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

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

External Quality Assessment (EQA) for SARS-CoV-2 RNA Point-of-Care Testing in Primary Healthcare Services: Analytical Performance over Seven EQA Cycles.

In April 2020, the Aboriginal and Torres Strait Islander COVID-19 Point-of-Care (POC) Testing Program was initiated to improve access to rapid molecular-based SARS-CoV-2 detection in First Nations communities. At capacity, the program reached 105 health services across Australia. An external review estimated the program contributed to averting between 23,000 and 122,000 COVID-19 infections within 40 days of the first infection in a remote community, equating to cost savings of between AU$337 million and AU$1.8 billion. Essential to the quality management of this program, a customised External Quality Assessment (EQA) program was developed with the Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP). From July 2020 to May 2022, SARS-CoV-2 EQA participation ranged from 93 to 100%. Overall concordance of valid EQA results was high (98%), with improved performance following the first survey. These results are consistent with those reported by 12 Australian and 4 New Zealand laboratories for three SARS-CoV-2 RNA EQA surveys in March 2020, demonstrating that SARS-CoV-2 RNA POC testing in primary care settings can be performed to an equivalent laboratory analytical standard. More broadly, this study highlights the value of quality management practices in real-world testing environments and the benefits of ongoing EQA program participation.

Outcome-based analytical performance specifications: current status and future challenges.

Analytical performance specifications (APS) based on outcomes refer to how 'good' the analytical performance of a test needs to be to do more good than harm to the patient. Analytical performance of a measurand affects its clinical performance. Without first setting clinical performance requirements, it is difficult to define how good analytically the test needs to be to meet medical needs. As testing is indirectly linked to health outcomes through clinical decisions on patient management, often simulation-based studies are used to assess the impact of analytical performance on the probability of clinical outcomes which is then translated to Model 1b APS according to the Milan consensus. This paper discusses the related key definitions, concepts and considerations that should assist in finding the most appropriate methods for deriving Model 1b APS. We review the advantages and limitations of published methods and discuss the criteria for transferability of Model 1b APS to different settings. We consider that the definition of the clinically acceptable misclassification rate is central to Model 1b APS. We provide some examples and guidance on a more systematic approach for first defining the clinical performance requirements for tests and we also highlight a few ideas to tackle the future challenges associated with providing outcome-based APS for laboratory testing.

Analytical performance evaluation of hemoglobin A1c on an ARKRAY HA-8160 analyzer with newly-developed mobile phase buffer.

Background: Most glycated hemoglobin A1c (HbA1c) analytical reagents used were obtained from the analyzer's manufacturer. However, clinical laboratories need more choices for HbA1c analytical reagents to overcome the limitations of dedicated reagents for special analyzers. We developed new mobile phase buffers as HbA1c diagnostic reagents and evaluated their analytical performance for the HbA1c assay. Methods: Different mobile phase buffers used as HbA1c diagnostic reagents were prepared using different concentrations of sodium salts. According to the Clinical and Laboratory Standards Institute (CLSI) recommendation guidelines, the analytical performances of the newly developed mobile phase buffers were evaluated on an ARKRAY HA-8160 Analyzer. Both quality controls and clinical blood samples were used in these experiments. To assess the quality of the newly developed mobile phase buffers, precision, accuracy, linearity, carryover, interference, bias, correlation with commercial reagents, and stability were analyzed. Results: The CVs of intra-assay precision and interassay precision of quality control and clinical.There were fewer than 1.00 % blood sample assays using the newly developed mobile phase buffer. The RDs of accuracy were less than 1.00 %. Linearity: R2 = 0.9998 in the concentration range of 4.40%-17.30 %. Carryover: 0.00 %. Reagent comparison revealed that the Pearson regression equation was Y = 0.9884x+0.05692 (R2 = 0.9977), and the Bland-Altman mean difference was -0.02650 % (CI: -0.2121 %-0.1591 %) between the two analytical reagents. Stability was also acceptable within 12 months. This mobile phase buffer showed good anti-interference ability. Conclusion: The newly developed mobile phase buffers demonstrated good analytical performance and were suitable for clinical HbA1c assays on an ARKRAY HA-8160 Analyzer.

Diagnostic performance of mpox virus (MPXV) real-time PCR assays: multicenter assessment and extended sensitivity analysis.

PURPOSE: To comprehensively investigate the diagnostic performance of routinely used assays in MPXV testing, the National Center of Clinical Laboratories in China conducted a nationwide external quality assessment (EQA) scheme and an evaluated nine assays used by ≥ 5 laboratories in the EQA. METHODS: MPXV virus-like particles with 2700, 900 and 300 copies/mL were distributed to 195 EQA laboratories. For extended analysis, triple-diluted samples from 9000 to 4.12 copies/mL were repeated 20 times using the assays employed by ≥ 5 laboratories. The diagnostic performance was assessed by analyzing EQA data and calculating the limits of detection (LODs). RESULTS: The performance was competent in 87.69% (171/195) of the participants and 87.94% (175/199) of the datasets. The positive percentage agreements (PPAs) were greater than 99% for samples at 2700 and 900 copies/mL, and 95.60% (761/796) for samples at 300 copies/mL. The calculated LODs for the two clades ranged from 228.44 to 924.31 copies/mL and were greater than the LODs specified by the respective kits. EasyDiagnosis had the lowest calculated LODs and showed superior performance in EQA, whereas BioGerm and Sansure, with higher calculated LODs, did not perform well in EQA. CONCLUSION: This study provides valuable information from the EQA data and evaluation of the diagnostic performance of MPXV detection assays. It also provided insights into reagent optimization and enabled prompt public health interventions for the outbreak.

Limitations of glycated albumin standardization when applied to the assessment of diabetes patients.

OBJECTIVES: Glycated albumin (GA) has potential value in the management of people with diabetes; however, to draw meaningful conclusions between clinical studies it is important that the GA values are comparable. This study investigates the standardization of the Norudia Glycated Albumin and Lucica Glycated Albumin-L methods. METHODS: The manufacturer reported imprecision was verified by performing CLSI-EP15-A3 protocol using manufacturer produced controls. The Japanese Clinical Chemistry Reference Material (JCCRM)611-1 was measured 20 times to evaluate the accuracy of both methods. GA was also measured in 1,167 patient samples and results were compared between the methods in mmol/mol and %. RESULTS: Maximum CV for Lucica was ≤0.6 % and for Norudia ≤1.8 % for control material. Results in mmol/mol and % of the JCCRM611-1 were within the uncertainty of the assigned values for both methods. In patient samples the relative difference in mmol/mol between the two methods ranged from -10.4 % at a GA value of 183 mmol/mol to +8.7 % at a GA value of 538 mmol/mol. However, the relative difference expressed in percentage units ranged from of 0 % at a GA value of 9.9 % to +1.7 % at a GA value of 30 %. CONCLUSIONS: The results in mmol/mol between the two methods for the patient samples were significantly different compared to the results in %. It is not clear why patient samples behave differently compared to JCCRM611-1 material. Valuable lessons can be learnt from comparing the standardization process of GA with that of HbA1c.

Applying the Milan models to setting analytical performance specifications - considering all the information.

Analytical performance specifications (APS) are used for decisions about the required analytical quality of pathology tests to meet clinical needs. The Milan models, based on clinical outcome, biological variation, or state of the art, were developed to provide a framework for setting APS. An approach has been proposed to assign each measurand to one of the models based on a defined clinical use, physiological control, or an absence of quality information about these factors. In this paper we propose that in addition to such assignment, available information from all models should be considered using a risk-based approach that considers the purpose and role of the actual test in a clinical pathway and its impact on medical decisions and clinical outcomes in addition to biological variation and the state-of-the-art. Consideration of APS already in use and the use of results in calculations may also need to be considered to determine the most appropriate APS for use in a specific setting.

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.

Reliability of the rapid antigen test for diagnosis of SARS-CoV-2 in Tunisia.

Background: Early and accurate diagnosis is crucial for preventing the spread of SARS-CoV-2 infection. The rapid antigen test was developed for testing infection, and it was necessary to assess its performance before widespread use in Tunisia. Aim: To evaluate the effectiveness of a rapid antigen test for the detection of SARS-CoV-2 in nasopharyngeal swabs in Tunisia. Methods: Nasopharyngeal samples were taken from COVID-19 suspected cases between October and December 2020 and tested using the Standard Q COVID-19 Ag test (SD-Biosensor, Republic of Korea) and real-time reverse transcription polymerase chain reaction (RT­PCR). Results: Overall, 4539 patients were tested. Of the total study population (N = 4539), 82.5% of positive samples remained positive with the rapid antigen test, while 20.2% (470/2321) of samples that were negative with rapid antigen test were confirmed positive with RT-PCR, giving a negative predictive value of 79.8% for the rapid antigen test. The sensitivity and negative predictive value of the rapid antigen test were 70.2% and 65.8%, respectively. These results improved to 96.4% and 92.8%, respectively, when considering the cycle threshold value by RT-PCR below 25. Conclusion: Although the rapid antigen test was less sensitive than RT-PCR, its ability to rapidly detect individuals with high viral loads makes it suitable for use during an epidemic.

Within- and between-subject biological variation estimates for the enumeration of lymphocyte deep immunophenotyping and monocyte subsets.

OBJECTIVES: This study aimed to deliver biological variation (BV) estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping (memory T/B cells, regulatory T cells, etc.) and classical, intermediate, and nonclassical monocyte subsets based on the full spectrum flow cytometry (FS-FCM) and a Biological Variation Data Critical Appraisal Checklist (BIVAC) design. METHODS: Samples were collected biweekly from 60 healthy Chinese adults over 10 consecutive two-week periods. Each sample was measured in duplicate within a single run for lymphocyte deep immunophenotyping and monocyte subset determination using FS-FCM, including the percentage (%) and absolute count (cells/µL). After trend adjustment, a Bayesian model was applied to deliver the within-subject BV (CVI) and between-subject BV (CVG) estimates with 95 % credibility intervals. RESULTS: Enumeration (% and cells/µL) for 25 types of lymphocyte deep immunophenotyping and three types of monocyte subset percentages showed considerable variability in terms of CVI and CVG. CVI ranged from 4.23 to 47.47 %. Additionally, CVG ranged between 10.32 and 101.30 %, except for CD4+ effector memory T cells re-expressing CD45RA. No significant differences were found between males and females for CVI and CVG estimates. Nevertheless, the CVGs of PD-1+ T cells (%) may be higher in females than males. Based on the desired analytical performance specification, the maximum allowable imprecision immune parameter was the CD8+PD-1+ T cell (cells/µL), with 23.7 %. CONCLUSIONS: This is the first study delivering BV estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping, along with classical, intermediate, and nonclassical monocyte subsets, using FS-FCM and adhering to the BIVAC design.

Analytical performance evaluation of the Mindray enzymatic assay for hemoglobin A1c measurement.

Hemoglobin A1c (HbA1c) plays a crucial role in diabetes management. We aimed to evaluate the analytical performance of a new enzymatic method kit for HbA1c measurement. The performance of the enzymatic method, including precision, accuracy, and linearity, was evaluated. Moreover, the interference effect from conventional interferents, Hb derivatives, Hb variants, and common drugs were assessed. In addition, the agreement of HbA1c results was compared between enzymatic methods, cation-exchange high-performance liquid chromatography (HPLC), and immunoassays. The intra-assay, between-assay, and total precision of HbA1c were all lower than 2%. HbA1c showed good linearity within the range of 3.96-20.23%. The enzymatic assay yielded results consistent with the external quality control samples, with a bias of less than ± 6% from the target values. The enzymatic method showed no interference from bilirubin, intralipid, vitamin C, Hb derivatives, common Hb variants, as well as antipyretic analgesics and hypoglycemic drugs. The HbA1c results of the enzymatic assay showed good agreement and accuracy compared to those obtained from the HPLC method and the immunoassay. The enzymatic method kit performed on the BS-600M chemistry analyzer is a reliable and robust method for measuring HbA1c. It is suitable for routine practice in clinical chemistry laboratories.

The role of analytical performance specifications in international guidelines and standards dealing with metrological traceability in laboratory medicine.

The goal of metrological traceability is to have equivalent results for a measurand in clinical samples (CSs) irrespective of the in-vitro diagnostic medical device (IVD-MD) used for measurements. The International Standards Organization standard 17511 defines requirements for establishing metrological traceability of values assigned to calibrators, trueness control materials and human samples used with IVD-MDs. Each step in metrological traceability has an uncertainty associated with the value assigned to a material. The uncertainty at each step adds to the uncertainty from preceding steps such that the combined uncertainty gets larger at each step. The combined uncertainty for a CS result must fulfil an analytical performance specification (APS) for the maximum allowable uncertainty (umax CS). The umax CS can be partitioned among the steps in a metrological traceability calibration hierarachy to derive the APS for maximum allowable uncertainty at each step. Similarly, the criterion for maximum acceptable noncommutability bias can be derived from the umax CS. One of the challenges in determining if umax CS is fulfilled is determining the repeatability uncertainty (u Rw) from operating an IVD-MD within a clinical laboratory. Most of the current recommendations for estimating u Rw from internal quality control data do not use a sufficiently representative time interval to capture all relevant sources of variability in measurement results. Consequently, underestimation of u Rw is common and may compromise assessment of how well current IVD-MDs and their supporting calibration hierarchies meet the needs of clinical care providers.

Using analytical performance specifications in a medical laboratory.

Analytical performance specifications (APS) are used for the quantitative assessment of assay analytical performance, with the aim of providing information appropriate for clinical care of patients. One of the major locations where APS are used is in the routine clinical laboratory. These may be used to assess and monitor assays in a range of settings including method selection, method verification or validation, external quality assurance, internal quality control and assessment of measurement uncertainty. The aspects of assays that may be assessed include imprecision, bias, selectivity, sample type, analyte stability and interferences. This paper reviews the practical use of APS in a routine clinical laboratory, using the laboratory I supervise as an example.

Prediction interval: A powerful statistical tool for monitoring patients and analytical systems.

Monitoring is indispensable for assessing disease prognosis and evaluating the effectiveness of treatment strategies, both of which rely on serial measurements of patients' data. It also plays a critical role in maintaining the stability of analytical systems, which is achieved through serial measurements of quality control samples. Accurate monitoring can be achieved through data collection, following a strict preanalytical and analytical protocol, and the application of a suitable statistical method. In a stable process, future observations can be predicted based on historical data collected during periods when the process was deemed reliable. This can be evaluated using the statistical prediction interval. Statistically, prediction interval gives an "interval" based on historical data where future measurement results can be located with a specified probability such as 95%. Prediction interval consists of two primary components: (i) the set point and (ii) the total variation around the set point which determines the upper and lower limits of the interval. Both can be calculated using the repeated measurement results obtained from the process during its steady-state. In this paper, (i) the theoretical bases of prediction intervals were outlined, and (ii) its practical application was explained through examples, aiming to facilitate the implementation of prediction intervals in laboratory medicine routine practice, as a robust tool for monitoring patients' data and analytical systems.

Simultaneous determination of inflammatory factors SAA and LTF based on stable element labeling and inductively coupled plasma mass spectrometry to aid in the diagnosis of infection.

OBJECTIVE: The clinical value of Serum amyloid A (SAA) and Lactoferrin (LTF) has received significant attention, but their detection methods are inadequate, which limits their application. This study aims to develop a dual detection method based on stable element labeling strategies and inductively coupled plasma mass spectrometry (ICP-MS) for SAA/LTF and to assess whether it can be widely used in clinical practice. METHODS: A duplex immunoassay system based on sandwich method was constructed. After optimization, methodological evaluation was performed with the guidelines of Clinical Laboratory Standards Institute (CLSI). Finally, 131 plasma samples were collected to analyze whether the new method is suitable for clinical detection. RESULTS: The LoB, LLoQ, ULoQ, and linear range of the assay were 1.09 ng/mL, 3 ng/mL, 1500 ng/mL, 3-1500 ng/mL for SAA and 0.85 ng/mL, 2 ng/mL, 1200 ng/mL, 2-1200 ng/mL for LTF respectively. The recovery rates were 95.01% to 106.26%, the intra-batch precision of low, intermediate, and high-level samples was <8%, and the inter-batch of them was <11%, the deviation of interference test results was less than±10%. The Area Under the Curve (AUC) was 0.9809 for SAA, 0.8599 for LTF, and 0.9986 for combination. CONCLUSION: The quantitative duplex immunoassay for SAA/LTF has high accuracy, good precision, and high specificity, which meets the clinical testing requirements and can be widely used in clinical practice.

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.

External quality assessment for molecular detection of Ureaplasma urealyticum in China.

BACKGROUND AND AIMS: A pilot external quality assessment (EQA) scheme for molecular detection of Ureaplasma urealyticum (UU) was conducted by the National Center for Clinical Laboratories (NCCL) to evaluate the testing capabilities of clinical laboratories and the actual performance of DNA-based nucleic acid amplification tests (NAAT) and RNA-based NAATs when applied in clinical settings. MATERIALS AND METHODS: The EQA panel contained twelve lyophilized samples, including positive samples containing inactivated cell culture supernatants of UU at different concentrations and sterile saline for negative samples. The positive samples were further divided into three groups of high, moderate and low concentrations. The panels were distributed to the participants and the datasets were analyzed according to the qualitative results. RESULTS: A total of 365 laboratories participated in the EQA scheme, and 360 results submitted by 338 laboratories were collected, of which 96.11 % (346/360) of the returned results and 95.86 % (324/338) of the laboratories were deemed competent. The positive percentage agreement (PPA) was ≥ 97.5 % for high and moderate concentration samples, but varied significantly for low concentration samples, decreasing from 86.94 % to 51.94 % as the sample concentration decreased. Additionally, for low concentration samples, RNA-based NAAT showed higher PPAs than DNA-based NAATs, but these results were specific to UU supernatants used in this study. CONCLUSION: Most of UU detection assays employed by the participants were generally consistent with their estimated limit of detection (LOD), and the majority of participants can reliably detect UU samples with high and moderate concentrations, while the poor analytical performance for low concentration samples requires further improvement and optimization.