clinicians towards appropriate clinical interventions. We may need to quantify one before we can interpret the other. The analytical data may be described

Decisions to introduce a new test are often approached by the scientific and clinical staff who have a natural interest and desire to expend the repertoire.

directly to the behaviour of the measurand in the system we are testing. There are a number of sources of such information, ranging from the well- established website (which itself aggregates much of the data found in other summaries of biological variation) to individual studies published in the literature. Its application comes with a word of caution though. Published studies, particularly for measurands performed less often, may be smaller than we would like. Results from such studies, particularly when they are the only ones available, must be interpreted in the context they were derived. Also, biological variation data invariably are generally performed in otherwise well, healthy volunteers. These data are essential to understand the underlying physiological variation of potential patients, but the complexity of studying biological variation in the diseased state means that data in that realm are lacking. When such studies are used, it is highly recommended that the source of data used for the performance specifications is clearly stated, why it was chosen and why that was deemed the most appropriate. If an assay is claimed to be at minimum, desirable or even optimal performance, that must be shown to be referencing a robust source of data to make the claim appropriate. Finally comes clinical outcome data – subdivided as either direct or indirect. Direct clinical outcome data are notoriously difficult to obtain, particularly for the less-common measurands. The data must also be critically appraised as being appropriate. The scarcity of direct clinical outcome data has led to the need for indirect measures of clinical outcome. One such method is the allowable


misclassification rate. This has been implemented with cardiac troponin in recent times. This quantifies misclassification error using duplicate measurements of the measurand. Patient clinical outcome (treatment pathway followed) is classified based on each replicate. If there is a difference, the impact is directly attributable to assay imprecision. In this specific case, the false-positive rate can be limited to 1% if the troponin assay bias and imprecision is kept below 10%. It is this that can be used as a performance specification for assays under test to achieve.

Screening, diagnosis, treatment and monitoring Assays can be used for any or all of the above purposes. The clinical requirements of the assay may differ depending on the clinical context. Some assays are established as screening tests, others are more specifically used for diagnosis, and yet others are used only for monitoring treatment such as drug therapies. Indirect clinical outcome data incorporate both analytical and clinical criteria. The clinical application may be different between, and even within, assays. So what is the difference?

Analytic performance is the ability of the assay to measure the analyte of interest. Clinical performance is the ability of the assay to use that measurement to make a distinction between different disease states of an individual, or to guide

by imprecision, reproducibility, linearity among others. Terms such as sensitivity and specificity particularly have been at the forefront of our minds, and that of the general public, due to SARS-CoV-2 and COVID-19, and relate to clinical performance. Less well publicised, but just as important, are predictive values (both positive and negative) and ratios (such as likelihood and odds ratios). So, what should we consider first? Experiments to investigate analytical performance of assays should be performed first. The results of these experiments will inform our interpretation of diagnostic accuracy. Established assays permit interpretation of the diagnostic accuracy from analytical performance.

Ensure consistency with manufacturers’ claims What is expected? Manufacturers are required to use a continual assessment process to evidence both the analytical and clinical validity of assays. The end goal of that assessment is to provide the performance evaluation to users of the assays as a baseline performance expectation. The in vitro diagnostic regulations (IVDR) replace previous EU legislation (97/79/EC) governing in vitro diagnostic devices. This came into place in May 2017. Manufacturers must provide more extensive and rigorous clinical evidence for their assays. These will include clinical performance studies which in themselves are extremely useful for the laboratory when finalising performance specifications for method comparisons. The documentation provided must also be more extensive and the details of such studies should be made available to the laboratories.

How do we use manufacturer specifications?

Laboratories should be able to reproduce (or better) the minimum quality requirement provided in the manufacturer documentation. However, we accept this is a starting point and should be viewed as a minimum. Verification studies including imprecision, reproducibility, bias assessment, calibration, traceability, and recovery experiments also provide

Manufacturers are required to use a continual assessment process to evidence both the analytical and clinical validity of assays


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