diagnostic (IVD) industry. This guidance paper aims to promote a shared understanding of the principles of clinical performance measures and study design. Measures of classification performance, also referred to as discrimination, such as sensitivity and specificity are firmly established as the primary measures for evaluating the clinical performance for screening and diagnostic tests. We explain these measures are just as relevant for other purposes of testing. We outline the importance of defining the most clinically meaningful classification of disease so the clinical benefits of testing can be explicitly inferred for those correctly classified, and harm for those incorrectly classified. We introduce the key principles and a checklist for formulating the research objective and study design to estimate clinical performance: (1) the purpose of a test e.g. diagnosis, screening, risk stratification, prognosis, prediction of treatment benefit, and corresponding research objective for assessing clinical performance; (2) the target condition for clinically meaningful classification; (3) clinical performance measures to assess whether the test is fit-for-purpose; and (4) study design types. Laboratory professionals, industry, and researchers can use this checklist to help identify relevant published studies and primary datasets, and to liaise with clinicians and methodologists when developing a study plan for evaluating clinical performance, where needed, to apply for regulatory approval.
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Lord et al. (2025) studied this question.
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