Adopting solutions for annotation and reporting of next generation sequencing in clinical practice

Comparative Merits of Available Mortality Data Sources for Clinical Research

Obtaining reliable data on patient mortality is a critical challenge facing observational researchers seeking to conduct studies using real-world data. As these analyses are conducted more broadly using newly-available sources of real-world evidence, missing data can serve as a rate-limiting factor. We conducted a comparison of mortality data sources from different stakeholder perspectives - academic medical center (AMC) informatics service providers, AMC research coordinators, industry analytics professionals, and academics - to understand the strengths and limitations of differing mortality data sources: locally generated data from sites conducting research, data provided by governmental sources, and commercially available data sets. Researchers seeking to conduct observational studies using extant data should consider these factors in sourcing outcomes data for their populations of interest.

Navigating the uncertainties of next-generation sequencing in the genetics clinic

This study explores the different manifestations and navigations of uncertainty in the practice of diagnostic next-generation sequencing (NGS) testing. Drawing upon multi-sited fieldwork conducted at a large Centre for Human Genetics in Belgium, we analyse how uncertainty takes shape and is managed in the different steps of the diagnostic process: starting from the testing offer, to the analysis in the lab, the multidisciplinary team meetings (MDTs) and ending with the consultation with the patient. Building on interviews with genetic healthcare professionals and their patients and observations in consultations and MDTs, our empirical work underlines the duality of uncertainty as both burdensome and productive. Building on the existing literature on uncertainty in medicine and NGS, our analysis shows the ontological politics at play in the everyday uncertainty work in this CHG. We show how the, at times, contrasting ways of dealing with uncertainty lead to friction but also result in constructive negotiation and collaboration between actors, making use of multiple types of evidence and expertise. By not only minimising but also sustaining or inviting uncertainty, genetic healthcare professionals are able to advance the practices around NGS in a way that matches their multidisciplinary understandings, considerations and more normative stances.

From Information Overload to Actionable Insights: Digital Solutions for Interpreting Cancer Variants from Genomic Testing

Given the increase in genomic testing in routine clinical use, there is a growing need for digital technology solutions to assist pathologists, oncologists, and researchers in translating variant calls into actionable knowledge to personalize patient management plans. In this article, we discuss the challenges facing molecular geneticists and medical oncologists in working with test results from next-generation sequencing for somatic oncology, and propose key considerations for implementing a decision support software to aid the interpretation of clinically important variants. In addition, we review results from an example decision support software, NAVIFY Mutation Profiler. NAVIFY Mutation Profiler is a cloud-based software that provides curation, annotation, interpretation, and reporting of somatic variants identified by next-generation sequencing. The software reports a tiered classification based on consensus recommendations from AMP, ASCO, CAP, and ACMG. Studies with NAVIFY Mutation Profiler demonstrated that the software provided timely updates and accurate curation, as well as interpretation of variant combinations, demonstrating that decision support tools can help advance implementation of precision oncology.