Working Group Final Report
Interpretation of Significant Scientific Agreement
in the Review of Health Claims
This document addresses the standard of significant scientific agreement used by the Food and Drug Administration (FDA) to authorize health claims on food labels. It, therefore, focuses on the review of scientific evidence about the relationship between a food substance and reduction of risk of a disease or health-related condition, which, in turn, forms the basis for determination of the existence of significant scientific agreement. The specific topics addressed in this report are: identifying data for review, performing reliable measurements, evaluating individual studies, evaluating the totality of the evidence, and assessing significant scientific agreement. Other aspects of and specific requirements for the health claim authorization process are described in the Code of Federal Regulations, in 21 CFR § 101.14 and 21 CFR § 101.70.
Major steps in the scientific review process for health claims are highlighted in bold-face type. For each specific step, details of the issues that must be considered are provided. Explanatory comment, illustrative discussion points, and examples of applications of criteria or requirements as demonstrated by existing health claim authorization reviews are provided in italics.
The 1990 Nutrition Labeling and Education Act (NLEA) was designed to give consumers more scientifically valid information about the foods they eat (1). Among other provisions, NLEA authorized FDA to allow food labels to carry statements that describe the relationship between food substances and disease or health-related conditions. Such statements are known as "health claims" and may now appear on the labels of foods qualified to bear such claims. The term food "substance" has been interpreted broadly to include a specific food or foods, as well as components of food, whether the food is in conventional food form or in the form of a dietary supplement. Thus, an authorized health claim can be used on both conventional foods and dietary supplements, assuming that the substance in the product and the product itself meet the appropriate standards. Health claims are directed to the general population or designated subgroups (e.g., the elderly). They are intended to assist the consumer in maintaining healthful dietary practices and they may encourage marketing of healthful foods.
To assure the validity of health claims, NLEA required that FDA use a scientific standard to authorize such claims. The standard permits a claim if the "totality of publicly available scientific evidence" supports the claim, and if there is "significant scientific agreement" that the claim is supported by such evidence. According to the legislation, scientific evidence includes results from well-designed studies conducted in a manner that is consistent with generally recognized scientific procedures and principles.
Health claims address the reduction of disease risk. From a legal perspective, they do not involve claims about prevention or treatment of disease; such statements are considered to be drug claims rather than food claims. The scientific criteria used to assess the validity of a reported risk reduction can be no less rigorous than those used to assess the validity of a reported disease prevention and treatment. However, evidence for the reduction of disease risk in the realm of foods and food components is derived by necessity from a broader range of studies. Studies that may be used to support a proposed health claim include not only controlled clinical trials but observational and epidemiological studies.
The NLEA identified 10 substance/disease relationships for initial consideration (1). Of these, significant scientific agreement was determined to exist for eight of the relationships and the use of health claims describing these relationships on food labels was authorized in 1993. The legislation allows that any interested person may petition FDA to issue a regulation regarding a health claim. Additional health claims have been authorized in response to such petitions.
For health claim petitions, the evaluation of data and the resulting decision about authorization of a health claim is conducted via an open process known as notice-and-comment rule making. The review and conclusions are first published as a proposal. Any interested person or organization may then submit written comments and requests for corrections or changes to the proposed findings. All comments are considered by FDA, the proposal is modified, and a final rule is published.
The health claim authorization process, including the interpretation of significant scientific agreement, was the subject of a 2-year Keystone Center dialogue among representatives from academia, industry, consumer groups, and government. The dialogue and resulting report affirmed the principles and approach used to authorize health claims (2). Based on the Keystone recommendations, an FDA Food Advisory Committee (FAC) working group has been developing a guide for preparing petitions for health claims. In response to the recent decision of the Court of Appeals for the District of Columbia in the case of Pearson v Shalala that required more guidance be provided on significant scientific agreement, the efforts of the FAC working group have shifted to focus on the scientific review of data for health claims and the interpretation of the significant scientific agreement standard.
The scientific review process for health claims is comprehensive and focuses first on review of individual studies. After relevant, good quality studies are identified and their strengths and weaknesses summarized, a more comprehensive review is conducted based on the body of evidence as a whole. Considerations in the scientific review of health claims are detailed below.
The standard of scientific validity for a health claim requires that 1) the totality of the publicly available evidence supports the claim, and 2) there is significant scientific agreement among qualified experts that the claim is valid.
A health claim must be based on the totality of publicly available data. Because of the limitations of the various research methods that can be used to study substance/disease relationships, it is not possible to specify the type or number of studies needed to support a health claim. In addition, each relationship involves a unique set of confounders (see discussion below) and measurement issues.
Sound science in research design and measurement -- which, in turn, provides the answers to the questions that need to be addressed concerning the relationship -- "drives" the decision to authorize health claims, not the specific type or number of studies. This point is illustrated graphically in Figure 1, which shows the number and nature of the human studies evaluated in determining the validity of certain of the initial health claims evaluated during the 1990-1992 review and claims for which petitions were submitted. The types of studies considered varied greatly among authorized claims.
A. Identifying Data for Review
The initial step is to identify all relevant studies.
The types of studies considered in a health claim review may range from human studies to in vitro laboratory investigations. Most clinical and epidemiological studies of humans can be divided into interventional studies and observational studies.
In an interventional study, the investigator controls whether the subjects receive an exposure or an intervention whereas in an observational study, the investigator does not have control over the exposure or the intervention. In general, interventional studies provide the strongest evidence for an effect of treatment.
Regardless of the inherent strengths and weaknesses of the study design, the overall quality of each individual study is paramount in assessing its contribution to the weight of the evidence for the proposed substance/disease relationship. A well-designed and conducted observational study is more persuasive and should be accorded greater weight than a poorly designed and conducted interventional study.
The "gold standard" of interventional studies is the randomized controlled clinical trial.
In a randomized controlled trial, subjects similar to each other are randomly assigned either to receive the intervention or not to receive the intervention. As a result, subjects who are most likely to have a favorable outcome independent of any intervention are not preferentially selected to receive the intervention being studied (selection bias). Bias may be further reduced if the researcher who assesses the outcome does not know which subjects received the intervention (blinding). Such studies are not an absolute requirement to permit authorization of a health claim but are often given the most weight and can provide the most persuasive evidence. In theory, a single, large, well-conducted and controlled clinical trial could provide sufficient evidence to establish a substance and disease relationship.
Interventional studies for foods may differ from those for drugs. Unlike drug studies, food interventional trials may have additional confounders secondary to using a food substance as the intervention (see discussion below). In addition, it may not be possible to use a placebo control group for food studies and subjects in such studies may not be blinded to the intervention. As a result of the greater likelihood for confounders and bias, interventional studies with foods may generate data that has less certainty than data from drug interventional studies.
Although interventional studies are the most reliable category of studies for determining cause-and-effect relationships, generalizing from selected populations often presents serious problems in the interpretation of such studies. Furthermore, in some cases, such as with cancers of different sites, interventional dietary studies are not feasible because diseases with lower frequency of occurrence, such as rare forms of cancer, require very large study samples to detect an effect. Moreover, there frequently are long delays from dietary exposure to onset of disease, often 20 to 30 years. Therefore, the scientific evidence supporting a substance/disease relationship may have to be derived wholly or in part from observational studies.
There is no universally valid method for weighing categories of studies. However, in general, observational studies include, in descending order of persuasiveness, cohort (longitudinal) studies, case-control studies, cross-sectional studies, uncontrolled case series or cohort studies, time-series studies, ecological or cross-population studies, descriptive epidemiology, and case reports.
Observational studies may be prospective or retrospective. In prospective studies, investigators recruit subjects and observe them prior to the occurrence of the outcome. In retrospective studies, investigators review the records of subjects and interview subjects after the outcome has occurred. Retrospective studies are usually considered to be more vulnerable to bias and measurement error but are less likely to suffer from the subject selection bias that may occur in prospective studies.
A common weakness of observational studies is the limited ability to ascertain the actual food or nutrient intake for the population studied. Observational data are also generally restricted to identifying associations between food substances and health outcomes, rather than the cause of the relationship.
The role of "research synthesis" studies, including meta-analysis, in the review of data for health claims is as yet unresolved.
The appropriateness of such analytical techniques to establish substance/disease relationships is not known. This is especially true when observational data are entered into meta-analyses. Discussions on the topic have been published (3-6), and there are on-going efforts to identify criteria and critical factors to consider in both conducting and using such analyses, but standardization of this methodology is still emerging. Therefore, in general, such analyses serve as supporting evidence rather than as primary evidence. To date, while meta-analyses have been reviewed as part of the health claim authorization process, no health claims have been authorized on the basis of meta-analysis studies alone.
Although human studies are weighted most heavily in the evaluation of evidence on a diet/disease relationship, data from animal model and in vitro (laboratory) studies also can be used to support a substance/disease relationship.
Lacking any data from human studies, animal and in vitro studies alone would not adequately support a diet and disease association. Although both types of studies permit greater control over variables, such as diet and genetics, and permit more aggressive intervention, each suffers from the uncertainties of extrapolating to clinical effects in humans. However, these studies can be useful in providing information on the mechanism of action of a food substance and the process that causes a disease or health-related condition. Animal and in vitro studies should be considered when there are problems designing interventional studies or in the absence of an appropriate biomarker. If such studies are used, they are subjected to the same kind of assessment as the human studies. In the case of animal studies, the consistency of the demonstrated association between a substance and the disease or health-related condition is important when considering whether evidence from such studies supports a health claim. Thus, the strongest animal evidence would be based on data derived from studies on appropriate animal models, on data that have been reproduced in different laboratories, and on data that give a statistically significant dose-response relationship.
B. Performing Reliable Measurements
Appropriate measurement is a key factor in the review of data for health claims.
Assessing the effects of diet on human health is limited by the use of biomarkers, the difficulty identifying and measuring the food substance that provides the effect, the difficulty of accurately measuring dietary intake, and the difficulty distinguishing the effects of diet on a chronic disease and those of other variables, such as weight change, physical activity, or environmental factors.
Because a number of the diseases associated with dietary factors are diseases that develop over a period of many years (chronic diseases), a person may not show outward signs or symptoms of a disease at a particular stage of the illness even though that person has the disease. For example, individuals may have deposits of fat and other material accumulating in the arteries to their hearts (athersclerotic/coronary heart disease) and not experience any symptoms until years later when they suffer a heart attack. Therefore, scientists seek to identify "biomarkers" (surrogate markers) for the presence or risk of disease.
A biomarkers is a measurements of a variable related to a disease that may serve as a predictor of developing that disease. Biomarkers are parameters that infer the presence or risk of a disease rather than being a measure of the disease itself. The scientific standard used for the health claim review process does not rely on a change in a biomarker as a measurement of the effect of a dietary factor and a disease unless there is evidence that altering the parameter can affect the risk of developing that disease or health-related condition. This is the case for serum cholesterol in that high levels are generally accepted as a predictor of risk for coronary heart disease and there is evidence that decreasing high serum cholesterol can decrease that risk. Therefore, the evaluation of whether decreasing the intake of dietary fat reduces the risk of developing heart disease took into account many studies that assessed changes in serum cholesterol, specifically LDL-cholesterol, rather the development of heart disease per se. For the existing authorized health claims, acceptable biomarkers are LDL-cholesterol levels for coronary heart disease, measures of bone mass for osteoporosis, and measures of blood pressure for hypertension.
The measurement of a food substance centers on the following questions: 1) What was measured? and 2) How does the measured substance relate to the subject of the health claim?
Studies that examine dietary components often focus on the intake of the substance of interest as part of a food or a total diet, or may infer intake as part of post-hoc evaluations of the data. Therefore, isolating the effect of the substance can be a critical consideration in authorizing a health claim. Common difficulties involve separating the effect of the food substance from the food itself, or the use of measures that reflect heterogeneous or poorly defined food substances. Without evidence that the substance, rather than the overall diet or specific foods in the diet, is responsible for the benefit, the linkage between the substance and the disease cannot be established.
During evaluations of the initial 10 substance/disease relationships in 1990-1992, this principle was paramount. In the case of claims related to omega-3 fatty acids, fiber, and antioxidant vitamins, there was considerable measurement overlap between the food containing the substance and the substance itself, or there were concomitant changes in other dietary components. Both folic acid and fiber were poorly defined and/or heterogeneous mixtures as measured in research available at the time of the initial health claim review. For example, as noted during the health claim authorization process for fiber and heart disease, the objective of the protocols of many studies was to evaluate the effectiveness of relatively large amounts of a single type of food or fiber source rich in soluble fiber (e.g., baked beans), rather than to examine total soluble dietary fiber intakes or to specifically identify the chemical and physical characteristics of soluble fiber that are most effective in lowering blood cholesterol levels. Thus, the effects could not be attributed to the fiber. Moreover, by adding large amounts of foods to diets (e.g., 1-2 cups of baked beans), these dietary changes were often accompanied by lower calorie intakes with resultant weight loss, which has an independent impact on the risk of developing heart disease.
Measurement issues generally focus on food substances, but the principles also apply when the substance of interest is a food. While a food can be the subject of a health claim, existing experience is that the subject is more likely to be a group of foods, such as fruits, vegetables, and grains which have been associated with a reduced risk of heart disease and of cancer. This identification, and consequently measurement, of a food group is, in turn, most likely to occur because it is not possible to identify and, therefore, measure a particular component of these foods responsible for the benefit. Nonetheless, in theory, it would be possible that a unique combination of nutrients or other substances in a single food could be the subject of a health claim. To date, this has not occurred.
Attention must be paid to how dietary intake is measured in the studies reviewed. Each method has its strengths and weaknesses. No one method is adequate for every purpose.
Dietary intake assessment methods include food records, 24-hour recalls, and diet histories. Food records are based on the premise that food weights provide an accurate estimation of food intake. Subjects weigh the foods they consume and record those values. The 24-hour recall method requires that subjects describe which foods and how much of each food they consumed during the prior 24-hour period. Diet histories use questionnaires or interviewers to estimate the typical diet of subjects over a certain period of time. For a more detailed description of these methods and their strengths and weaknesses, see Diet and Health (7).
Scientific studies provide the means to identify which effects on a disease or health-related condition result from the consumption of a particular food substance and which effects are the products of other factors. Evaluating the conclusions of a study requires an assessment of both the study design and conduct of the study as well as the methods used to interpret the data obtained from the study.
C. Evaluating Individual Studies
The evaluation of study design, protocol, measurement, and statistical issues for individual studies serves as the starting point from which the overall strengths and weaknesses of the data will be determined and the weight of the evidence assessed.
The review of individual studies on substance/disease relationships is standardized as much as possible and generally follows the approaches outlined in the Guide to Clinical Preventive Services (8) and Diet and Health (7).
The persuasiveness of a study depends on the quality of the study.
Evaluation of the quality of individual studies on substance and disease relationships begins with a consideration of the inherent strengths and weaknesses of various study designs. The three most important measures of the quality of a study are design, conduct, and analysis and interpretation.
Certain study designs tend to be more persuasive because they are less subject to bias and measurement error.
The susceptibility of research data to bias and confounding depends on several factors including the methods used to choose subjects and to measure outcomes, the use of a comparison (control) group, and whether the study was conducted retrospectively or prospectively. Confounders are factors associated with the disease in question and the intervention, but do not cause the measured outcome.
Several aspects of substance/disease relationships may give rise to confounders. Foods are rarely composed of a simple mixture of chemical constituents. The addition of a nutrient to a diet, or an increase in total daily intake of that nutrient, may have unintended effects. The added nutrient may displace other nutrients in the diet. Therefore, it may be difficult to ascertain whether the health outcome is the result of the added nutrient or the related changes on the original diet. For example, "total diet" was a confounder in a number of studies used to support a claim that lowering of dietary saturated fat intake and resultant decreases in serum LDL-cholesterol led to a reduced risk of coronary heart disease. Diets low in fat can result in a lower-calorie intake and in turn weight loss. Since weight loss per se can reduce levels of LDL-cholesterol, the benefit could not be attributed to the lack of the food substance (saturated fat), but may have been related to the total diet. Nonetheless, sufficient studies that did control for such related factors were available and there was adequate evidence to establish a relationship between diets low in saturated fat and cholesterol and reduced risk of heart disease. Other potential confounders include variability in the quantity or quality of the food substance being administered.
Criteria that are considered in assessing the quality of individual studies of substance/disease relationships include the following:
Were the specific questions to be answered by the study clearly described at the outset?
Was the methodology used in the study clearly described and appropriate for answering the questions posed by the study?
Was the duration of the study intervention or follow-up period sufficient to detect an effect on the outcome of interest?
Were potential confounding factors identified, assessed, and/or controlled?
Was subject attrition (subjects leaving the study before the study is completed) assessed, explained, and reasonable?
Was the sample size large enough to provide sufficient statistical power to conclude that the absence of an effect is not due to chance?
Was the study population representative (for factors such as age, gender distribution, race, socioeconomic status, geographic location, family history, health status, and motivation) of the population to which the health claim will be targeted?
Were criteria for inclusion and exclusion of study subjects clearly stated and appropriate?
Were recruitment procedures that minimized selection bias used?
For controlled interventions, were subjects randomized? If matching was employed to assign the subjects to control and treatment groups, were appropriate demographic characteristics and other variables used for the matching? Was randomization successful in producing similar control and intervention groups?
Were analytical methodology and quality control procedures to assess dietary intake adequate?
Was the dietary intervention or exposure well defined and appropriately measured? (See discussion above.)
For intervention studies, was an appropriate (effective) level of intake for the food substance of interest planned, monitored, and achieved?
Were the background diets to which the test substance was added, or the control and interventional diets, adequately described, measured, and suitable?
Was a "lead-in" period employed for dietary interventions? (Because changes in the diet may induce compensatory metabolic changes, the effect of an intervention should be measured after stabilization has occurred, i.e., a lead-in period.)
In studies with cross-over designs, was there an appropriate "wash-out" period (period during which subjects do not receive an intervention) between dietary treatments? (Lack of a sufficient wash-out period between interventions may lead to confusion as to which intervention produced the health outcome.)
Were the form and setting of the intervention representative of the "real world?"
Were other possible concurrent changes in diet or health-related behavior (weight loss, exercise, alcohol intake, smoking cessation) during the study that could account for the outcome identified, assessed, and/or controlled?
Were the health, intermediate, or surrogate (biomarker) outcomes well defined and appropriately measured? (Intermediate markers are measures that are predictive for establishing a relationship to a disease.) If biomarkers were measured, has their relevance to health outcomes been validated?
Were efforts made to detect harmful as well as beneficial effects? (Although foods are generally considered safe, extracting or concentrating a food substance may render it injurious to health.)
Were appropriate statistical analyses applied to the data?
Was "statistical significance" interpreted appropriately? (For example, differences between groups that are not statistically significant should be described as not demonstrating a difference rather than as showing a trend.)
Were relative and absolute effects distinguished?
As part of the review process, the individual studies are summarized for the comprehensive review by means of summary tables. The creation and publication of such summary tables not only organizes and guides the comprehensive review, it assists in making the process of authorizing a health claim more transparent.
D. Evaluating the Totality of the Evidence
The totality of the evidence must support the claim.
After relevant, good quality studies are identified and their strengths and weaknesses assessed and summarized, a more comprehensive review is conducted based on the body of evidence as a whole. The evaluation of the totality of the evidence providing the basis for the health claim is objective. Conclusions regarding the association between nutritional exposures or interventions and outcomes must be specific to the identified studies and the interpretation limited to the research conducted.
A classic set of reviews that demonstrate the process for evaluating substance/disease relationships is the work conducted by The Task Force on The Evidence Relating Six Dietary Factors to the Nation's Health (10). Its approach incorporated the standard principle that the strength of evidence associating a nutritional "exposure" with a health outcome depends not only on the quality of the individual studies but on the overall "grade" or assessment of the evidence taken together, the number of studies, consistency of results, and the magnitude of effects.
The strength of evidence that exposure to a particular food substance is associated with a health outcome depends on several factors.
Both the design category and the quality of the research methodology must be considered together. Various coding and scoring schemes have been devised to systematize this process. The U.S. Preventive Services Task Force's grading system assigns a letter code to rate the quality of the evidence (8). Other groups have developed systems that score a study quantitatively, assigning points for different aspects of design quality and performance (11). However, although both study design codes and quantitative scores are appropriate for rating individual studies, they do not adequately describe the evidence as a whole. For example, these methods do not capture the number of studies or consistency of findings. At present, a universally applicable system for evaluation of the evidence as a whole is not available.
The number of studies required to be persuasive is often inversely related to the overall class of evidence available. Simply counting the studies with positive results without regard for their individual quality is an inadequate approach to assessing the overall strength of the evidence.
Conflicting results do not disprove an association (because elements of the study design may account for the lack of an effect in negative studies) but do tend to weaken confidence in the strength of the association. In general, the greater the consistency, the more likely a health claim will be authorized. However, repetition of a poorly designed study does not add to the consistency or quality of the evidence.
Evidence of an association does not, however, prove cause and effect. An association of variables only indicates that they occur together but not that one causes the other. Therefore, another step in the process of a health claim review is to determine the strength of the evidence for a causal relationship.
A causal relationship exists when data show that the consumption of a substance increases or decreases the probability of developing or not developing a particular disease or health-related condition. A causal relationship can be inferred through strength of association, consistency of association, independence of association, dose-response relationship, temporal relationship, effect of dechallenge, specificity, and explanation by a pathogenic mechanism (biological plausibility). Strength of association, dose-response relationship, and temporal relationship may be used in the evaluation of the totality of the evidence. Although these features strengthen the claim that a substance contributes to a certain health outcome, they do not prove that eating more or less of the substance will produce a clinically meaningful outcome.
When performing the comprehensive review, the operative analysis is whether the weight of the evidence supports the existence of a causal relationship between the substance and the disease or health condition that is the subject of a proposed claim. Put simply, as a threshold matter that must be addressed prior to consideration of significant scientific agreement, does the evidence in support of the claim outweigh the evidence against the claim?
E. Assessing Significant Scientific Agreement
There must be significant scientific agreement among qualified experts.
Congress required that there be significant scientific agreement among qualified experts before FDA can authorize a health claim. Significant scientific agreement refers to the extent of agreement among qualified experts in the field. Significant scientific agreement is a point in the process of scientific discovery that occurs between the stage of emerging science, where data and information permit an inference, and the final endpoint of consensus within the relevant scientific community that the inference is valid.
It is important to recognize that significant scientific agreement is not consensus, but that it represents considerably more than an initial body of emerging evidence. Because each situation may differ with the nature of the claimed substance/disease relationship, it is necessary to consider both the extent of agreement and the nature of the disagreement on a case-by-case basis. If scientific agreement were to be assessed under any specific quantitative or rigidly defined criteria, the resulting inflexibility could cause some valid claims to be disallowed where the disagreement, while present, is not persuasive.
Although consensus is not required to demonstrate significant scientific agreement, there is considerable potential for incorrect conclusions if only emerging science is used to authorize health claims.
This is best illustrated by the body of evidence for the association between beta-carotene and cancer risk. At the time of the health claim review, no results from relevant clinical trials had been reported. However, human epidemiological studies were available, as well as laboratory data for mechanistic theories on how beta-carotene might provide a risk reduction effect. While there was strong evidence that high intakes of fruits and vegetables rich in carotenoids were associated with a reduced risk of developing cancer, it was unclear whether the component(s) of fruits and vegetables responsible for reducing the effect were beta-carotene, other carotenoids, or some other compound(s). However, animal studies strongly pointed to a positive effect of beta-carotene in lowering the frequency and severity of experimental cancer induced in animals. The review concluded, nonetheless, that existing evidence was inconclusive and significant scientific agreement did not exist; the animal studies could not be applied directly to humans because the type and amount of carcinogen exposure in the experimental conditions were not similar to human exposure. The decision was further supported when a randomized, controlled trial in Finland tested the ability of antioxidant vitamins, including beta-carotene, to prevent the development of lung cancer in high-risk Finnish men with a history of smoking (9). The unexpected outcome was a significant increase in the rate of cancer among the beta-carotene supplemented group. This experience has emphasized the importance of requiring a threshold of evidence before agreement can be reached concerning the validity of a health claim.
Figure 2 provides a graphical representation of the interplay of considerations that contribute to determining if the standard of validity for a health claim has been met. It illustrates the manner in which evaluations of the various types and amounts of data that may exist for a substance/disease relationship are combined to assess the overall strength and consistency of the scientific evidence to lead to significant scientific agreement. The schema shows that a body of evidence about the claim must exist, and that the weight of the evidence must support the claim, before significant scientific agreement can be reached. This schema also recognizes that the standard should produce a high level of confidence in the validity of the claim and that the standard should be objective, flexible, and responsive.
In order for qualified experts to reach an informed opinion regarding the claim, the data and information that pertain to the claim must be available to the relevant scientific community.
The usual mechanism to show that the evidence is available to qualified experts is that the data and information are published in peer-reviewed scientific journals. However, not all the data need be published. Evidence also can be made available through other means, such as scientific meetings. FDA reviews information that is not publicly available as long as that information is placed in the public domain at the time the agency takes action on a health claim petition. However, the value of an expert's opinion will be limited if he/she did not have access to all the evidence.
When determining whether there is significant agreement, FDA takes into account the viewpoints of qualified experts outside the agency.
Significant scientific agreement can be supported based on an objective and disinterested review of:
1) multiple well-designed studies from various researchers when results consistently and strongly support the claim, 2) publications that critically summarize data and information in the secondary scientific literature, such as authoritative review articles, textbooks, and compendia; 3) documentation of the opinion of an "expert panel" that is specifically convened for this purpose by a credible, disinterested body; or 4) the opinion or recommendation of an authoritative body such as the National Academy of Sciences (NAS), the Committee on Nutrition of the American Academy of Pediatrics (AAP), the American Heart Association (AHA), NIH task forces, and others.
References
1. Public Law 101-553, 104 Stat. 2353 (codified at 21 USC ' 343 (1994). Nutrition Labeling and Education Act. November 8, 1990.
2. The Keystone National Policy Dialogue on Food, Nutrition, and Health: Final Report. Keystone, CO: Keystone Press, 1996.
3. Sacks HS, Berrier J, Reitman D, Ancona-Berk VA, Chalmers TC. Meta-analyses of randomized controlled trials. N Engl J Med 1987;316:450-455.
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7. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Report of the US Preventive Services Task Force: Guide to Clinical Preventive Services. 2nd ed. Washington, DC: Office of Public Health and Science, April, 1989.
8. National Research Council. Diet and Health: Implications for Reducing Chronic Disease Risk. Washington, DC: National Academy Press, 1989.
9. Albanes D, Heinonen OP, Huttunen JK, Taylor PR, Virtamo J, Edwards BK, Haapakoski J, Rautalahti M, Hartman AM, Palmgren J, et al. Effects of alpha-tocopherol and beta-carotene supplements on cancer incidence in the Alpha-Tocopherol Beta-Carotene Cancer Prevention Study. Am J Clin Nutr 1995;62(6 Suppl):1427S-1430S.
10. Ahrens EH, Connor WE, eds. Symposium: Report of the Task Force on he Evidence Relating Six Dietary Factors to the Nation's Health. Am J Clin Nutr 1979;23(suppl):2621-2748.
11. Mohar D, Jadad AR, Tugwell P. Assessing the quality of randomized controlled trials: current issues and future directions. Int J Technol Assess Health Care 1996;12:125-208.
This document was issued in June 1999.
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