A formal risk-benefit framework for genomic tests: facilitating the appropriate translation of genomics into clinical...

Evaluation of genomic tests is often challenging because of the lack of direct evidence of clinical benefit compared with usual care and unclear evidence requirements. To address these issues, this study presents a risk-benefit framework for assessing the health-related utility of genomic tests.

We incorporated approaches from a variety of established fields including decision science, outcomes research, and health technology assessment to develop the framework. Additionally, we considered genomic test stakeholder perspectives and case studies.

We developed a three-tiered framework: first, we use decision-analytic modeling techniques to synthesize data, project incidence of clinical events, and assess uncertainty. Second, we defined the health-related utility of genomic tests as improvement in health outcomes as measured by clinical event rates, life expectancy, and quality-adjusted life-years. Finally, we displayed results using a risk-benefit policy matrix to facilitate the interpretation and implementation of findings from these analyses.

A formal risk-benefit framework may accelerate the utilization and practice-based evidence development of genomic tests that pose low risk and offer plausible clinical benefit, while discouraging premature use of tests that provide little benefit or pose significant health risks compared with usual care.