Knowledge integration at the center of genomic medicine

Rapid discoveries in genomics and other “omic” fields are creating expectations that new tests and interventions will be developed for use in clinical practice and disease prevention.1 Cancer has been at the forefront of clinical applications of these technologies, which offer the potential to use germ-line and tumor genomic data to develop personalized interventions.2 Despite this promise, the information needed to move applications into clinical practice is often scarce and stakeholders sometimes disagree on how much evidence is needed.3 In this issue of Genetics in Medicine, three articles tackle the complexities of gathering, evaluating, and disseminating the evidence on genomic tests. Two articles stem from a National Cancer Institute initiative on comparative effective research in cancer genomics and personalized medicine.4 Comparative effective research arose as a result of increased interest in measuring patient-centered health outcomes and comparing alternative approaches to disease prevention and treatment.5 Genomic medicine provides an ideal opportunity to apply comparative effective research methods to compare genomic tools and applications with usual care in real-world settings.6 In the first article, Goddard et al.7 identify approaches to assessing genomic applications through literature reviews and demonstrate lessons learned from the National Cancer Institute initiative. Using case studies, they identify significant challenges in the conduct and evaluation of comparative effective research, including the rapid pace of innovation and data acquisition, lack of oversight, and variable evidentiary thresholds for clinical and personal utility. They conclude that a variety of methodological approaches are needed to develop and synthesize the knowledge needed to ensure an effective translation of genomic discoveries in cancer. These approaches include a combination of comparative observational studies and randomized trials, as well as decision modeling and economic analysis of patient-centered outcomes. In the second article, Deverka et al.8 explore how stakeholders view knowledge about genomic applications in cancer. Stakeholders include clinicians, insurers, test developers, advocates, policy makers, and others whose views can influence translation from research to practice. Using case studies, the authors present results of evidence synthesis to 22 diverse stakeholders who participated in a workshop to explore the evidence of cancer genomic tests for clinical practice and coverage decision-making. Describing how the stakeholders’ opinions on evidentiary thresholds diverged and changed during the workshop, the authors highlight the need for ongoing stakeholder engagement in unbiased settings. A common understanding of the existing evidence base should guide the development of evidentiary thresholds in genomic medicine. In the third article, Wallace et al.9 explore a new way to rapidly update the evidence base on genomic applications in practice. Systematic reviews and meta-analyses, the principal tools for evidence synthesis, are labor intensive and time consuming; thus, the volume and rapid evolution of information in genomic medicine presents a substantial challenge. The authors demonstrate an approach to mining curated, online knowledge bases that can reduce the burden of updating systematic reviews. Their findings provide important impetus for the development and deployment of modern approaches based on text or data mining and other technologies to reduce the labor necessary to produce and maintain systematic reviews in the rapidly developing field of genomic medicine.