculation. We next propose a graphical method using a simple algorithm that quantifies the discrepancy between the results of a test measurement and the corresponding reference value, in terms of the percentage overlap of two probability density functions. We propose that bias should be corrected wherever possible and we illustrate this approach using the graphical method. Even though this review is focused principally on analytical chemistry and medical laboratory applications, much of the discussion is applicable to all areas of metrology.

Biochemical screening of intellectually disabled and healthy children in Punjab, Pakistan: differences in liver function test and lipid profiles

Objectives: Inborn errors of metabolism (IEMs) are rare genetic disorders. Generally, IEMs are untreatable; however, some IEMs causing intellectual disability are potentially treatable if diagnosed earlier. In this study, levels of some clinically important biochemical parameters in intellectually disabled children suspected for IEMs were tested to see their association with intellectual disability, which could be helpful in preliminary screening. Methods: This comparative cross-sectional observational study was carried out from 2014 to 2017. Blood samples from 800 boys and girls (aged 4-24 years) were collected, of which 391 were healthy (IQ >90) and 409 were intellectually disabled (IQ <70) children with unknown cause. Clinically important (Liver and kidney enzymes etc.) biochemical parameters were analyzed in sera samples using commercial kits on semi-automated clinical chemistry analyzer. Results: Serum analysis showed the levels of ALP (p < 0.00001), ASAT (p = 0.001), ALAT (p = 0.016), albumin (p < 0.001), uric acid (p < 0.001), cholesterol (p < 0.001), triglycerides (p < 0.001), and hemoglobin (p = 0.005) were significantly different between healthy and intellectually disabled children. Conclusion: Changes in the liver function test and lipid profile parameters were significantly different in children with intellectual disability; however, it requires further detailed analysis for complete characterization of these diseases.

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.

Laboratory sample stability. Is it possible to define a consensus stability function? An example of five blood magnitudes

Background:

The stability limit of an analyte in a biological sample can be defined as the time required until a measured property acquires a bias higher than a defined specification. Many studies assessing stability and presenting recommendations of stability limits are available, but differences among them are frequent. The aim of this study was to classify and to grade a set of bibliographic studies on the stability of five common blood measurands and subsequently generate a consensus stability function.

Methods:

First, a bibliographic search was made for stability studies for five analytes in blood: alanine aminotransferase (ALT), glucose, phosphorus, potassium and prostate specific antigen (PSA). The quality of every study was evaluated using an in-house grading tool. Second, the different conditions of stability were uniformly defined and the percent deviation (PD%) over time for each analyte and condition were scattered while unifying studies with similar conditions.

Results:

From the 37 articles considered as valid, up to 130 experiments were evaluated and 629 PD% data were included (106 for ALT, 180 for glucose, 113 for phosphorus, 145 for potassium and 85 for PSA). Consensus stability equations were established for glucose, potassium, phosphorus and PSA, but not for ALT.

Conclusions:

Time is the main variable affecting stability in medical laboratory samples. Bibliographic studies differ in recommedations of stability limits mainly because of different specifications for maximum allowable error. Definition of a consensus stability function in specific conditions can help laboratories define stability limits using their own quality specifications.