One hundred years after its first description, major advances in laboratory science and genetics have transformed the diagnosis and clinical characterization of von Willebrand disease (VWD). This review provides an updated overview of diagnostic approaches to VWD, with emphasis on countries with limited resources, the growing role of next-generation sequencing (NGS), and insights gained from external quality assessment (EQA) programs. First, we discuss recent developments in diagnostic testing for VWD, including the use of standardised automated assays and structured bleeding assessment tools that enhance diagnostic accuracy and reproducibility. We also propose simplified diagnostic algorithms suited to resource-limited settings, where access to specialised assays remains restricted. Second, we examine the impact of NGS on VWD diagnostics, which enables comprehensive sequencing of the large and complex VWF gene, supports subtype classification, and distinguishes VWD from phenotypically similar disorders such as platelet-type VWD and mild haemophilia A. The ongoing challenges of variant interpretation and incomplete genotype-phenotype correlation are also addressed. Finally, we summarise evidence from international EQA programs showing improved assay precision and diagnostic concordance but highlighting residual variability in laboratory interpretation and testing availability. Together, these developments illustrate a century of progress in the understanding and diagnosis of VWD, underscoring the importance of global harmonization, quality assurance and equitable access to advanced diagnostic tools.

Pneumatic transportation systems (PTS) are used for sample transportation to ensure faster turn-around-times. This transportation form can however cause preanalytical changes in the samples, especially haemolysis, and it must therefore be controlled and surveyed. In order to elucidate the use and quality control (QC) of PTS in the Nordic countries, a survey was conducted in 2018 and 2024. A questionnaire was constructed using Webropol based on the CLSI document H18-A4 on handling and processing of blood specimens. It was distributed electronically in 2018 to all Nordic biochemistry laboratories through the National societies of clinical biochemistry. Due to Covid-19, the results were unfortunately not handled timely, and a follow-up questionnaire was therefore distributed in 2024. In 2018, 85 laboratories replied, while 30 laboratories replied in 2024. In 2018, 24% of the transportation lines ended either directly on the analysis track or in a bulk sorter connected to the track, while in 2024, 59% ended directly on the analysis track. In 2018, 69% had validated their PTS, mostly using haemolysis index (32%), while in 2024, 88% had validated their PTS with 87% using haemolysis index. In 2024, only 10% used internal QC for their PTS, while just 24% had entered an external quality assessment program, which was unavailable in 2018. Despite a promising development in PTS validation and quality control, several necessary actions are needed when samples are delivered via PTS. The Nordic preanalytical scientific working group has listed recommendations that should be adopted to ensure sample quality.

This article explores the use of artificial intelligence in higher education external quality assessment. Specifically, the study demonstrates the feasibility and accuracy of predicting potential non-full compliance (defined as quality risk) in the quality assessment of higher education degree programmes. Using data from the Catalan University Quality Assurance Agency (Catalonia, Spain) covering the period 2015–2023, the study applies machine learning techniques to identify hidden patterns between 74 quality indicators and the accreditation outcomes of 1.416 degree programme evaluations. This research provides an innovative perspective to optimise and complement institutional assessment processes that are widely established at the international level.

A comprehensive ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed for the simultaneous quantification of 50 pesticide biomarkers across nine current-use chemical classes in human urine. These classes include organophosphorus insecticides (which encompass dialkyl phosphates and specific metabolites), pyrethroid insecticides, fungicides, neonicotinoid insecticides, herbicides, insect repellents, organochlorine pesticide metabolites, and plant growth regulators. The method employs solid-phase extraction (SPE) for sample preparation, requiring only 0.2 mL of urine. Chromatographic separation was optimized using a Hypersil Gold AQ column, achieving a total run time of 18 min. Mass spectrometric detection utilized polarity switching in electrospray ionization mode with multiple reaction monitoring. Method validation demonstrated satisfactory linearity (R2 > 0.99), high sensitivity with limits of detection ranging from 0.01 to 0.88 ng/mL, and extraction efficiencies between 85% and 113%. Precision and accuracy were within acceptable ranges, with relative standard deviations generally below 15%. The method's robustness was confirmed through participation in external quality assessment schemes. Application to real samples revealed significant inter-individual variability in pesticide biomarker concentrations, with total measured biomarker levels ranging from 89 to 1242 ng/mL across the 10 individuals analyzed. This method offers comprehensive coverage of current-use pesticide chemical classes, including 30 biomarkers from the U.S. National Health and Nutrition Examination Survey (NHANES) biomonitoring program, and demonstrates improved sensitivity and broader analyte coverage compared to existing methods. The developed assay provides a valuable tool for large-scale biomonitoring studies and environmental health research.

Quality of tuberculosis diagnostic laboratories in Ethiopia assessed through External Quality Assessment components: a systematic review.

3-Epimer-25-hydroxyvitamin D3 interference in assays for the measurement of 25-hydroxyvitamin D3.

ObjectivesThe increasing prevalence of antimicrobial resistance (AMR) in Escherichia coli, notably those producing AmpC, ESBL and carbapenemases among food-producing animals, poses a significant public health threat, especially in low- and middle-income countries. With support from the Fleming Fund and in alignment with the WHO, FAO and WOAH tripartite Tricycle project, the EQASIA Matrix External Quality Assessment (EQA) scheme aimed at evaluating laboratories’ proficiency from different One Health (OH) sectors in detecting resistant E. coli from food-like matrices in South and South-East Asia.MethodsBetween 2021 and 2024, four Matrix EQA rounds were implemented across OH sectors. Each round involved four lyophilized simulated meat samples spiked with well-characterized E. coli strains expressing β-lactam resistance phenotypes. Participating laboratories performed selective isolation, species identification, antimicrobial susceptibility testing (AST) and phenotypic classification using routine methods. Results were submitted via a secure online platform and evaluated against expected outcomes, using CLSI-based interpretive criteria and a standardized error categorization system.ResultsTwenty-one laboratories from 10 countries participated across the four rounds. Accuracy in E. coli identification declined from 75% in 2021 to 23.1% in 2024. Only one laboratory achieved full identification accuracy in any round. AST performance showed inter-laboratory variation, with deviation rates ranging from 0.5% to 41%. Misclassification of resistance phenotypes, particularly AmpC and combined ESBL + AmpC, was common. Quality control testing improved modestly over time but remained incomplete.ConclusionsThe Matrix EQA revealed critical insights into regional laboratory capacity and highlighted persistent technical gaps in detecting complex resistance mechanisms from food matrices. With the conclusion of the Fleming Fund, maintaining these gains will require sustained national investment, EQA integration into AMR strategies and continued regional coordination to support Tricycle-aligned surveillance.

Since 2022, highly pathogenic H5N1 influenza A virus clade 2.3.4.4b has caused global outbreaks among wild birds and poultry, with increasing mammalian and sporadic human infections. This elevates concerns about zoonotic transmission and pandemic risk, highlighting the need for accurate detection and identification of animal influenza A viruses by human clinical diagnostic laboratories (hCDL). To evaluate routine diagnostic performance, an External Quality Assessment (EQA) panel containing inactivated influenza A viruses of avian (three subtype H5, one H7), swine (two H1, one H3), and human (one H1pdm09, one H3) origin was distributed to 50 hCDL in the Netherlands, Aruba, Bonaire, and Curaçao. Laboratories conducted their routine molecular influenza virus detection and, if available, subtyping workflows. A total of 118 detection workflows were reported. Of these, 109 (91 %) successfully detected influenza A virus in all positive specimens. At least one workflow in 49/50 (98 %) laboratories reliably detected all animal influenza viruses as type A influenza virus. Most false negatives occurred with swine H1N1v. Only 24 workflows from 20 laboratories attempted subtyping for one or multiple panel specimens (total 109 subtype-specific results reported): for human viruses, 37/39 results were correct; for avian viruses, 13/14 were correct (including 12/12 for H5); for swine viruses, only 2/56 were correct (both swine H3N2 using broad-reactive H3 assays). hCDL in the Netherlands demonstrate high performance for detecting animal influenza A viruses. However, subtyping capacity is limited, necessitating referral of specimens of suspected zoonotic influenza cases to the National Influenza Centre for further characterization.

Circulating tumour DNA (ctDNA) assays are increasingly applied in haematological malignancies for non-invasive genotyping, quantitative response assessment, measurable residual disease (MRD) detection, and relapse surveillance, often complementing bone marrow-based testing and, in selected scenarios, potentially reducing its frequency. Yet, translating ctDNA results into comparable clinical decisions across laboratories, platforms, and time remains challenging because ctDNA measurements are influenced by the definition of the measurand (for example, variant allele fraction versus mutant molecules per mL), pre-analytical variables, end-to-end workflow losses, and lineage-specific confounders such as clonal haematopoiesis of indeterminate potential (CHIP), therapy-related clonal haematopoiesis, and compartmental disease (marrow, plasma, cerebrospinal fluid, extramedullary sites). This review proposes a harmonisation framework for haematological ctDNA based on three linked concepts-metrological traceability, which connects reported values to reference systems with stated uncertainty, commutability, which ensures that reference materials behave like patient specimens across diverse workflows and fit-for-purpose reference materials that support calibration, and quality control, external quality assessment, and cut-off setting for intended uses such as early molecular response in large B-cell lymphoma, molecular MRD in acute myeloid leukaemia, and deep response monitoring in multiple myeloma. This framework is accompanied by harmonised CHIP-aware reporting rules for settings without matched cellular DNA and practical change-control/bridging strategies to preserve clinical decision thresholds when platforms or bioinformatic pipelines evolve.

Clinical laboratories face stringent privacy constraints, limited datasets for rare conditions, and rising demands to validate AI algorithms and workflows safely. Synthetic data-artificially generated data that preserve the statistical characteristics of real clinical data without exposing patient identities-has emerged as a powerful tool to address these challenges. This review provides a comprehensive overview of synthetic data in the context of laboratory medicine. We begin by defining synthetic data and describing the main generation methods, from rule-based simulations to modern generative models (including generative adversarial networks, variational autoencoders, and diffusion models) with examples of their use in healthcare. We then delve into key applications in the clinical laboratory: quality control and method validation, education and training, machine learning development, test utilization and workflow simulation, and external quality assessment. Advantages of synthetic data-such as enhanced privacy, scalability, flexibility in simulating rare events, and cost-effectiveness-are discussed with illustrative case studies. We also examine challenges and limitations, including concerns about data fidelity, bias amplification, risks of model overfitting or re-identification attacks, and the cautious stance of regulators that still require real patient data for approvals. Finally, we outline future directions for synthetic data in laboratory medicine, from hybrid real-synthetic datasets and privacy-enhancing techniques to evolving regulatory frameworks and the potential to democratize data access globally. While synthetic data cannot entirely replace real clinical data-especially for regulatory validation-it can significantly augment what laboratories can design, test, and achieve, provided it is used with careful validation and ethical safeguards.

Clostridioides difficile laboratory testing algorithms and performance: a review of the Royal College of Pathologists of Australasia Quality Assurance Programs external quality assessments for C. difficile.

Smoking-dependent circulating non-coding biomarkers in lung cancer.

Multi-omic biomarker detection in UV-induced melanoma.

Background: (1,3)--D-Glucan (BDG) is an adjunctive biomarker for invasive fungal infections, but its analytical variability and lack of external quality assessment (EQA) programs limit assay reliability.This study evaluated BDG stability under practical storage conditions and explored the feasibility of a split-sample procedure as an alternative quality-assurance approach.Methods: The reliability of BDG assay results was assessed through three experiments addressing pre-analytical handling, storage stability, and interlaboratory comparability.To examine the effect of freeze-thaw stress, samples with low, moderate, and high BDG concentrations were repeatedly frozen and thawed.Short-term stability was then evaluated using pooled samples at near-cutoff, weak-positive, and strong-positive levels stored at different temperatures for up to 72 hours, with triplicate testing at predefined intervals.In addition, seven serum samples were aliquoted and analyzed in parallel at two institutions to assess interlaboratory agreement.Results: Repeated freeze-thaw cycles resulted in a marked reduction in BDG concentrations, whereas values remained largely stable for up to 72 hours under both refrigerated and frozen storage.Variability was the greatest near the assay cutoff.Interlaboratory comparison showed acceptable agreement in six of seven samples, with one discrepant result likely attributable to specimen-specific or handling-related factors.Conclusions: BDG assays remain stable under short-term refrigerated or frozen storage but are susceptible to repeated freeze-thaw cycles and variability near the cutoff range.The split-sample procedure offers a practical interim approach when EQA is unavailable and may serve as a foundation for standardized quality-assurance frameworks for BDG testing.

Digital PCR as a potential reference measurement procedure to support monkeypox virus/Orthopoxvirus external quality assessment schemes.

Malaria still poses a public health burden in India despite ongoing elimination efforts. Blood donor screening for malaria is mandated in India, yet data on transfusion-transmitted malaria (TTM) are lacking. We sought to evaluate testing practices for malaria, associated rates of positivity in donors and reported cases of TTM in India. We conducted a cross-sectional survey of blood collection facilities in India from May to September 2025. Facilities were recruited through professional networks and direct outreach; responses were de-identified. Data were collected on screening practices, malaria endemicity, quality control measures and TTM cases from 2020 to 2024. Among 262 facilities, 256 (97.7%) reported routine malaria screening of all donations, most commonly using antigen rapid diagnostic tests (RDTs) (228/256, 89.1%). From 2020 to 2024, facilities tested 9,275,688 donations, with 1231 confirmed positive donations (overall 13.27 per 100,000 units) and a rising annual positivity rate from 3.4 to 22.0 per 100,000 units. Only eight facilities (3.1%) reported TTM cases, and less than half of facilities (116/256, 45.3%) participated in external quality assessment (EQA) and/or performed lookback investigations (88/262, 33.6%). In this national survey sample in India, almost all facilities reported routine malaria screening of blood donations, mostly using RDT. The findings suggest that rates of donor positivity may have increased, yet TTM is under-recognized and/or unreported. Strengthening EQA and haemovigilance, particularly in malaria endemic regions, is needed to safeguard the blood supply, particularly as India strives towards malaria elimination.

Background/Objectives: Allopurinol, a first-line drug for gout and hyperuricemia, carries a risk of severe cutaneous adverse reactions (SCARs). Studies have established a strong association between HLA-B*58:01 and this adverse reaction. Although pre-treatment genotyping is recommended, the reliability of HLA-B*58:01 genetic testing varies across laboratories. This study aims to assess the performance of HLA-B*58:01 genetic testing of clinical laboratories in Shanghai through an External Quality Assessment (EQA) program, evaluating accuracy and standardization. Methods: The EQA program was carried out twice a year in 2023 and 2024. Each EQA sample panel consisted of five distinct samples, including HLA-B*58:01 allele-positive and -negative cell cultures. Sample panels were distributed to clinical laboratories through the cold chain system and results were analyzed and scored. Results: EQA samples used in this study were optimized for evaluating current HLA-B*58:01 genotyping assays, and the EQA samples were proved to be homogeneous and stable through each EQA period. In 2023, 17 and 16 clinical laboratories participated in the two EQA schemes; in 2024, 34 and 33 laboratories participated. A total of 14/17 (82.4%), 16/16 (100%), 33/34 (97.1%), and 33/33 (100%) laboratories achieved "optimal" scores. Conclusions: EQA results indicate that most of clinical laboratories in Shanghai exhibit constantly satisfactory performance for HLA-B*58:01 genotyping. However, a few laboratories still need further improvement. Additionally, EQA has demonstrated to be an important method for monitoring clinical laboratories' performance.

Research to build a process for production and testing ofstable dry blood sample HbA1capplication in external quality assessment

A DEQAS review of the current performance of assays for the measurement of 1,25dihydroxyvitamin D.

The TP53 gene is the most frequently mutated gene in human cancers, with alterations occurring in ∼50% of all malignancies. When properly optimized, p53 immunohistochemistry (IHC) can serve as a reliable surrogate for detecting TP53 mutations. However, many laboratories struggle to identify p53 IHC reaction patterns beyond overexpression, particularly the absence, cytoplasmic, and wild-type patterns. As the clinical relevance of these additional patterns became recognized, NordiQC updated its assessment in 2021 to include wild-type and absence patterns, thereby increasing the complexity of p53 IHC and revealing widespread difficulties across laboratories. In this study, we analyze data from 6 consecutive NordiQC external quality assessment rounds from 2007 to 2024, covering 1,796 submitted p53 IHC assays. Our findings show that while most laboratories can reliably detect high antigen expression of overexpression, many protocols fail to adequately demonstrate low-level p53 expression, limiting the validity of the IHC assay. Ready-To-Use products, particularly when used according to manufacturer recommendations, performed suboptimally. These kits are calibrated exclusively to detect overexpression, leading to false-negative or too-weak results for other mutation-associated patterns. Our data represents the most comprehensive evaluation of p53 IHC assay performance to date. The findings underscore an urgent need to recalibrate p53 IHC protocols, with a special focus on improving analytical sensitivity and ensuring consistent use of both internal and external controls. Aligning IHC assays calibrated to identify the full spectrum of TP53 mutations, including those that result in absent and wild-type patterns, can significantly enhance the diagnostic accuracy of p53 IHC.