Appendix A
Letter Report on the Development of a Model for Ranking FDA Product Categories on the Basis of Health Risks

Committee on Ranking FDA Product Categories Based on Health Consequences


Board on Environmental Studies and Toxicology


Division on Earth and Life Studies


National Research Council


Institute of Medicine


NATIONAL RESEARCH COUNCIL AND
INSTITUTE OF MEDICINE
OF THE NATIONAL ACADEMIES


THE NATIONAL ACADEMIES PRESS
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Appendix A Letter Report on the Development of a Model for Ranking FDA Product Categories on the Basis of Health Risks Committee on Ranking FDA Product Categories Based on Health Consequences Board on Environmental Studies and Toxicology Division on Earth and Life Studies National Research Council Institute of Medicine 149

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150 A Risk-Characterization Framework for Decision-Making at FDA National Research Council 500 Fifth Street, NW Division on Earth and Life Studies Washington, DC 20001 Board on Environmental Studies and Toxicology Phone: 202 334 2347 Fax: 202 334 2752 February 17, 2009 Dr. Kathleen M. Koehler Science Policy Analyst Office of Science and Data Policy U.S. Department of Health and Human Services Hubert Humphrey Building, Room 434E 200 Independence Avenue, SW Washington, DC 20201 Dear Dr. Koehler: At your request, the National Academies convened the Committee on Ranking FDA Product Categories Based on Health Consequences. The commit- tee members were selected on the basis of their expertise in food safety, health economics, medical devices, vaccine safety, pharmacoepidemiology, biostatis- tics, comparative risk analysis, and decision analysis. The committee was tasked with developing and applying a conceptual model to rank product categories in FDA program areas on the basis of health risks, both positive and negative aspects (that is, the committee was to consider beneficial aspects of the product categories in the context of possible adverse health consequences). The study was divided into two phases: selection of the model (phase I) and development, refinement, and application of the model to conduct a risk ranking of FDA product categories (phase II). The committee’s task is described in greater detail below. This letter report fulfills the task speci- fied for phase I of this project. The committee held two meetings. The first included a public session dur- ing which FDA staff and other invited experts made presentations. During that session, some indicated that a model that incorporates evaluations of interven- tions would be particularly valuable. The committee agrees but notes two com- plicating factors: evaluating baseline risks among product categories is a task of great magnitude and complexity, and it is the nature of interventions to be at the individual-product level and not the product-category or program level. There- fore, the model dictated by the committee’s task is not directly applicable to

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Appendix A 151 “intervention” analysis and cannot be used to evaluate strategies to reduce risk. However, the committee acknowledges that the existence of intervention capa- bilities is an important measure in determining risk, and model parameters will need to capture that aspect. Given the size and complexity of the task, the com- mittee will attempt to keep the model as simple as possible, recognizing that rough estimates of risk may be all that is possible at the product-category level. This letter report first provides background information on comparative risk analysis. Next, it outlines the conceptual model. Considerations regarding the product categories and their attributes are provided. The report concludes with a discussion of the steps needed to refine the model and conduct a risk- ranking exercise. (There are also several attachments: a verbatim statement of the committee’s task, a committee roster and biographies, a bibliography, and acknowledgment of reviewers.) The report reflects the consensus of the commit- tee and has been reviewed in accordance with standard National Research Council review procedures. Sincerely, Robert Lawrence, Chair Committee on Ranking FDA Product Categories Based on Health Consequences

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152 A Risk-Characterization Framework for Decision-Making at FDA LETTER REPORT ON THE DEVELOPMENT OF A MODEL FOR RANKING FDA PRODUCT CATEGORIES ON THE BASIS OF HEALTH RISKS BACKGROUND In 1986, U.S. Environmental Protection Agency (EPA) Administrator Lee Thomas asked 75 scientists and managers to develop a report on the “relative importance” of various environmental threats that were mainly in EPA’s juris- diction. In 1987, the group issued Unfinished Business (EPA 1987), which cate- gorized environmental threats in 31 problem areas, defined largely along exist- ing programmatic lines. The group identified and divided the risks according to four important attributes with respect to the characterization of the 31 environ- mental problem areas: cancer risk, noncancer risk, ecologic risk, and “welfare” effects. The resulting report provided separate assessments (ranked low, me- dium, or high) for each of the four attributes. A key insight of Unfinished Busi- ness was that EPA's resource allocations appeared to be more in line with what the public perceived as the most important risks than with the priorities identi- fied by the agency's experts. EPA asked its Science Advisory Board (SAB) to review the report, and the SAB released a follow-up report, Reducing Risk (EPA SAB 1990), which endorsed the broad comparative risk analysis (CRA) ap- proach and produced findings similar to those in Unfinished Business. In addition to spawning many applications of CRA at the office, region, state, and local levels (Minard 1996; Jones 1997), the early CRA efforts led to questions about how best to facilitate comparisons and identify useful attributes for characterizing risks or risk-reduction opportunities. The EPA SAB noted that ranking risks or ranking the alternative actions that might be available for reduc- ing risks would probably yield different rankings (EPA SAB 1990). In particu- lar, although some risks might rank high, they might also be associated with very expensive or uncertain risk-reduction actions and therefore be unamenable to intervention according to cost-benefit criteria. In addition, if risks associated with some low-priority areas can be addressed effectively with certainty at low or no cost, their low-priority status should not prevent these “bargains” from being recognized. Progress on CRA method development continues, although its use remains relatively limited. Finkel and Golding (1995) noted that the “comparison of risks involves values in at least five areas: defining what we mean by ‘risk’; selecting the endpoints to consider; categorizing the risks for comparison; selecting a time frame for evaluating the adverse effects; and gauging the seriousness of the con- sequences.” In February 1994, a workshop organized by Resources for the Fu- ture for the President’s Office of Science and Technology Policy brought to- gether researchers in CRA with the goal of developing a systematic process for comparing risks among different federal agencies (Davies 1996). As part of that work, researchers from Carnegie Mellon University developed a framework for

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Appendix A 153 ranking risks that included both quantitative and qualitative measures of relevant programmatic attributes (Fischhoff 1995; Morgan et al. 1996). They included health-impact measures (such as morbidity and mortality) and psychometric measures that research shows play an important role in the evaluation of risks (such as fairness, scientific understanding, and uncertainty). That work spawned a series of research projects and papers that refined and applied the framework (e.g., Morgan et al. 1999, 2001; Long and Fischhoff 2000; Morgan et al. 2000; DeKay et al. 2001; Florig et al. 2001; Willis et al. 2004, 2005; Fischhoff 2006; Gutiérrez et al. 2006; Bronfman et al. 2007, 2008a,b), including a discussion directly related to food safety (DeKay et al. 2005). Recently, those risk-ranking methods have been adopted by a variety of national and international entities. For example, the U.S. Army Corps of Engineers is using the methods to rank hurricane mitigation opportunities on the Louisiana Gulf Coast (USACE 2008), researchers at the University of North Carolina School of Public Health and RAND Corporation are using them to develop an environmental-health strategy and action plan for the United Arab Emirates (UNC 2008), and the British gov- ernment is using them to communicate with and gather information from the general public on health-related priority-setting strategies (HM Treasury 2004, 2005a,b; OGC 2008). Regardless of the application, such projects share the goals of collecting and presenting risk information in a systematic manner to guide and assess informed judgments. After assessment, those judgments may serve as a valuable input into a decision-making process focused on evaluating difficult policy choices. STATEMENT OF TASK AND COMMITTEE’S APPROACH In light of the increased use of CRA by federal agencies, the Department of Health and Human Services (DHHS) and the Food and Drug Administration (FDA) asked the National Research Council to convene an expert committee to develop and apply an evidence-based conceptual model and methods for ranking categories of products addressed by FDA programs. The conceptual model and methods were to focus on ranking product categories according to the ranges of magnitude of various potential health consequences to U.S. users of the products at the individual level and the population level, taking both adverse and benefi- cial effects into consideration. To accomplish its task, the committee was to in- clude the following activities: consult with the sponsor to select FDA product categories to be ranked; consider products currently in use and near-term future products expected to come under FDA purview; review selected scientific litera- ture bearing on adverse and beneficial health consequences; consider the scien- tific literature broadly to include social-science and economics literature, gray literature, and regulatory-policy literature; seek opportunities to assess health consequences in a way that allows results to be compared among broad product categories; identify information needed to address key uncertainties; assess the performance of the evidence-based model for ranking the selected product cate-

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154 A Risk-Characterization Framework for Decision-Making at FDA gories and identify next steps for model refinement; and where applicable and feasible, consider the potential effects on population health if risk-reduction strategies curtail the beneficial use of products. The committee was asked first to produce a brief letter report that de- scribes the scientific conceptual framework to be used to rank product categories (phase I) and then to perform ranking exercises by using the proposed concep- tual framework (phase II). In neither phase was the committee to recommend regulatory strategies; those choices entail policy judgments that transcend scien- tific and technologic considerations. This letter report fulfills phase I of the pro- ject. To accomplish its task, the committee held a public session at its first meeting, during which it heard presentations from FDA staff in the various pro- gram areas and from experts in the fields of decision analysis and CRA. The committee reviewed numerous scientific publications on CRA and literature provided by FDA. On the basis of its review and the statement of task, the committee selected a model that has the capacity to evaluate multiple product categories and compare them; to evaluate the magnitude and variation in distri- bution of both favorable and unfavorable effects; to improve FDA’s discharge of its responsibilities as they affect public health; to evaluate new product catego- ries, risks, benefits, and other considerations; and to include multiple non- health-related outcomes of interest, such as equity and the quality of scientific understanding. The committee recognized that the model should be able to func- tion to the greatest extent possible with sparse information. Although the pri- mary focus of the committee was human health, the model considers animal health and welfare to be consistent with the full scope of activities conducted by FDA. The CRA exercise requested in the statement of task is a valuable tool in determining relative risks among product categories, but such exercises are not sufficient to guide many policy decisions unless they incorporate additional con- cerns. For example, the absolute risk in a category may not be a good indicator of the potential to reduce risk in that category or of the potential to reduce risk by any specific action. Measures of the potential benefits of specific actions are critical for resource-allocation decisions. Likewise, the presence of a health risk may or may not be associated with the economic costs or benefits of addressing the risk, the equity concerns (who pays and who benefits), the likelihood and timeframe of achieving the stated risk reduction, or the public’s perceptions of the risk-mitigation options. To the extent that any of those concerns are or should be important in making policy decisions, the proposed CRA alone would not be sufficient for making decisions. On the basis of the guidance that the committee received from the statement of task and from clarification offered by the sponsor during its first public meeting, it concluded that discussion of the merits of other theoretical frameworks that might be valuable in assessing risk- mitigation alternatives was outside its task. Baseline ranking of risks is a neces- sary but not sufficient step in the more general decision-making process.

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Appendix A 155 RANKING MODEL Conceptual Framework On the basis of recent literature, the committee concluded that the best ap- proach to ranking FDA product categories on the basis of health risk is to use a conceptual framework similar to that described by Florig et al. (2001). Unlike other comparative methods (such as the World Health Organization’s Global Burden of Disease Study [Murray and Lopez 1996; WHO 2008], which ranks solely on the basis of utility loss from illness), the approach described by Florig and colleagues allows for disparate items, such as cosmetics and vaccines, to be ranked, as will be necessary for FDA. Furthermore, although this is not explic- itly required by FDA, the selected approach is designed to accommodate qualita- tive and quantitative variables in the formal ranking process. That will facilitate inclusion of important variables and may greatly improve the utility of the pro- posed approach for FDA. Figure 1 summarizes the two phases and the multistep process envisioned by the committee. As illustrated in Figure 1, steps A and B involve defining the FDA product categories to rank and identifying the risk attributes to describe the categories, respectively. In phase I of this project, which is summarized in this letter report, the committee has proposed a preliminary list of categories and attributes. The final determination of the categories and attributes will require further input from knowledgeable FDA staff, iteration, and refinement and will be completed in phase II of this project. The committee’s final report will dis- cuss the final categorization and identification of attributes and the process used to make those determinations. Step C requires describing the categories in terms of the attributes, step D involves performing the risk-ranking exercises, and step E involves summarizing and evaluating the results of the risk-ranking process. Steps C-E will be accomplished in phase II of this project, the results of which will be described in the committee’s final report. Each step in the multistep process is described in greater detail in the sections that follow. Phase I Phase II PRELIMINARY PRELIMINARY FINAL Step A: Define the Step A: Define the FDA product FDA product categories to be ranked categories to be ranked Step E: Describe Step C: Describe Step D: Select the issues the categories in participants and identified and terms of perform the risk the resulting attributes rankings rankings PRELIMINARY FINAL Step B: Identify the risk Step B: Identify the attributes that should risk attributes to be be considered for each considered for each of of the product the product categories categories FIGURE 1 Framework of health-risk ranking model. Source: Adapted from Florig et al. 2001. Reprinted with permission; copyright 2001, Risk Analysis.

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156 A Risk-Characterization Framework for Decision-Making at FDA Uncertainties in the risk-ranking model will be captured in two ways. For some attributes, such as those measuring mortality risks, a quantitative approach can be used by providing a mean (or median) with population upper and lower bounds. Other attributes can be selected to represent uncertainties with a qualita- tive description. For example, an attribute that captures the quality of scientific understanding will indicate knowledge gaps, which will lead to uncertainty in the ranking exercise. The committee recognizes that successful ranking will re- quire both iteration and further engagement with FDA. Step A: Defining the Product Categories Any ranking process must begin with development of a list of the risk items to rank. Many approaches exist to categorize risk, and as Morgan et al. (1996) note, “no single categorization scheme is likely to serve all … needs.” Morgan et al. (2000) describe criteria for defining categories and state that cate- gories should be “exhaustive so that no relevant risks are overlooked,” “mutu- ally exclusive so that risks are not double-counted,” and “homogenous so that all risk categories can be evaluated on the same set of attributes.” Furthermore, the categories should be relevant to the organizational structure, legislative man- dates, and risk-management activities of the organization. Among the other cri- teria listed by Morgan et al. (2000) is the goal of keeping the number of catego- ries to a number that makes the risk-ranking exercise feasible. Depending on the techniques used during the ranking, a feasible number would generally be in the range of 15-30. Given the number of products that FDA regulates, the commit- tee recognizes that the number of categories could be expanded too much and make risk-ranking impossible. That means that the task of ranking products for FDA as a whole must of necessity focus on highly aggregated product catego- ries. FDA provided the committee with an initial list of product categories, which is shown in Table 1. The list includes 28 categories, and it primarily mir- rors FDA’s organizational structure and statutory and regulatory authorities (that is, it is broken down according to FDA’s existing five product-focused centers). Although the committee noted that the categorization could alternatively focus on type or magnitude of hazard, it concluded that the final selection of the prod- uct categories for ranking will require further input from FDA staff who have specific expertise in the FDA products. Valuable input from FDA will include data on the size of each potential category (for example, with respect to numbers of regulated individual products or firms and relative market sizes in dollars). The committee expects that some of the categories will expand, others will con- tract, and some will be substantially revised. For example, the committee ques- tioned the product categories suggested for medical devices. Currently, medical devices are defined according to risk and classified as class I, II, or III devices. Accordingly, this scheme may be more appropriate for categorization of medical devices. Furthermore, the committee notes that the present list includes catego-

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Appendix A 157 ries at different levels of specificity, and this could obscure the value of the ranking exercise. The committee will determine whether additional categories will be needed to address near-term future products, such as nanomaterials, or whether those products can be integrated into the existing categories. Using the criteria of Morgan et al. (2000) discussed above and input from FDA, the com- mittee will be able to determine the most appropriate product categories for evaluation in phase II of this project. Step B: Identifying the Attributes Ranking risks requires identifying the important attributes of the risks. Morgan et al. (1996) described criteria for selecting attributes and noted that attributes should be comprehensive, non-overlapping, stand-alone, measurable, and minimal to reduce the complexity of the risk-ranking exercise. As a prelimi- nary scoping exercise, the committee selected five attribute groups related to exposure, severity of effect, ability to anticipate and prevent adverse events, ability to mitigate adverse events, and benefits of products or product categories. Each group contains multiple specific attributes, which are shown in Table 2. The committee emphasizes that Table 2 is only a preliminary list. Overlapping attributes must be explicitly noted to avoid double-counting in the risk-ranking exercise, and most important, attributes must be selected that are applicable be- tween and within the broad FDA product categories. That exercise will be chal- lenging and will require input from FDA staff who have specific expertise in FDA product categories. The committee will use the criteria of Morgan et al. (1996) discussed above and further input from FDA to finalize the list of risk attributes in phase II of this project. At the conclusion of this process, the attrib- utes will be clearly defined and well understood by FDA staff and the risk rank- ers. The committee defined exposure as the condition of being subject to some effect or influence and considered the five risk attributes shown in Table 2 to be appropriate for quantifying or describing it. The exposed population is the per- centage of the U.S. population potentially exposed. Cumulative incidence is the number of new cases of illness, injury, or other health-related events attributable to an exposure during a specified period in a specified population and is ex- pressed as a rate. Prevalence is the number of cases of a health-related state or event that exist in a specified population at a particular time, regardless of when they began or how long they have existed, and can be expressed as a rate. Vul- nerable groups refer to people who have increased susceptibility to adverse out- comes because of genetics, age, socioeconomic status, occupational or environ- mental exposure, or physiologic state; this attribute could be described in terms of the number and size of vulnerable populations. Cluster refers to a group of people who are at excess risk for adverse events that are related temporally, by proximity, or by source; this attribute could be described in terms of group size.

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158 A Risk-Characterization Framework for Decision-Making at FDA TABLE 1 Suggested Initial List of Product Categories for Ranking Provided by FDA Program Area Product Categories Food, cosmetics, and dietary Food supplements Produce Eggs and dairy Processed food Seafood Cosmetics Dietary supplements Food and color additives Drugs and biologics regulated as Over-the-counter drugs drugs Diagnostic prescription drugs Preventive prescription drugs Prescription drugs that are life-sustaining Prescription drugs for treatment for symptoms or improvement in quality of life Prescription drugs that are used cosmetically Biologic products other than those Vaccines regulated as drugs Blood and tissue products In vitro diagnostics related to donor testing Devices regulated as biologics Allergenics Cell and gene therapy Veterinary products Approved animal drugs Unapproved animal drugs Animal feeds Pet food Medical devices and radiation- Critical devices for professional use emitting products Noncritical devices for professional use Noncritical devices for lay use Nonmedical radiation-emitting devices Patient cables and lead wires

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Appendix A 159 TABLE 2 Risk Attributes for Model for Ranking FDA Product Categories on the Basis of Health Risk Attribute Groups Risk Attributes Exposure Exposed population Cumulative incidence Prevalence Vulnerable groups Cluster Severity of effect Mortality Morbidity Vulnerable groups Catastrophic event Diffusion effects beyond intended usea Animal health Ability to anticipate and prevent Quality of scientific understanding adverse events Availability of substitutes History of problems and corrective actions Availability of quality standards, guidelines, or standard operating procedures (quality assurance and quality control, good manufacturing practices) Variability in product composition or performance Vulnerability of supply chain Ability to mitigate adverse events Availability of substitutes Availability of corrective actions Traceability Latency Ability to recall Reversibility Product benefits Mortality reduction Morbidity reduction Efficacy and effectiveness Animal welfare a Diffusion effects is an attempt to capture effects on people who do not use the product.

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166 A Risk-Characterization Framework for Decision-Making at FDA The committee will not recommend regulatory strategies, because those choices will entail policy judgments that transcend scientific and technologic considerations. Seven months after initiation of the study, the committee will prepare a brief letter report describing the conceptual model and methods it will use to rank product categories in its final report.

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Appendix A 167 Attachment B COMMITTEE MEMBERSHIP ROBERT LAWRENCE, Chair, Johns Hopkins University, Baltimore, MD JAMES ANDERSON, Case Western Reserve University, Cleveland, OH FRANCISCO DIEZ-GONZALEZ, University of Minnesota, St. Paul KATHRYN EDWARDS, Vanderbilt University, School of Medicine, Nashville, TN SUSAN ELLENBERG, University of Pennsylvania, Philadelphia PAUL FISCHBECK, Carnegie Mellon University, Pittsburgh, PA HELEN JENSEN, Iowa State University, Ames ROBIN KELLER, University of California, Irvine DAVID MELTZER, University of Chicago, Chicago, IL SANFORD MILLER, University of Maryland, College Park RICHARD PLATT, Harvard Medical School, Boston, MA KIMBERLY THOMPSON, Harvard School of Public Health, Boston, MA STAFF ELLEN MANTUS, Project Director DAVID A. BUTLER, Senior Program Officer NORMAN GROSSBLATT, Senior Editor HEIDI MURRAY-SMITH, Research Associate PANOLA GOLSON, Senior Program Assistant BIOGRAPHIES Robert S. Lawrence (IOM), Chair, is the Center for a Livable Future (CLF) professor and director of the CLF in the Department of Environmental Health Sciences, professor of health policy and international health at the Johns Hop- kins Bloomberg School of Public Health and professor of medicine at the Johns Hopkins University School of Medicine. His expertise and research interests include community and social medicine, human rights, health promotion and disease prevention, evidence-based decision rules for prevention policy, and food security. Dr. Lawrence is a master of the American College of Physicians and a fellow of the American College of Preventive Medicine. He is a member of the Institute of Medicine and has served on numerous National Academies committees, most recently the Committee on Adolescent Health Care Services and Models of Care for Treatment, Prevention, and Health Development and the Committee to Evaluate Measures of Health Benefits for Environmental, Health,

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168 A Risk-Characterization Framework for Decision-Making at FDA and Safety Regulation. Dr. Lawrence received his MD from Harvard Medical School and trained in internal medicine at the Massachusetts General Hospital. James M. Anderson (IOM) is professor of pathology, macromolecular science, and biomedical engineering at Case Western Reserve University. His research interests range from his activity as a pathologist in clinical implant retrieval and evaluation to fundamental mechanistic studies focused on tissue, cell, and blood interactions with biomaterials. Dr. Anderson is the recipient of the Elsevier Biomaterials Gold Medal for the most significant contributions to biomaterials science from 1980 to 2005 and the Society of Investigative Pathology Chugai Mentoring Award. He has been involved in the International Standards Organi- zation Task Force to Develop Standards for Medical Device Safety for the last 18 years. He is editor-in-chief of the Journal of Biomedical Materials Research. Dr. Anderson is a member of the Institute of Medicine and has served as a member of its Committee on Postmarket Surveillance of Pediatric Medical De- vices and Committee on Capturing the Full Power of Biomaterials for Military Medical Needs. He received his MD from the Case School of Medicine and his PhD in chemistry from Oregon State University. Francisco Diez-Gonzalez is an associate professor in the Department of Food Science and Nutrition at the University of Minnesota. His research expertise is in food-safety microbiology, foodborne pathogens, safety of fresh fruits and vegetables, preharvest control of pathogenic E. coli, bioterrorism agents, and safety of organic food. Dr. Diez-Gonzalez teaches courses in food safety and food microbiology. He has served on the University of Minnesota Institutional Biosafety Committee, and he has advised both undergraduate and graduate stu- dents. He is also the recipient of the New Career Excellence Award for the Col- lege of Human Ecology at the University of Minnesota. He is member of the Editorial Board of the Journal of Food Protection and the Journal of Food Ana- lytical Methods. Dr. Diez-Gonzalez received his PhD in food science from Cor- nell University. Kathryn M. Edwards (IOM) is Sarah H. Sell Chair in Pediatrics and the direc- tor of the Vanderbilt Vaccine Research Program at Vanderbilt University Medi- cal Center. Her research focuses on the evaluation of vaccines for the prevention of infectious diseases in adults and children. She is a fellow of the Infectious Diseases Society of America and of the American Academy of Pediatrics. Dr. Edwards has served as a member of the Advisory Committee on Immunization Practices of the Centers for Disease Control and Prevention and the Vaccines and Related Biological Products Advisory Committee of the Food and Drug Administration. She has also served as a member of the National Academies Committee to Assess the Safety and Efficacy of the Anthrax Vaccine. Dr. Ed- wards received her MD from the University of Iowa College of Medicine.

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Appendix A 169 Susan S. Ellenberg is professor of biostatistics and associate dean for clinical research at the University of Pennsylvania School of Medicine. Her research focuses on the design and analysis of clinical trials and the assessment of medi- cal-product safety. Dr. Ellenberg is associate editor of Clinical Trials and of the Journal of the National Cancer Institute. She is a fellow of the American Statis- tical Association, the Society for Clinical Trials, and the American Association for the Advancement of Science. She has served as a member of the National Academies Planning Committee for the IOM Drug Safety Report: Resource Implications, Committee on the Assessment of the U.S. Drug Safety System, and Committee on Applied and Theoretical Statistics. Dr. Ellenberg received her PhD in mathematical statistics from George Washington University. Paul S. Fischbeck is professor of social and decision sciences, professor of en- gineering and public policy, and director of the Center for the Study and Im- provement of Regulation at Carnegie Mellon University. His research focuses on the quantification and communication of uncertainty, including theoretical improvements in decision analysis and numerous applied real-world problems. Dr. Fischbeck has written extensively on various applications of decision and risk-analysis methods and has won several awards from the Institute for Opera- tions Research and the Management Sciences. He is a member of the National Research Council Marine Board and has served on several committees, includ- ing the Committee on Marine Salvage Response Capability: A Workshop and the Committee on Risk Assessment and Management of Marine Systems. Dr. Fischbeck received a PhD in industrial engineering and engineering manage- ment from Stanford University. Helen H. Jensen is a professor of economics and head of the Food and Nutri- tion Policy Division of the Center for Agricultural and Rural Development at Iowa State University. Her research fields are food and nutrition policy, analysis of food-consumption behavior, economics of food safety, and health risk as- sessment. Dr. Jensen is on the Board of Directors of the American Agricultural Economics Association and of the Council on Food, Agricultural and Resource Economics and has recently been on the Editorial Boards of Food Economics, Agricultural Economics, and Agribusiness: An International Journal. She has served on U.S. Department of Agriculture expert review panels, including the Panel on Measuring Food Security in the United States and the Panel on the Health Eating Index. She has served on several National Academies committees and is currently involved with the Committee on Nutrition Standards for Na- tional School Lunch and Breakfast Programs and the Committee on Economic Development and Current Status of the Sheep Industry in the United States. Dr. Jensen received her PhD in agricultural economics from the University of Wis- consin-Madison. L. Robin Keller is a professor of operations and decision technologies at the University of California, Irvine. Her research is in decision analysis, risk analy-

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170 A Risk-Characterization Framework for Decision-Making at FDA sis, creative problem-structuring, and behavioral decision theory. She is the edi- tor-in-chief of Decision Analysis. Dr. Keller has served as program director for the Decision, Risk, and Management Science Program of the U.S. National Sci- ence Foundation, and she has conducted studies funded by the U.S. Environ- mental Protection Agency and the Department of Energy. She has served as a member of the National Research Council Committee to Assess the Distribution and Administration of Potassium Iodide in the Event of a Nuclear Incident, and she is currently a member of the U.S. National Committee for the International Institute for Applied Systems Analysis. Dr. Keller received her PhD from the University of California, Los Angeles. David O. Meltzer is an associate professor in the Department of Medicine, chief of the Section of Hospital Medicine, and an associate faculty member of the Harris School and the Department of Economics at the University of Chi- cago. He is also director of the Center for Health and the Social Sciences and co- director of the Program on Outcomes Research Training. Dr. Meltzer’s research explores problems in health economics and public policy, with a focus on theo- retical foundations of medical cost-effectiveness analysis and the effects of managed care and medical specialization on the cost and quality of care. He is the recipient of numerous awards, including the National Institutes of Health Medical Scientist Training Program Fellowship, the National Science Founda- tion Graduate Fellowship in Economics, and the Lee Lusted Prize of the Society for Medical Decision Making, of which he is the immediate past president. Dr. Meltzer has served on several National Academies committees, most recently the Committee on the Assessment of the U.S. Drug Safety System and the Committee on Establishing a National Cord Blood Stem Cell Bank Program. He received his MD and his PhD in economics from the University of Chicago. Sanford A. Miller is a senior fellow at the Joint Institute for Food Safety and Applied Nutrition at the University of Maryland. He was named professor and dean emeritus of the Graduate School of Biomedical Sciences at the University of Texas Health Science Center in December 2000 after serving as dean from 1987 to 2000. He is a former director of the Center for Food Safety and Applied Nutrition in the Food and Drug Administration. Dr. Miller has served on many national and international government and professional-society advisory com- mittees, including the National Advisory Environmental Health Sciences Coun- cil of the National Institutes of Health and the Joint World Health Organization- United Nations Food and Agricultural Organization Expert Advisory Panel on Food Safety. He is a member of the National Academies Food and Nutrition Board and the Committee on Use of Dietary Supplements by Military Personnel. Dr. Miller received his PhD in physiology and biochemistry from Rutgers, The State University of New Jersey, New Brunswick. Richard Platt is professor and chair of the Department of Ambulatory Care and Prevention and a professor of medicine at Harvard Medical School. His research

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Appendix A 171 focuses on the safety and effectiveness of marketed drugs and vaccines and on infectious diseases in the community and hospital settings. Dr. Platt is a former chair of the Food and Drug Administration Drug Safety and Risk Management Advisory Committee. He is a member of the Advisory Panel for Research of the Association of American Medical Colleges and has chaired the Executive Committee of the HMO Research Network, the Epidemiology and Disease Con- trol Study Section of the National Institutes of Health, and the Steering Commit- tee of the Centers for Disease Control and Prevention Office of Health Care Partnerships. He has served on several National Academies committees and is a member of the Roundtable on Evidence-Based Medicine. Dr. Platt received his MD from Harvard Medical School. Kimberly M. Thompson is associate professor of risk analysis and decision science at the Harvard School of Public Health. Her research is related to devel- oping and applying quantitative methods for risk assessment and risk manage- ment and the public-policy implications of including uncertainty and variability in risk characterization. She has served on several National Academies commit- tees, including the Committee for the Study of a Motor Vehicle Rollover Rating System and the Subcommittee to Update the 1999 Arsenic Report. She is a member of the Board on Environmental Studies and Toxicology. Dr. Thompson received her ScD in environmental health from the Harvard School of Public Health.

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172 A Risk-Characterization Framework for Decision-Making at FDA Attachment C REFERENCES Bronfman, N.C., L.A. Cifuentes, M.L. DeKay, and H.H. Willis. 2007. Accounting for variation in the explanatory power of the psychometric paradigm: The effects of aggregation and focus. J. Risk Res. 10(4):527-554. Bronfman, N.C., L.A. Cifuentes, and V.V. Gutierrez. 2008a. Participant-focused analysis: Explanatory power of the classic psychometric paradigm in risk perception. J. Risk Res. 11(6):735-753. Bronfman, N.C., E.L. Vazquez, V.V. Gutierrez, and LA. Cifuentes. 2008b. Trust, acceptance and knowledge of technological and environmental hazards in Chile. J. Risk Res. 11(6):755-773. Davies, J.C. 1996. Comparing Environmental Risks: Tools for Setting Government Pri- orities. Washington, DC: Resources for the Future. DeKay, M.L., H.K. Florig, P.S. Fischbeck, M.G. Morgan, K.M. Morgan, B. Fischhoff, and K.E. Jenni. 2001. The use of public risk ranking in regulatory development. Pp. 208-230 in Improving Regulation: Cases in Environment, Health, and Safety, P.S. Fischbeck, and R.S. Farrow, eds. Washington, DC: Resources for the Future. DeKay, M.L., P.S. Fischbeck, H.K. Florig, M.G. Morgan, K.M. Morgan, B. Fischhoff, and K.E. Jenni. 2005. Judgment-based risk ranking for food safety. Pp. 198-226 in Toward Safer Food: Perspectives on Risk and Priority Setting, S.A. Hoffmann, and M.R. Taylor, eds. Washington, DC: Resources for the Future. EPA (U.S. Environmental Protection Agency). 1987. Unfinished Business: A Compara- tive Assessment of Environmental Problems. EPA/230/2-87/025. Office of Policy, Planning, and Evaluation, U.S. Environmental Protection Agency, Washington, DC. EPA SAB (U.S. Environmental Protection Agency Science Advisory Board). 1990. Reducing Risk: Setting Priorities and Strategies for Environmental Protection. SAB-EC-90-021. U.S. Environmental Protection Agency Science Advisory Board, Washington, DC [online]. Available: http://yosemite.epa.gov/sab/sabproduct.nsf/28704D9C420FCBC1 852573360053C692/$File/REDUCING+RISK++++++++++EC-90-021_90021_5-11- 1995_204.pdf [accessed Dec. 2, 2008]. Finkel, A.M., and D. Golding. 1995. Worst Things First? The Debate over Risk-Based National Environmental Priorities. Washington, DC: Resources for the Future. Fischhoff, B. 1995. Ranking risks. Risk Health Saf. Environ. 6:189-200. Fischhoff, B. 2006. Cognitive processes in stated preference methods. Pp. 937-968 in Handbook of Environmental Economics, Vol. 2. Valuing Environmental Changes, K.G. Mäler, and J.R. Vincent, eds. Amsterdam: Elsevier. Florig, H.K., M.G. Morgan, K.M. Morgan, K.E. Jenni, B. Fischhoff, P.S. Fischbeck, and M.L. DeKay. 2001. A deliberative method for ranking risks (I): Overview and test- bed development. Risk Anal. 21(5): 913-921. Gutiérrez, V.V., L.A. Cifuentes, and N.C. Bronfman. 2006. The influence of information delivery on risk ranking by lay people. J. Risk Res. 9(6):641-655. HM Treasury. 2004. The Orange Book: Management of Risk-Principles and Concepts. London, UK: Her Majesty’s Stationery Office. October 2004 [online]. Available: http://www.who.int/management/general/risk/managementofrisk.pdf [accessed Dec. 2, 2008].

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Appendix A 173 HM Treasury. 2005a. Managing Risks to the Public: Appraisal Guidance. London, UK: Her Majesty’s Stationery Office. June 2005 [online]. Available: http://www.hm- treasury.gov.uk/d/Managing_risks_to_the_public.pdf [accessed Dec. 2, 2008]. HM Treasury. 2005b. Principles of Managing Risks to the Public. HM Treasury Cabinet Office, London, UK [online]. Available: http://www.hm-treasury.gov.uk/ d/risk_principles_180903.pdf [accessed Dec. 2, 2008]. Jones, K. 1997. A Retrospective on Ten Years of Comparative Risk. Prepared for American Industrial Health Council, Washington, DC, by Green Mountain Institute for Envi- ronmental Democracy, Montpelier, VT. January 24, 1997 [online]. Available: http://heartland.temp.siteexecutive.com/pdf/23157i.pdf [accessed Dec. 2, 2008]. Long, J., and B. Fischhoff. 2000. Setting risk priorities: A formal model. Risk Anal. 20(3):339-352. Minard, R.A. 1996. Comparative risk assessment and the States: History, politics and results. Pp. 23-62 in Comparing Environmental Risks: Tools for Setting Govern- ment Priorities, J.C. Davies, ed. Washington, DC: Resources for the Future. Morgan, K.M., M.L. DeKay, and P.S. Fischbeck. 1999. A multi-attribute approach to risk prioritization. Risk Policy Report 6(6):38-40. Morgan, M.G., H.K. Florig, M.L. DeKay, and P. Fischbeck. 2000. Categorizing risks for risk ranking. Risk Anal. 20(1):49-58. Morgan, K.M., M.L. DeKay, P.S. Fischbeck, M.G. Morgan, B. Fischhoff, and H.K. Florig. 2001. A deliberative method for ranking risks (II): Evaluation of validity and agreement among managers. Risk Anal. 21(5):923-937. Morgan, M.G., B. Fischhoff, L. Lave, and P. Fischbeck. 1996. A proposal for ranking risks within federal agencies. Pp. 111-148 in Comparing Environmental Risks: Tools for Setting Government Priorities, J.C. Davies, ed. Washington, DC: Re- sources for the Future. Morgan, M.G., H.K. Florig, M.L. DeKay, and P. Fischbeck. 2000. Categorizing risks for risk ranking. Risk Anal. 20(1):49-58. Murray, C.J.L., and A.D. Lopez, eds. 1996. The Global Burden of Disease: A Compre- hensive Assessment of Mortality and Disability from Diseases, Injuries and Risk Factors in 1990 and Projected to 2020. Cambridge, MA: Harvard University Press. OGC (Office of Government Commerce). 2008. Management of Risk (M_o_R). Office of Government Commerce, HM Treasury, London, UK [online]. Available: http://www.ogc.gov.uk/guidance_management_of_risk_4441.asp [accessed Dec. 2, 2008]. Palmgren, C.R., M.L. DeKay, P.S. Fischbeck, B. Fischhoff, and M.G. Morgan. 2000. Evaluating a Risk-Ranking Methodology. Society of Risk Analysis Annual Meet- ing Applications of Risk Analysis in Industry and Government, December 3-6, 2000, Washington, DC. UNC. 2008. UNC School of Public Health to help UAE assess environmental health risks. UNC Gillings School of Global Public Health. School of Public Health News: June 9, 2008 [online]. Available: http://www.sph.unc.edu/school_of_pu blic_health_news/unc_school_of_public_health_to_help_uae_assess_environment al_health_risks_7546_1957.html [accessed Dec. 2, 2008]. USACE (US Army Corps of Engineers). 2008. Risk-Informed Decision Framework Ap- pendix, Draft. Louisiana Coastal Protection and Restoration Technical Report. U.S. Army Corps of Engineers, New Orleans District, Mississippi Valley Division. February 2008 [online]. Available: http://lacpr.usace.army.mil/\Report\Draft Ap- pendices\Risk Informed Decision Framework Appendix.pdf [accessed Dec. 2, 2008].

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174 A Risk-Characterization Framework for Decision-Making at FDA WHO (World Health Organization). 2008. The Global Burden of Disease: 2004 Update. Geneva: World Health Organization [online]. Available: http://www.who.int/ healthinfo/global_burden_disease/GBD_report_2004update_full.pdf [accessed Jan. 9, 2009]. Willis, H.H., M.L. DeKay, M.G. Morgan, H.K. Florig, and P.S. Fischbeck. 2004. Eco- logical risk ranking: Development and evaluation of a method for improving pub- lic participation in environmental decision making. Risk Anal. 24(2):363-378. Willis, H.H., M.L. DeKay, B. Fischhoff, and M.G. Morgan. 2005. Aggregate, disaggre- gate, and hybrid analyses of ecological risk perceptions. Risk Anal. 25(2):405-428.

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Appendix A 175 Attachment D ACKNOWLEDGMENT OF REVIEWERS This report has been reviewed in draft form by persons chosen for their diverse perspectives and technical expertise in accordance with procedures ap- proved by the Report Review Committee of the National Research Council. The purposes of the independent review are to provide candid and critical comments that will assist the institution in making its published report as sound as possible and to ensure that the report meets institutional standards of objectivity, evi- dence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative proc- ess. We thank the following for their review of this report: Ann Bostrom, Uni- versity of Washington; Paul Citron, Medtronic, Inc.; Alan M. Garber, Stanford University; Sandra A. Hoffman, Resources for the Future; Robert E. Johnston, University of North Carolina, Chapel Hill; Ralph L. Keeney, Duke University; Harley W. Moon, Iowa State University; Joseph V. Rodricks, ENVIRON; and Brian L. Strom, University of Pennsylvania School of Medicine. Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations, nor did they see the final draft of the report before its release. The review of the report was overseen by the review coordinator, Lauren Zeise, California Environmental Protection Agency, and the review monitor, John C. Bailar, III, University of Chicago. Appointed by the National Research Council, they were responsible for making certain that an independent examination of the report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of the report rests entirely with the committee and the institution.

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