1

Introduction1

Randomized clinical trials (RCTs) are often referred to as the “gold standard” of clinical research. However, it is well documented that, in its current state, the U.S. clinical trials enterprise faces substantial challenges to the efficient and effective conduct of research (IOM, 2012a; Sung et al., 2003). Streamlined approaches to RCTs, such as large simple trials (LSTs), may provide opportunities for progress on these challenges.

Clinical trials support the development of new medical products and the evaluation of existing products by generating knowledge about safety and efficacy in pre- and post-marketing settings and serve to inform medical decision making and medical product development. Although well-designed and well-implemented clinical trials can provide robust evidence, a gap exists between the evidence needs of a continuously learning health system, in which all medical decisions are based on the best available evidence, and the reality, in which the generation of timely and practical evidence faces significant barriers.

Escalating costs, lengthy timelines, and the inability to regularly apply the evidence from clinical trials to broader populations are some of the challenges facing the U.S. clinical trials enterprise. Clinical trials are frequently conducted in a one-off manner: resources, staff, and research

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1 The planning committee’s role was limited to planning the workshop, and the workshop summary has been prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop. Statements, recommendations, and opinions expressed are those of individual presenters and participants and are not necessarily endorsed or verified by the Roundtable, the Forum, or the Institute of Medicine, and they should not be construed as reflecting any group consensus.



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1 Introduction1 Randomized clinical trials (RCTs) are often referred to as the “gold standard” of clinical research. However, it is well documented that, in its current state, the U.S. clinical trials enterprise faces substantial challenges to the efficient and effective conduct of research (IOM, 2012a; Sung et al., 2003). Streamlined approaches to RCTs, such as large simple trials (LSTs), may provide opportunities for progress on these challenges. Clinical trials support the development of new medical products and the evaluation of existing products by generating knowledge about safety and efficacy in pre- and post-marketing settings and serve to inform medical decision making and medical product development. Although well-designed and well-implemented clinical trials can provide robust evidence, a gap ex- ists between the evidence needs of a continuously learning health system, in which all medical decisions are based on the best available evidence, and the reality, in which the generation of timely and practical evidence faces significant barriers. Escalating costs, lengthy timelines, and the inability to regularly ap- ply the evidence from clinical trials to broader populations are some of the challenges facing the U.S. clinical trials enterprise. Clinical trials are frequently conducted in a one-off manner: resources, staff, and research 1  The planning committee’s role was limited to planning the workshop, and the workshop summary has been prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop. Statements, recommendations, and opinions expressed are those of individual presenters and participants and are not necessarily endorsed or verified by the Roundtable, the Forum, or the Institute of Medicine, and they should not be construed as reflecting any group consensus. 1

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2 LARGE SIMPLE TRIALS IN A LEARNING HEALTH SYSTEM participants are brought together for a single study and subsequently dis- banded, increasing time and costs across the research enterprise. The com- plexity of individual clinical trials is also a barrier to the efficient generation of evidence. Clinical trial protocols (i.e., the blueprint for how a study will be conducted) involve increasing amounts of tests, procedures, and data collection to support noncore endpoints (Tufts Center for the Study of Drug Development, 2012). The inclusion of these additional components heightens the workload for clinical study staff, increases overall study time and costs, and increases the burden on participants. Although challenges to the traditional RCT exist, a diverse portfolio of research methods, including innovative approaches to RCTs, is warranted to address evidence needs across the learning health care system—for example, to inform medical providers treating patients with multiple conditions, re- searchers comparing the effectiveness of medical treatments, newly diagnosed patients exploring treatment options, and medical product developers pursu- ing new treatments for unmet medical needs. Innovative approaches include the use of streamlined designs, such as those used for LSTs; trials performed in settings that more closely mirror real-world settings, such as pragmatic trials; trials embedded in health care delivery settings, such as point-of-care trials; and trials that are modified while they are in progress, such as adaptive trials, among others. The simplified design and the use of large, diverse populations to study an intervention make LSTs useful for scientific inquiries of commonly used therapies for which the difference in treatment effects is unknown. This is in contrast to, for example, an early stage (Phase I) clinical trial to test the tol- erability of a new medicine. Such a trial requires a small group of patients with a particular disease profile and would be less well-suited to an LST type of design. According to Peto et al. (1995), LSTs are designed to detect small or moderate treatment effects through the use of a simplified clinical trial design that deploys randomization to minimize bias and random error. During the workshop, the term “LST” was used broadly and encom- passed trials with a number of different attributes. The attributes of LSTs discussed during the workshop include the following: LSTs have simple randomization; broad eligibility criteria leading to a large, diverse patient population and increased generalizability of the study results; enough trial participants to provide evidence on interventions with small to moderate effects; a focus on meaningful outcomes important to patient care; and a streamlined design that provides a mechanism for effectively and efficiently capturing outcomes. Several examples of successful LSTs are available, including the Gruppo Italiano per lo Studio della Sopravvivenza nell’Infarto Miocardico (GISSI) trials, which evaluated patient survival after acute myocardial infarction. The GISSI trials employed protocols embedded in clinical practice, which

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INTRODUCTION 3 allowed the participation of more than 60,000 patients and almost four out of every five coronary care units that existed in Italy at the time (GISSI, 2013). The involvement of such a large percentage of the country’s cardiol- ogy clinics is credited with accelerating the uptake and implementation of the trials’ results. Significant opportunities exist to accelerate the use of LSTs to efficiently generate practical evidence for medical decision making and product de- velopment. Data for LSTs can be obtained from electronic health records (EHRs), whose increased adoption continues to be driven by the imple- mentation of the Health Information Technology for Economic and Clini- cal Health Act, which pays incentives to hospitals or eligible office-based professionals if they demonstrate use of their EHRs in a meaningful way. With more than 40 percent of hospitals and office-based physicians employ- ing at least a basic EHR system in 2012, the ability to collect research data in the course of regular care is greater than ever (RWJF, 2013). This could allow trials with streamlined data collection requirements to be supported by data captured in preexisting EHRs. For example, the Study of Technol- ogy to Accelerate Research (STAR) in Massachusetts (which is discussed in more detail in Chapter 3) successfully based its ongoing trial on childhood obesity screening and management strategies on the electronic medical re- cords already in use at each of its 14 participating sites (Clinicaltrials.gov, 2012). STAR offers a strong example of how the EHR can be used as the foundation for LST design and implementation. With the potential for such applicability and widespread use, LSTs present the opportunity, together with and as a complement to quasiex- perimental methods, registries, and safety efforts, to improve the speed and practicality of knowledge generation, characteristics fundamental to a learning health care system. With the development of new technologies capable of acquiring, managing, linking, and analyzing large quantities of data, the potential for innovation in methods, including the ability to draw research insights from routine clinical care experiences more effectively, is growing. Moreover, the increased use of innovative methodologies, such as LSTs, and their incorporation into routine clinical care can allow more patients than ever to engage in research to improve health care delivery and outcomes. Through streamlined protocols, the electronic availability of trial tools and outcomes data, and capabilities for remote participation, every patient has the potential to be a contributor to the continuous learning process and improve not only the outcomes of treatment for that individual but also the outcomes for other patients with similar conditions. LSTs offer the potential to drive the transformation necessary to realize this vision. To address these opportunities, as well as challenges, the Institute of Medicine’s (IOM’s) Roundtable on Value & Science-Driven Health Care (the Roundtable) and the Forum on Drug Discovery, Development, and

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4 LARGE SIMPLE TRIALS IN A LEARNING HEALTH SYSTEM Translation (the Forum) convened a public workshop on November 26 and 27, 2012, titled Large Simple Trials and Knowledge Generation in a Learn- ing Health System. A frequent theme raised in the workshops conducted for both the Roundtable and the Forum is that the cost, timing, and applicabil- ity limitations of the current effectiveness research and drug development paradigms, namely, a reliance on classic RCTs, become more acute daily. This workshop thus expanded on other workshops and discussions of the Forum to address the challenges facing the U.S. clinical trials enterprise and engage stakeholders in an open discussion of potentially transformative strategies to improve the efficiency and effectiveness of clinical trials, as summarized in Box 1-1. The workshop similarly expanded on the Round- table’s previous discussions and workshops on improving approaches to clinical effectiveness research, as summarized in Box 1-2, which it continues to foster through the discussions and products of the Clinical Effectiveness Research Innovation Collaborative. WORKSHOP SCOPE AND OBJECTIVES The workshop participants included a broad range of experts in clini- cal research, medical product development, patient advocacy, biostatistics, health information technology, clinical data standards, ethics, legal/regula- tory issues, and health care payment and financing. The workshop was structured to highlight the pros and cons of the design characteristics of LSTs, explore the utility of LSTs on the basis of case studies of past suc- cesses, and consider the challenges and opportunities for accelerating the use of LSTs in the context of a U.S. clinical trials enterprise that could benefit from increased implementation of simplified and streamlined clinical trial designs that produce generalizable results. In addition to drawing on a diverse array of perspectives on LST up- take, the workshop also explored infrastructure needs, the role of EHRs in LSTs, policies surrounding the enhanced use of LSTs, and the need for enhanced stakeholder engagement with health systems, clinicians, patients, and payers to successfully implement LSTs. The workshop statement of task can be found in Box 1-3, and the stated meeting objectives were as follows: • Explore acceleration of the use of LSTs to improve the speed and practicality of knowledge generation for medical decision making and medical product development; • Consider the concepts of LST design, examples of successful LSTs, the relative advantages of LSTs, and the infrastructure needed to build LST capacity as a routine function of care;

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INTRODUCTION 5 BOX 1-1 Key Themes from Workshops Conducted for the Forum on Drug Discovery, Development, and Translation • dentification of inefficiencies in the U.S. clinical trials enterprise. High costs, I extended trial timelines, high rates of investigator turnover, and low patient recruitment are a few challenges facing the conduct of clinical trials in the United States (IOM, 2010a, 2012a). •  esearch in the context of globalization. Competition from other countries, R where research costs are lower or governments are supporting growth in their indigenous medical research industry, is growing (IOM, 2010a, 2012a). •  ransformative strategies to improve the efficiency of clinical trials. Harmoni- T zation of regulatory standards and institutional processes, establishment of a national clinical trials infrastructure, and consideration of models to more effectively manage the nation’s research portfolio could advance the efficiency and effectiveness of the research enterprise and ultimately improve patient care (IOM, 2012a). •  onvergence of clinical research and clinical practice. Incorporation of clinical C research into the continuous quality improvement activities already undertaken by the health care system can help generate valid, reliable, and relevant evi- dence for medical practice (IOM, 2012a,b). •  atients and community health care providers as partners in clinical research. P The formation of collaborations between researchers, community health care providers, and patients early in the research process can facilitate the success of a clinical trial, from patient recruitment to the dissemination of trial results and assurance of the uptake of those results in clinical practice (IOM, 2012b). •  orkforce and career development. Greater attention to research in medical W school could improve practitioners’ attitudes toward research and attract young physicians to research careers. Similarly, placement of a higher value on the conduct of clinical trials in tenure decisions could enhance career ladders in research (IOM, 2012a). •  ultural and financial incentives. Incentives for research may be provided and C the efficiency of research may be increased if academic institutions and re- search organizations were encouraged to move beyond provincial systems in favor of greater efficiency (e.g., abandoning a site-specific institutional review board [IRB] for a centralized IRB model) and disincentives for research were corrected through the provision of more coverage under evidence development (from private payers as well as Medicare) (IOM, 2012a). • Identify structural, cultural, and regulatory barriers hindering the development of an enhanced LST capacity and discuss needs and strategies in building public demand for and participation in LSTs; and • Suggest near-term strategies for accelerating progress in the uptake of LSTs in the United States.

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6 LARGE SIMPLE TRIALS IN A LEARNING HEALTH SYSTEM BOX 1-2 Key Themes from Workshops Conducted for the Roundtable on Value & Science-Driven Health Care •  imitations to applicability of research results. Current clinical studies are often L designed to focus on people with just one condition, limiting their applicability to the increasing number people with multiple conditions (IOM, 2010b). • nefficiencies related to the timeliness, cost, and volume of clinical research. I Each incremental unit of research time and money could contribute to confi- dence in the results but also carries greater opportunity costs (IOM, 2010b). •  ew research designs, tools, and analytics. Innovative research designs and N statistical techniques may accelerate the timeliness and level of research insights, helping to better target, tailor, and refine approaches (IOM, 2010b, 2011). • ncentives for innovation in clinical effectiveness research. The use of new and I emerging tools to draw clinical research closer to practice will also require in- novative economic, regulatory, and clinician-patient cultural incentives for their application (IOM, 2010b). •  ffectiveness research as a routine part of practice. Learning from every E element of the care process is the theoretical goal of a learning health care system. This means anchoring the focus of clinical effectiveness research planning and priority setting on the point of service—the patient–provider in- terface—and enlisting the patient as an advocate in the process (IOM, 2010b, 2011). •  ransformational research potential of information technology. Broad applica- T tion and linkage of electronic health records afford the possibility of real-time clinical effectiveness research (IOM, 2010b, 2011). •  atients as central partners in the learning culture. Taking full advantage of P clinical records, even with blinded information, requires a strong level of under- standing and support for the work and its importance to improving the quality of health care. (IOM, 2010b). •  ontinuous learning in all aspects of care. This foundational principle of a C learning health care system depends on system and culture change in each element of the care process with the potential to promote interest, activity, and involvement in the process of knowledge and evidence development, from health professions education to care delivery and payment (IOM, 2010b). ORGANIZATION OF THE SUMMARY This publication summarizes the proceedings of Large Simple Trials and Knowledge Generation in a Learning Health System, a joint workshop coordinated by the Roundtable and the Forum in 2012. Each chapter of this summary corresponds to a workshop session and includes a summary of key speaker themes from each presentation. A selection of key speaker themes from across all sessions can be found in Box 1-4.

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INTRODUCTION 7 BOX 1-3 Statement of Task An ad hoc planning committee will plan and conduct a public workshop to explore acceleration of the use of large simple trials (LSTs) to improve the speed and practicality of knowledge generation for medical decision making and medi- cal product development, including efficacy and effectiveness assessments, in a continuously learning health system. The committee will steer development of the agenda for the workshop, including selection of speakers and discussants. Work- shop content will explore the concepts of LST design; examples of successful LSTs; the relative advantages of LSTs (in terms of cost and the utility of the results); the infrastructure needed to build LST capacity as a routine function of care; the structural, cultural, and regulatory barriers hindering the development of such an LST capacity; building public demand for and participation in LSTs; and identifying near-term strategies for accelerating progress. BOX 1-4 Select Speaker Themes •  STs and greater patient involvement in research will be key to moving the L U.S. health care system to a future in which every clinical encounter is an op- portunity for learning (Michael S. Lauer). •  STs pose a series of challenges and opportunities for the clinical research L enterprise. These include solidification of their external validity, better under- standing of the implications for the detection of treatment heterogeneity and patient safety, and exploration of opportunities for greater integration of patient- reported outcomes (Ralph I. Horwitz). •  STs provide an opportunity to conduct cost-efficient research with clinical and L policy relevance, as well as take advantage of emerging research methods and data sources for the benefit of population health (Niteesh K. Choudhry, P. J. Devereaux, Joann E. Manson, Elsie M. Taveras). •  STs provide an opportunity to bridge the gap between research activities and L clinical practice by appropriately balancing the risks and benefits of research when the safety and effectiveness of routine clinical practices are often un- known (Ruth R. Faden). •  echnical challenges to LSTs have been addressed in large part, and policy T and culture changes remain the primary challenges to increased LST uptake (Robert M. Califf).

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8 LARGE SIMPLE TRIALS IN A LEARNING HEALTH SYSTEM Chapters 2 to 8 summarize the expert presentations at the workshop and are organized by thematic focus. Chapter 2 focuses on the current state and momentum of the LST enterprise. Chapter 3 looks at several examples of LSTs, emphasizing trade-offs in trial design and their impact on the research process and outcomes. Chapter 4 takes a look at the cur- rent state of trial complexity, strategies for increasing trial efficacy, and the perspective of the U.S. Food and Drug Administration. Chapter 5 addresses the infrastructure needs and barriers to the performance of more LSTs and discusses both the current state and future potential of the use of EHRs as platforms for LSTs. Chapter 6 delves into the real and perceived ethical and policy barriers to the greater use of LSTs, highlighting examples of ways in which such barriers have been confronted and suggesting components of a policy framework that would facilitate LSTs. Chapter 7 explores partner- ships with stakeholders relevant to the increased use of LSTs, focusing on the elements of the greatest importance to patients, payers, clinicians, and health care systems in advancing the uptake of LSTs. Chapter 8 highlights the United Kingdom–based Randomized Evaluations of Accepted Choices in Treatment trials, underscoring lessons learned and best practices for LST investigators. Chapter 9 highlights the workshop participants’ insights into strategies moving forward and summarizes the workshop’s concluding dis- cussion, in which many participants suggested potential strategies and pri- orities for accelerating progress in the uptake of LSTs in the United States. REFERENCES Clinicaltrials.gov. 2012. Study of Technology to Accelerate Research (STAR). http://clinical trials.gov/show/NCT01537510 (accessed June 17, 2013). GISSI (Gruppo Italiano per lo Studio della Sopravvivenza nell’Infarto Miocardico). 2013. What Is Gissi? http://www.gissi.org/EngIntro/T_Intro_ENG.php (accessed June 17, 2013). IOM (Institute of Medicine). 2010a. Transforming Clinical Research in the United States: Challenges and Opportunities: Workshop Summary. Washington, DC: The National Academies Press. IOM. 2010b. Redesigning the Clinical Effectiveness Research Paradigm: Workshop Summary. Washington, DC: The National Academies Press. IOM. 2011. Learning What Works: Infrastructure Required for Comparative Effectiveness Research: Workshop Summary. Washington, DC: The National Academies Press. IOM. 2012a. Envisioning a Transformed Clinical Trials Enterprise in the United States: Establishing an Agenda for 2020: Workshop Summary. Washington, DC: The National Academies Press. IOM. 2012b. Public Engagement and Clinical Trials: New Models and Disruptive Technolo- gies: Workshop Summary. Washington, DC: The National Academies Press. Peto, R., R. Collins, and R. Gray. 1995. Large-scale randomized evidence: large, simple trials and overviews of trials. Journal of Clinical Epidemiology 48(1):23–40.

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INTRODUCTION 9 RWJF (Robert Wood Johnson Foundation). 2013. Health Information Technology in the United States: Better Information Systems for Better Care. Princeton, NJ: RWJF. http:// www.rwjf.org/content/dam/farm/reports/reports/2013/rwjf406758 (accessed June 20, 2013). Sung, N. S., W. F. Crowley, M. Genel, P. Salber, L. Sandy, L. M. Sherwood, S. B. Johnson, V. Catanese, H. Tilson, K. Getz, E. L. Larson, D. Scheinberg, E. A. Reece, H. Slavkin, A. Dobs, J. Grebb, R. A. Martinez, A. Korn, and D. Rimoin. 2003. Central challenges facing the national clinical research enterprise. Journal of the American Medical Association 289(10):1278–1287. Tufts Center for the Study of Drug Development. 2012. News Report: Extraneous Data Col- lected in Clinical Trials Cost Drug Developers $4 Billion to $6 Billion Annually. http:// csdd.tufts.edu/news/complete_story/pr_ir_nov-dec_2012 (accessed June 19, 2013).

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