Is this test fit-for-purpose? Principles and a checklist for evaluating the clinical performance of a test in the new era of diagnostic (IVD) regulation.

Recent changes in the regulatory assessment of medical tests reflect a growing recognition of the need for more stringent clinical evidence requirements to protect patient safety and health. Under current regulations in the United States and Europe, when needed for regulatory approval, clinical performance reports must provide clinical evidence tailored to the intended purpose of the test and allow assessment of whether the test will achieve the intended clinical benefit. The quality of evidence must be proportionate to the risk for the patient and/or public health. These requirements now cover both commercial and laboratory developed tests (LDT) and demand a sound understanding of the fundamentals of clinical performance measures and study design to develop and appraise the study plan and interpret the study results. However, there is a lack of harmonized guidance for the laboratory profession, industry, regulatory agencies and notified bodies on how the clinical performance of tests should be measured. The Working Group on Test Evaluation (WG-TE) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) is a multidisciplinary group of laboratory professionals, clinical epidemiologists, health technology assessment experts, and representatives of the 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.