Comparability, compatibility, equivalence and interchangeability: metrological concepts widely misunderstood in laboratory medicine
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Raúl Rigo-Bonnin
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Sofía Durán-Espín
Abstract
Background
Method-comparison studies in laboratory medicine are routinely interpreted using regression-based or Bland–Altman analyses. Although useful descriptively, these statistical procedures are frequently misapplied to infer “agreement”, “equivalence”, or “interchangeability”. Such interpretations overlook essential metrological conditions – including the definition of the measurand, the traceability chain, and measurement uncertainty – leading to misconceptions with potential clinical consequences.
Content
This Opinion Paper clarifies the distinct meanings of four metrological concepts that are often treated as synonyms: comparability, compatibility, equivalence, and interchangeability. We explain why numerical similarity or statistical association does not establish metrological relatedness, and outline the specific requirements for each concept. Comparability requires a shared measurand and calibration hierarchy; compatibility requires differences smaller than the combined uncertainty; equivalence requires clinically irrelevant residual differences; and interchangeability requires stability of clinical decisions when substituting one measuring system for another. We also discuss familiar sources of misinterpretation, including ambiguous definitions of the measurand, incomplete traceability chains, and uncritical reliance on regression- or bias-based summaries.
Summary and outlook
Distinguishing among comparability, compatibility, equivalence, and interchangeability is essential for the metrological interpretation of method-comparison studies and for ensuring safe analytical and clinical decision-making. Integrating these concepts explicitly into study design, harmonisation strategies, and reporting practice will strengthen traceability implementation, prevent erroneous claims of “agreement”, and support more reliable patient care.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: While preparing this work, the authors used Grammarly software only to check English grammar. After using this tool, the authors reviewed and edited the content as needed and took full responsibility for the publication’s content.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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