Reimagining External Quality Assessment for precision medicine: a perspective from biochemistry laboratories
-
Stanford Chigaro
and
Maria Mvere
Abstract
External Quality Assessment (EQA) is central to quality assurance in laboratory medicine, providing independent measures of tests trueness, and inter-laboratory comparability. Traditional EQA schemes, designed around stable and well-characterised measurands, have been successful in routine analytes such as electrolytes and liver enzymes. However, the rise of precision medicine presents new challenges that extend beyond the scope of traditional EQA models. Advances in genomics, proteomics and metabolomics require quality systems capable of evaluating complex and context-specific biomarkers which may lack reference materials or established targets values. This creates a paradox: while EQA depends on standardisation, precision medicine is individualised. To remain relevant, EQA must evolve from static, one-size-fits-all models into adaptive, technology-driven, and clinically contextualised systems. In our view, the evolution of EQA must be immediate and decisive. Adaptive program design, cloud-based digital integration, AI-assisted analytics, and hybrid models provide a roadmap towards more flexible and clinically relevant systems. Together, these approaches offer a template for ensuring that EQA continues to safeguard quality while supporting innovation in personalised diagnostics.
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: Stanford Chigaro: Writing (original draft), review & editing. Maria Mvere: Review & editing. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: None declared.
-
Conflict of interest: The authors state no conflict of interest.
-
Research funding: None declared.
-
Data availability: Not applicable.
References
1. Jones, GRD, Delatour, V, Badrick, T. Metrological traceability and clinical traceability of laboratory results – the role of commutability in External Quality Assurance. Clin Chem Lab Med 2022;60:669–74. https://doi.org/10.1515/cclm-2022-0038.Search in Google Scholar PubMed
2. Buchta, C, De la Salle, B, Marrington, R, Aburto Almonacid, A, Albarède, S, Badrick, T, et al.. Behind the scenes of EQA – characteristics, capabilities, benefits and assets of External Quality Assessment (EQA): part V – benefits for stakeholders other than participants. Clin Chem Lab Med 2025;6:898–915. https://doi.org/10.1515/cclm-2024-1293. PMID: 39753240.Search in Google Scholar PubMed
3. Kim, S, Jeong, TD, Lee, K, Chung, JW, Cho, EJ, Lee, S, et al.. Quantitative evaluation of the real-world harmonization status of laboratory test items using External Quality Assessment data. Ann Lab Med 2024;44:529–36. https://doi.org/10.3343/alm.2024.0082.Search in Google Scholar PubMed PubMed Central
4. Arikat, S, Saboor, M. Evolving role of clinical laboratories in precision medicine: a narrative review. J Lab Precis Med 2024;9:17. https://doi.org/10.21037/jlpm-23-96.Search in Google Scholar
5. Singh, S, Sarma, DK, Verma, V, Nagpal, R, Kumar, M. Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders. Biochem Biophys Res Commun 2023;682:1–20. https://doi.org/10.1016/j.bbrc.2023.09.064.Search in Google Scholar PubMed
6. Cao, H, Oghenemaro, EF, Latypova, A, Abosaoda, MK, Zaman, GS, Devi, A. Advancing clinical biochemistry: addressing gaps and driving future innovations. Front Med 2025;12:1521126. https://doi.org/10.3389/fmed.2025.1521126.Search in Google Scholar PubMed PubMed Central
7. Esposito Abate, R, Cheetham, MH, Fairley, JA, Pasquale, R, Sacco, A, Nicola, W, et al.. External Quality Aassessment (EQA) for tumor mutational burden: results of an international IQN path feasibility pilot scheme. Virchows Arch 2023;482:347–55. https://doi.org/10.1007/s00428-022-03444-y.Search in Google Scholar PubMed PubMed Central
8. Kremser, M, Weiss, N, Kaufmann-Stoeck, A, Vierbaum, L, Schmitz, A, Schellenberg, I, et al.. Longitudinal evaluation of External Quality Assessment results for CA 15-3, CA 19-9, and CA 125. Front Mol Biosci 2024;11:1401619. https://doi.org/10.3389/fmolb.2024.1401619.Search in Google Scholar PubMed PubMed Central
9. Armbruster, D, Donnelly, J. Harmonization of clinical laboratory test results: the role of the IVD industry. EJIFCC 2016;27:37–47.Search in Google Scholar
10. Relling, MV, Evans, WE. Pharmacogenomics in the clinic. Nature 2015;526:343–50. https://doi.org/10.1038/nature15817.Search in Google Scholar PubMed PubMed Central
11. Wan, JCM, Massie, C, Garcia-Corbacho, J, Mouliere, F, Brenton, JD, Caldas, C, et al.. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer 2017;17:223–38. https://doi.org/10.1038/nrc.2017.7.Search in Google Scholar PubMed
12. Merker, JD, Oxnard, GR, Compton, C, Diehn, M, Hurley, P, Lazar, AJ, et al.. Circulating tumor DNA analysis in patients with cancer: American society of clinical oncology and college of American pathologists joint review. J Clin Oncol 2018;36:1631–41. https://doi.org/10.1200/JCO.2017.76.8671.Search in Google Scholar PubMed
13. Tembuyser, L, Dequeker, EMC. Endorsing good quality assurance practices in molecular pathology: risks and recommendations for diagnostic laboratories and External Quality Assessment providers. Virchows Arch 2016;468:31–41. https://doi.org/10.1007/s00428-015-1839-z.Search in Google Scholar PubMed
14. Theodorsson, E. Reference materials and reference measuring systems; 2023. https://cms.jctlm.org/wp-content/uploads/2023/02/Reference-materials-and-reference-measuring-systems-2022-03-27.pdf [Accessed: 14 September 2025].Search in Google Scholar
15. Miller, WG, Tate, JR, Barth, JH, Jones, GRD. Harmonization: the sample, the measurement, and the report. Ann Lab Med 2014;34:187–97. https://doi.org/10.3343/alm.2014.34.3.187.Search in Google Scholar PubMed PubMed Central
16. Plebani, M. Quality in laboratory medicine: 50 years on. Clin Biochem 2017;50:101–4. https://doi.org/10.1016/j.clinbiochem.2016.10.007.Search in Google Scholar PubMed
17. Ren, L, Shi, L, Zheng, Y. Reference materials for improving reliability of multiomics profiling. Phenomics 2024;4:487–521. https://doi.org/10.1007/s43657-023-00153-7.Search in Google Scholar PubMed PubMed Central
18. UK NEQAS. Interpretative comments; 2025. https://ukneqasmicro.org.uk/schemes/interpretive-comments/?utm_source=chatgpt.com [Accessed 14 September 2025].Search in Google Scholar
© 2025 Walter de Gruyter GmbH, Berlin/Boston
