Design and reporting considerations for genetic screening tests
Author and article information
Abstract
Testing asymptomatic individuals for unsuspected conditions is not new to the medical and public health communities and protocols to develop screening tests are well-established. However, the application of screening principles to inherited diseases presents unique challenges. Unlike most screening tests, the natural history and disease prevalence of most rare inherited diseases in an unselected population are unknown. It is difficult or impossible to obtain a “truth set” cohort for clinical validation studies. As a result, it is not possible to accurately calculate clinical positive and negative predictive values for “likely pathogenic” genetic variants, which are commonly returned in genetic screening assays. In addition, many of the genetic conditions included in screening panels do not have clinical confirmatory tests. All of these elements are typically required to justify the development of a screening test, according to the World Health Organization screening principles. Nevertheless, as the cost of DNA sequencing continues to fall, more individuals are opting to undergo genomic testing in the absence of a clinical indication. Despite the challenges, reasonable estimates can be deduced and used to inform test design strategies. Here, we review test design principles and apply them to genetic screening.
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2019. Design and reporting considerations for genetic screening tests. PeerJ Preprints 7:e27922v3 https://doi.org/10.7287/peerj.preprints.27922v3Author comment
Corrected Table 3. The last row was automatically rounded up from 99.99% to 100%. This version reflects the correct value of 99.99%.
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Competing Interests
Dr. Hagenkord is a shareholder in Color Genomics. Dr. Funke and Ms Qian is a shareholder in Veritas Genetics. Dr. Hegde is a shareholder in Perkin Elmer. Mr. Jacobs is a shareholder in Progenity. The remaining authors have no conflict of interest to declare.
Author Contributions
Jill Hagenkord analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Birgit Funke analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
Emily Qian analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Madhuri Hegde analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
Kevin B Jacobs analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.
Matthew Ferber analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
Matthew Lebo analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
Adam H Buchanan analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
David Bick analyzed the data, authored or reviewed drafts of the paper, approved the final draft.
Data Deposition
The following information was supplied regarding data availability:
This is a review article.
Funding
The authors received no funding for this work.
