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A new version of the EFLM Biological Variation Database — the primary resource for accessing quality-assessed biological variation (BV) data — was recently released. It can be found online at https://biologicalvariation.eu and is managed by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Technical Committee for the Biological Variation Database.
The database’s 2026 iteration offers laboratory professionals and others an improved user interface and enhanced functionality. Today, users can access more than 3,250 BV datasets extracted from over 600 published studies.
Structured appraisal and meta-analysis
BV data are reference data that serve many purposes, such as defining analytical performance specifications (APS) and reference change values (RCVs). Although numerous BV studies have been published over the past 50 years, their quality varies.
For that reason, all publications in the database are evaluated using the Biological Variation Data Critical Appraisal Checklist (BIVAC) (1). This structured appraisal method, developed by the EFLM BV groups, assesses each study against 14 quality items. The BIVAC assessment appears alongside each dataset, supporting a transparent assessment of study quality.
Additionally, for each study, the BV database includes a minimum dataset that summarizes information essential for judging the applicability and transportability of BV estimates to local clinical practice.
When several BV studies with acceptable quality are identified for a measurand, the database automatically provides global BV estimates derived from meta- analyses. Currently, more than 190 meta analysis-based global point estimates with confidence intervals have been published.
Data view and automatic calculation of APS and RCV
The database’s website is intuitively structured, with three main access points: “Global BV estimates,” “All BV datasets,” and “BIVAC datasets by measurand.” When accessing the global BV estimates, users will see all measurands for which BV data are included, including all identified BV datasets and global meta- analysis results if available. This enables users to choose either the global estimate or, if relevant, study‑specific data appropriate for their patient population and the intended use of the BV data.
For measurands with meta‑analysis estimates, APS and RCVs are automatically generated. The APS calculator provides specifications for imprecision, bias, total allowable error, and measurement uncertainty (2). The RCV calculator allows users to enter their own local analytical imprecision and select a probability level to help assess the significance of change between serial patient results in the context of local analytical performance.
Background and development
The database traces its origins to the EFLM’s first Strategic Conference in Milan in 2014, during which attendees raised concerns about the reliability of available BV data. Building on the foundational work of the EFLM Committee: Biological Variation (previously, Biological Variation Working Group), experts from Europe and beyond have contributed through successive EFLM task groups and committees to address the issues that were identified (3). Their efforts have clarified quality issues in BV studies and produced tools to improve both historical assessment and future study design.
The BIVAC appraisal mentioned earlier was a major output of this work, as was the more recent Standard for Reporting Biological Variation Studies (STARBIV) (4). These tools support rigorous evaluation of existing BV literature and promote higher standards for new studies.
STARBIV is now listed on the EQUATOR Network, an international initiative dedicated to improving the quality and transparency of health research. Its inclusion — alongside links to the STARBIV mind map hosted on the Biological Variation Database website — aligns BV reporting with established standards such as the Standards for Reporting Diagnostic Accuracy Studies.
The 2026 update of the EFLM Biological Variation Database provides a comprehensive, critically assessed repository of BV data supported by robust appraisal tools. It supports safe and effective use of BV information in laboratories and enhances users’ confidence in applying BV-derived APS and RCVs to clinical decision making.
Aasne K. Aarsand, MD, PhD, is director of the Norwegian Organization for Quality Improvement of Laboratory Examinations and chairs the EFLM Technical Committee: Biological Variation Database, which is responsible for the development and curation of the EFLM Biological Variation Database. +Email: [email protected]
Craig Webster, FRCPath, is director of pathology and a consultant clinical scientist at University Hospitals Birmingham NHS Foundation Trust and leads technical, coding, and online platform development for the EFLM Biological Variation Database. +Email: [email protected]
Sverre Sandberg, MD, PhD, is a consultant at the Norwegian Quality Improvement of Laboratory Examinations and chairs the EFLM Committee: Biological Variation and the International Federation of Clinical Chemistry and Laboratory Medicine’s Committee on Point-of-Care Testing. +Email: [email protected]
References
- Aarsand AK, Røraas T, Fernandez-Calle P, et al. The biological variation data critical appraisal checklist: A standard for evaluating studies on biological variation. Clin Chem 2018; doi.org/10.1373/clinchem.2017.281808.
- Sandberg S, Coskun A, Carobene A, et al. Analytical performance specifications based on biological variation data — considerations, strengths, and limitations. Clin Chem Lab Med 2024; doi.org/10.1515/cclm-2024-0108.
- Sandberg S, Carobene A, and Aarsand AK. Biological variation — Eight years after the 1st Strategic Conference of EFLM. Clin Chem Lab Med 2022; doi.org/10.1515/cclm-2022-0086.
- Bartlett WA, Sandberg S, Carobene A, et al. A standard to report biological variation data studies — Based on an expert opinion. Clin Chem Lab Med 2024; doi.org/10.1515/cclm-2024-0489.