Risk Benefit Framework for Genetic Tests
Project Funding and Leadership Information
Project Title: Risk-Benefit Framework for Genetic Tests
Funding: Centers for Disease Control (CDC) Office of Genomics and Disease Prevention
Grant number: U18 GD000005
- David Veenstra, PharmD, PhD, Director, Graduate Studies and Postdoctoral Fellowship Programs in Pharmacoeconomics; Associate Professor, Department of Pharmacy, University of Washington
- Louis Garrison, PhD; Professor, Department of Pharmacy; Associate Director, Pharmaceutical Outcomes Research & Policy Program, University of Washington
- Wylie Burke, MD, PhD; Chair, Department of Bioethics and Humanities; Professor, Department of Bioethics and Humanities; Adjunct Professor, Department of Epidemiology, University of Washington
- Karen Edwards, PhD, Associate Professor; Department of Epidemiology, University of Washington
- Scott Ramsey, MD, PhD; Adjunct Professor, Department of Medicine & Department of Pharmacy, University of Washington; Director, Cancer Outcomes Research Program, Fred Hutchinson Cancer Research Cente
Rationale for the Genetic Test Risk-Benefit Analysis Project
The rapid technological advances in genetic analysis over the past decade present a significant, yet challenging, opportunity to improve the public’s health through genomics. Most often the clinical utility of a genetic test is not well known or understood at the time of its
availability to patients. Because of the plethora of genetic information being generated, and the significant time and resources required to generate randomized controlled trial-level evidence, the paucity of data will be an ongoing issue. Perhaps as challenging, the evidence criteria for genetic tests and the approaches for evaluating their clinical utility are unclear, complicating the translational pathway for genomic technologies.
A key to accelerating the appropriate integration of genomic applications into healthcare in the coming decades will be the ability to assess the tradeoffs between clinical benefits and clinical risks of genetic tests in a timely manner. Traditional evidence-based methods that rely on direct evidence will have limited usefulness due to the lack of data. Approaches for incorporating indirect evidence in the evaluation of preventive services have been developed, but they lack a summary measure of net benefit and formal assessment of uncertainty. Although decision-analytic techniques are beginning to be used to explore the clinical utility of genetic tests, a framework for incorporating their findings into decision making in a manner that consistently meets stakeholders’ needs has not been developed.
Recently, there has been significant interest in the use of formal risk-benefit analysis in regulatory decision making for drugs and biologics. One such approach uses disease-based health outcomes modeling to incorporate clinical, epidemiological, and patient preference data to project the effect of an intervention on the incidence of clinical events, and the probabilistic range of likely outcomes. We propose this approach will be particularly useful for assessing genetic tests intended to influence health outcomes, and communicating the potential clinical benefits, harms, and uncertainty to providers and policy makers. A formal risk-benefit
framework would serve as an adjunct to current evaluation processes, and facilitate the prioritization of genetic tests into several potential categories such as:
- Likely benefit and low risk appropriate for clinical use
- Unclear benefit but low risk appropriate for practice-based evidence-development
- Low likelihood of benefit or serious risk requiring further research
Specific Aims of the Risk-Benefit Framework for Genetic Tests
The overall goal of this project is to develop a formal clinical risk-benefit framework to facilitate the translational pathway for genomic technologies using three case studies, specifically:
- Develop a quantitative risk-benefit framework for evaluating the clinical utility of genetic tests in collaboration with stakeholder groups, utilizing warfarin pharmacogenomics as a case example
- Assess the generalizability of the framework by applying it to two additional case studies:
a) Gene expression profiling in women with early stage breast cancer, and
b) Factor V Leiden testing for pregnant women with clotting or adverse pregnancy outcomes
- Evaluate and optimize the utility of the risk-benefit framework via a consensus development process with stakeholder groups.
Specific case study webpages.
Please direct project correspondence to David Veenstra, PharmD, PhD (Primary Investigator): email@example.com
or Joshua Roth, MHA (Research Assistant): firstname.lastname@example.org
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Copyright 2009 University of Washington