The Uncertainties of Clinical Next-Generation Sequencing

Many years ago, our discipline introduced the concept of “uncertainty of measurement” of clinical chemistry tests. The idea is that every generated result comes with a degree of uncertainty, depending on the accuracy of the analytical method used. Clinical chemists and clinicians must be aware of this statistical variation and interpret changes accordingly, before making diagnostic or therapeutic decisions. Including uncertainty of measurement for all performed tests has become an accreditation requirement. Now that whole-exome and whole-genome next-generation sequencing (NGS) are finding their way into the clinic, similar concerns have been raised. That is, what are the uncertainties of NGS that laboratorians, clinicians, and patients should be aware of? Knowing and managing these uncertainties are of paramount importance because wrong interpretations of NGS data could lead to consequential medical decisions. NGS is technically quite complex and is a multistep process that includes sample acquisition, preparation, analysis, generation of the report, and communication of results. Each of these steps introduces a degree of uncertainty, such as the accuracy and reliability of test results. The clinical uses of genomic testing introduce additional uncertainties, such as the benefits and harms of the genomic information; the optimal strategies for transferring this information to clinicians and patients; and the consequences of genomic testing for patients, family members, the healthcare system, and society. In a recent article in Genetics in Medicine (1), the authors provide a working definition of “uncertainty” as the conscious awareness of ignorance—a self-awareness of incomplete knowledge of some aspect. They then attempt to develop a framework of cataloging these uncertainties related to NGS in a systematic way. To obtain input for future improvements, they also opened an interactive website. The strategy for developing their taxonomy is based on expert opinion by 6 scientists/clinicians with extensive experience in clinical NGS. Here are some important caveats of this new taxonomy. Uncertainty is divided into 3 major categories: source, issue, and locus. According to the authors, “Source refers to the cause of a given uncertainty, or the fundamental reason for a specific knowledge gap. Issue refers to the substantive situation, outcome, or alternative to which a given uncertainty applies. Locus is the particular party or stakeholder in whose mind(s) a given uncertainty resides” (1). These major categories are then broken down into numerous subcategories. Many of the cited uncertainties are already well known to clinical chemists, such as methodological (preanalytical, analytical, postanalytical) and clinical/diagnostic uncertainties. The technical terms used in this highly detailed taxonomy are rather obscure to the casual reader, and their meaning is not self-evident. For this reason, the authors provide a hypothetical case report and outline the identified uncertainties from the point of view of the laboratorian, patient, and clinician. The authors suggest that the utility of their proposed systematic categorization of uncertainty in NGS is to facilitate consistency in publications and presentations about this subject. As NGS is further implemented in clinical practice, its major uncertainties must be recognized and eliminated or reduced to minimize risk and maximize patient benefit. In this respect, this paper makes an important and very relevant contribution.

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