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Comprehensive genomic profiling (CGP) is increasingly used as a clinical laboratory test and being applied to cancer treatment; however, standardization and external quality assessments (EQA) have not been fully developed. This study performed cost-effective EQA and proficiency tests (PT) for CGP testing among multiple institutions those belong to the EQA working group of Japan Association for Clinical Laboratory Science (JACLS). This study revealed that preanalytical processes, such as derived nucleic acids (NA) extraction from formalin fixed paraffine embedded (FFPE) samples, are critical. First, EQA with extracted DNA from cell lines showed a detection rate of 100% (9 out of 9) in KRAS (c.38G > A; p.G13D), PIK3CA (p.H1047R), and B-Raf proto-oncogene, serine/threonine kinase (BRAF) (c.1799 T > A; p.V600E) in cases of > 10% variant allele frequency (VAF). However, BRAF (c.1799 T > A; p.V600E) detection decreased to 67% (6 out of 9) for a VAF of 4.9%. Second, when DNA was extracted from FFPE samples, pathogenic variants and variants with companion diagnostic indications were detected in all 10 participating laboratories. Each variant had < 20% VAFs on average (8.1–19.1%) and wide variability among laboratories was observed (relative standard deviation, 13–60%). Nonetheless, BRAF (c.1798_1799delinsAA; p.V600K) of 8.1% VAF, EGFR (c.2235_2249del; p.E746_A750del) of 9.7% VAF, and EGFR (c.2254_2277del; p.S752_I759del) of 9.8% VAF were detected with 70% (7/10), 70% (7/10), and 60% (6/10) frequency, respectively. Therefore, 10% VAF in pre-analytic processing for DNA extraction from FFPE was critical for variant detection in CGP analysis. Further, incorrect results were reported in case independent variant calling of BRAF; c.1798_1799delinsAA (p.V600K) was mistakenly interpreted as c.1798G > A, and c.1799 T > A was on the other strand. In conclusion, the EQA/PT among 10 institutes with common samples revealed the importance of VAF in pre-analysis and helped us understand the significance of the pipeline and common pitfalls usually ignored by the internal quality control in a single institute. [ABSTRACT FROM AUTHOR]

The S-score is a new performance score applicable to proficiency testing (PT) for binary data. It allows the proficiency test provider to choose how the assigned value (AV) is defined, e.g., positive versus negative, either by the PT provider or by laboratory consensus based on participating laboratories. It is a flexible tool that can be used to select as a maximum four types of proficiency test items (PTIs) depending on the required correct results and expected correct results predefined by the PT provider. Regarding the required correct results, for an easy tasks, e.g., easy analyte detection, correct results matching with the assigned value are required for all PTI1s. For difficult tasks, e.g. close to the limit of detection (LOD) with replicated samples and for mixed tasks with unreplicated, an acceptable range of correct results is required using the binomial probability density from at least six PTI2s. Regarding correct results expected but not required for difficult tasks, results matching with the assigned value are requested by the PT provider for all PTI3s and by a participating laboratory consensus (LC) for all PTI4s. The S-score was designed as a numerical indicator taking into account all the combinations of the different types of PTIs. The decimal part summarizes the laboratory results indicating the rate of incorrect results in relation to the different PTIs assigned values. The integer part provides a similar interpretation to the one of the z-score for quantitative PT, with 'satisfactory' (1 ≤ S-score < 2), 'questionable' (2 ≤ S-score < 3), and 'unsatisfactory' (S-score ≥ 3) performance, respectively. [ABSTRACT FROM AUTHOR]

In May, 2023, the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) published the international standard ISO/IEC 17043:2023 Conformity assessment—General requirements for the competence of proficiency testing providers. This article describes the 100 % online revision process from the perspective of the Working Group (WG) members, explains the latest changes, and explores the potential impact of these changes on interested parties. [ABSTRACT FROM AUTHOR]

This paper presents the results of two proficiency testing (PT) rounds conducted by the Export Inspection Agency (EIA) Chennai laboratory in 2021 for food testing laboratories in India. The PT program was designed in accordance with ISO/TS 22117, a standard for proficiency testing in food microbiology, and targeted Listeria monocytogenes and Salmonella spp as the organisms of focus. The samples were found to be stable and recoverable during the analysis, and all PT sample packages were delivered to participant laboratories in good condition. The participant laboratories reported high sensitivity rates of 100% for PT round 061021 M and 96.49% for PT round 050721 M. The accuracy rate in PT round 061021 M was 91.89% and 92.10% in case of PT round 050721 M. However, there were some false positive and false negative results reported by some participant laboratories in both PT rounds, which may have been caused by operational errors or inconsistencies in analysis. During the PT round 061021 M, out of a total of 38 participant laboratories, five laboratories reported false positive results and one laboratory reported a false negative result. Similarly, during the PT round 050721 M, six laboratories reported false positive results which resulted in their results being deemed unsatisfactory. [ABSTRACT FROM AUTHOR]

Glucometer is the most commonly used POCT device and guides monitoring of blood glucose level in both clinical settings and outside. Inaccurate glucometer readings resulting in erroneous therapeutic intervention has critical consequences on patient care. Regulatory guidelines for performance evaluation of glucometers are not available in many countries. A robust program implemented by the hospital is essential to ensure accuracy and precision of glucometers to produce optimal results. The objective of this study was to design a quality assurance program for the evaluation of glucometers in a high volume tertiary care referral hospital and evaluate the results from July'18 to July'19. Seventy three glucometers used across the hospital were subjected to Internal Quality Control checks and Proficiency Testing performed once a month and every 3 months respectively. The results were reviewed and plotted on a Bland Altman Graph. Clarke Error Grid Analysis was done to evaluate the clinical significance of inaccuracies in the measurement of blood glucose concentration as per ISO 15197: 2013. Eight devices were identified as unacceptable by ISO standards and replaced subsequently. 96.83% and 3.17% of the values were in Zone A and B of Clarke Error Grid Analysis. The study complied with the standard which requires that 99% of the values fall within zones A and B. The review of the program after one year and its ability to identify defective glucometers has validated the efficacy of the model. The method used may be suggested as a prototype for quality management of glucometers in a clinical setting. [ABSTRACT FROM AUTHOR]

Data processing of microbial enumeration expressed as colony counts requires the use of specific statistical approaches due to the particular aspect of the analyte and the consideration of the variability related to the growth of microorganisms. A challenging matter in the organization of proficiency testing (PT) schemes for water microbiology is to provide representative, homogeneous and stable enough samples with the aim of assessing participants' performance but also characterizing the accuracy of measurement. As a consequence, the proficiency testing design may help to make clear distinction between the different sources of variation and facilitate the subsequent error analysis associated with the analytical procedures of the participants. Besides, the statistical tools may be selected to provide explicit outcomes which enable the participants to interpret the data in line with other existing indicators such as those arising from validation studies or measurement uncertainty procedures in the laboratory quality assurance system. In this paper, the suitability of a Poisson–Gamma hierarchical generalized linear model is tested in order to evaluate the interlaboratory error, the batch homogeneity and the repeatability error from water microbiology PT. A probabilistic approach deriving from the negative binomial distribution is proposed for assessing the participating laboratories performance in terms of generalized z-score. [ABSTRACT FROM AUTHOR]

The estimation of uncertainty in organic elemental analysis for C, H, N and S is reported. Both “bottom up” and “top down” strategies are used for uncertainty calculations. The bottom up approach used the results of C, H, N, and S obtained from the homogeneity study of two pure chemicals (toluene-4-sulfonamide and 4(6)-methyl-2-thiouracil). Two calibration systems, K factor and calibration curve, were applied in this study and no significant differences were obtained. For the “top down” approach, we used the data obtained from a proficiency test on both pure chemicals from among 45 Spanish laboratories. Both approaches are compared and discussed below. [ABSTRACT FROM AUTHOR]