Gurvaneet Randhawa

Comparative effectiveness research and genomic medicine: An evolving partnership for 21st century medicine

The American Recovery and Reinvestment Act has provided resources for comparative effectiveness research that will lead to evidence-based decisions about health and health care choices. Some have voiced concerns that evidence-based comparative effectiveness research principles are only relevant to “average” patients and not as much to individuals with unique combinations of genes, exposures and disease outcomes, intrinsic to genomic medicine. In this commentary, we argue that comparative effectiveness research and genomic medicine not only can and should coexist but also they will increasingly benefit from each other. The promise and success of genomic medicine will depend on rigorous comparative effectiveness research to compare outcomes for genome-based applications in practice to traditional non–genome-based approaches. In addition, the success of comparative effectiveness research will depend on developing new methods and clinical research infrastructures to integrate genome-based personalized perspectives into point of care decisions by patients and providers. There is a need to heal the apparent schism between genomic medicine and comparative effectiveness research to enhance knowledge-driven practice of medicine in the 21st century.

The Genomic Applications in Practice and Prevention Network

The authors describe the rationale and initial development of a new collaborative initiative, the Genomic Applications in Practice and Prevention Network. The network convened by the Centers for Disease Control and Prevention and the National Institutes of Health includes multiple stakeholders from academia, government, health care, public health, industry and consumers. The premise of Genomic Applications in Practice and Prevention Network is that there is an unaddressed chasm between gene discoveries and demonstration of their clinical validity and utility. This chasm is due to the lack of readily accessible information about the utility of most genomic applications and the lack of necessary knowledge by consumers and providers to implement what is known. The mission of Genomic Applications in Practice and Prevention Network is to accelerate and streamline the effective integration of validated genomic knowledge into the practice of medicine and public health, by empowering and sponsoring research, evaluating research findings, and disseminating high quality information on candidate genomic applications in practice and prevention. Genomic Applications in Practice and Prevention Network will develop a process that links ongoing collection of information on candidate genomic applications to four crucial domains: (1) knowledge synthesis and dissemination for new and existing technologies, and the identification of knowledge gaps, (2) a robust evidence-based recommendation development process, (3) translation research to evaluate validity, utility and impact in the real world and how to disseminate and implement recommended genomic applications, and (4) programs to enhance practice, education, and surveillance.

Cancer Pharmacogenomics and Pharmacoepidemiology: Setting a Research Agenda to Accelerate Translation

Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled “Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation” on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.

Observational studies in systemic reviews of comparative effectiveness: AHRQ and the Effective Health Care Program

OBJECTIVE Systematic reviewers disagree about the ability of observational studies to answer questions about the benefits or intended effects of pharmacotherapeutic, device, or procedural interventions. This study provides a framework for decision making on the inclusion of observational studies to assess benefits and intended effects in comparative effectiveness reviews (CERs). STUDY DESIGN AND SETTING The conceptual model and recommendations were developed using a consensus process by members of the methods workgroup of the Effective Health Care Program of the Agency for Healthcare Research and Quality. RESULTS In considering whether to use observational studies in CERs for addressing beneficial effects, reviewers should answer two questions: (1) Are there gaps in the evidence from randomized controlled trials (RCTs)? (2) Will observational studies provide valid and useful information? The latter question involves the following: (a) refocusing the study questions on gaps in the evidence from RCTs, (b) assessing the risk of bias of the body of evidence of observational studies, and (c) assessing whether available observational studies address the gap review questions. CONCLUSIONS Because it is unusual to find sufficient evidence from RCTs to answer all key questions concerning benefit or the balance of benefits and harms, comparative effectiveness reviewers should routinely assess the appropriateness of inclusion of observational studies for questions of benefit. Furthermore, reviewers should explicitly state the rationale for inclusion or exclusion of observational studies when conducting CERs.

Characterizing genetic variants for clinical action

Genome‐wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome‐scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop.

Payer perspectives on pharmacogenomics testing and drug development

A series of questions about hypothetical drugs and pharmacogenomic tests was posed to a panel of representatives from the health plan, government and employer sectors in order to elicit suggestions for input on data or study design considerations important for coverage determination. The panel suggested seven areas for drug developers to strongly consider. These areas were to include comparative information on new tests versus usual care, assess the negative predictive value of new tests, measure and report on cost offsets, balance relative risk improvement with absolute risk, consider the policy implications of the products or tests, report percentage responders in addition to group mean improvements, and to include specific pharmacogenomic information in US FDA approved labels. The panel was generally enthusiastic about the promise of the field to improve drug selection or dosing.

A Health Services Research Agenda for Cellular, Molecular and Genomic Technologies in Cancer Care

Background: In recent decades, extensive resources have been invested to develop cellular, molecular and genomic technologies with clinical applications that span the continuum of cancer care. Methods: In December 2006, the National Cancer Institute sponsored the first workshop to uniquely examine the state of health services research on cancer-related cellular, molecular and genomic technologies and identify challenges and priorities for expanding the evidence base on their effectiveness in routine care. Results: This article summarizes the workshop outcomes, which included development of a comprehensive research agenda that incorporates health and safety endpoints, utilization patterns, patient and provider preferences, quality of care and access, disparities, economics and decision modeling, trends in cancer outcomes, and health-related quality of life among target populations. Conclusions: Ultimately, the successful adoption of useful technologies will depend on understanding and influencing the patient, provider, health care system and societal factors that contribute to their uptake and effectiveness in ‘real-world’ settings.

Sustainability Considerations for Health Research and Analytic Data Infrastructures

Introduction: The United States has made recent large investments in creating data infrastructures to support the important goals of patient-centered outcomes research (PCOR) and comparative effectiveness research (CER), with still more investment planned. These initial investments, while critical to the creation of the infrastructures, are not expected to sustain them much beyond the initial development. To provide the maximum benefit, the infrastructures need to be sustained through innovative financing models while providing value to PCOR and CER researchers. Sustainability Factors: Based on our experience with creating flexible sustainability strategies (i.e., strategies that are adaptive to the different characteristics and opportunities of a resource or infrastructure), we define specific factors that are important considerations in developing a sustainability strategy. These factors include assets, expansion, complexity, and stakeholders. Each factor is described, with examples of how it is applied. These factors are dimensions of variation in different resources, to which a sustainability strategy should adapt. Summary Observations: We also identify specific important considerations for maintaining an infrastructure, so that the long-term intended benefits can be realized. These observations are presented as lessons learned, to be applied to other sustainability efforts. We define the lessons learned, relating them to the defined sustainability factors as interactions between factors. Conclusion and Next Steps: Using perspectives and experiences from a diverse group of experts, we define broad characteristics of sustainability strategies and important observations, which can vary for different projects. Other descriptions of adaptive, flexible, and successful models of collaboration between stakeholders and data infrastructures can expand this framework by identifying other factors for sustainability, and give more concrete directions on how sustainability can be best achieved.

Moving To A User-Driven Research Paradigm

The traditional “bench-to-bedside” paradigm for clinical research has been successfully used for many decades. This model of knowledge generation has led to discoveries that have enhanced the quality and length of life. The combination of changes in research practice and in health care delivery, growing complexity in decision-making, increasing use of electronic health records (EHR), and growing resource constraints necessitate a shift to a user-driven research paradigm to generate new knowledge. This conceptual framework was created to clarify the perspective of the decision makers as well as the range of factors and the variability in thresholds used to make decisions. This framework may help researchers in creating actionable information to meet the needs of decision makers, which is needed for the transition to a user-driven research paradigm. Further, it is important to create an appropriate set of incentives to facilitate this transition to a user-driven research paradigm.