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5.7 SUBSTANTIATION OF CLAIMS 5.7.1 FDA’s Evidence‐Based Review System
ОглавлениеFDA’s evidence‐based review system of health claims involves a systematic science‐based evaluation to determine the strength of the scientific evidence to support a proposed claim about a substance–disease relationship. FDA evaluation of the scientific evidence for health claims includes the following steps:
Identify scientific studies that evaluate the substance–disease relationship.
Identify surrogate endpoints of disease risk.
Evaluate human studies.
Assess the methodological quality of the scientific studies.
Evaluate the totality of the scientific evidence.
Assess significant scientific agreement.
As a preliminary matter before evaluating the science, to determine what information is needed to substantiate a claim, one must first identify and understand the meaning of the claim, expressed and implied. Clearly understanding a claim’s meaning is crucial in identifying the appropriate study hypotheses and measurable endpoints needed to substantiate the claim.
Next, a threshold review of the studies and other evidence is needed to determine whether they have a relationship to the claim. Did the study specify and measure the ingredient that is the subject of the claim? For example, a study only measuring carrot consumption will not support a claim about carotene consumption. Did the study specify and measure the affect that is the subject of the claim? That is, an appropriate endpoint needs to be measured to evaluate the effect.
Then the scientific quality of the evidence must be determined. The criteria of scientific quality include the study type, the study population, the study design and conduct (e.g., presence of a placebo control), data collection, statistical analysis, and outcome measures. High‐quality scientific study adequately addresses all or most of the above criteria.
Finally, whether there is adequate evidence to substantiate a claim is based on the strength of the entire body of evidence. Ideally, the evidence has been replicated in independent studies and is supported by the surrounding body of evidence. However, there is no rule on the number of studies needed or what combination of evidence is sufficient to support a claim because of the diverse nature of various studies. The quality and quantity of the studies and their consistency and relevancy matter. Conflicting or inconsistent results raise serious questions as to whether a particular claim is substantiated. All of the evidence must be weighed in totality.
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Guidance for Industry Evidence‐Based Review System for the Scientific Evaluation of Health Claims
CFSAN, FDA (Jan. 2009)
… This guidance document describes the evidence‐based review system that FDA intends to use to evaluate the publicly available scientific evidence for [significant scientific agreement] SSA health claims or qualified health claims on the relationship between a substance and a disease or health‐related condition. This guidance document explains the agency’s current thinking on the scientific review approach FDA should use and is intended to provide guidance to health claim petitioners.
The specific topics addressed in this guidance document are: (1) identifying studies that evaluate the substance/disease relationship, (2) identifying surrogate endpoints for disease risk, (3) evaluating the human studies to determine whether scientific conclusions can be drawn from them about the substance/disease relationship, (4) assessing the methodological quality of each human study from which scientific conclusions about the substance/disease relationship can be drawn, (5) evaluating the totality of scientific evidence, (6) assessing significant scientific agreement, (7) specificity of claim language for qualified health claims, and (8) reevaluation of existing SSA or qualified health claims….
An evidence‐based review system is a systematic science‐based evaluation of the strength of the evidence to support a statement. In the case of health claims, it evaluates the strength of the scientific evidence to support a proposed claim about a substance/disease relationship. The evaluation process involves a series of steps to assess scientific studies and other data, eliminate those from which no conclusions about the substance/disease relationship can be drawn, rate the remaining studies for methodological quality and evaluate the strength of the totality of scientific evidence by considering study types, methodological quality, quantity of evidence for and against the claim (taking into account the numbers of various types of studies and study sample sizes), relevance to the U.S. population or target subgroup, replication of study results supporting the proposed claim, and overall consistency of the evidence. After assessing the totality of the scientific evidence, FDA determines whether there is SSA to support an authorized health claim, or credible evidence to support a qualified health claim….
Before the strength of the evidence for a substance/disease relationship can be assessed, FDA separates individual relevant articles on human studies from other types of data and information. FDA intends to focus its review primarily on articles reporting human intervention and observational studies because only such studies can provide evidence from which scientific conclusions can be drawn about the substance/disease relationship in humans. Next, the agency considers a number of threshold questions in the review of the scientific evidence:
Have the studies specified and measured the substance that is the subject of the claim? Studies should identify a substance that is measurable… .
Have the studies appropriately specified and measured the specific disease or health‐related condition that is the subject of the claim? “Disease or health‐related condition” is defined as damage to an organ, part, structure, or system of the body such that it does not function properly (e.g., cardiovascular disease), or a state of health leading to such dysfunctioning (e.g., hypertension). 21 C.F.R. 101.14(a) (5). Studies should identify a specific measurable disease or health‐related condition by either measuring incidence, associated mortality, or validated surrogate endpoints that predict risk of a specific disease.
For example, cancer is a constellation of more than 100 different diseases, each characterized by the uncontrolled growth and spread of abnormal cells. Cancer is categorized into different types of diseases based on the organ and tissue sites. Cancers at different organ sites have different risk factors, treatment modalities, and mortality risk… . Since each form of cancer is a unique disease based on organ site, risk factors, treatment options, and mortality risk, FDA’s current approach is to evaluate each form of cancer individually in a health claim or qualified health claim petition to determine whether the scientific evidence supports the potential substance–disease relationship for that type of cancer, which would constitute a disease under 21 C.F.R. 101.14(a)(5)….
After considering these threshold issues, FDA categorizes the studies by type.
Intervention Studies
In an intervention study, subjects are provided the substance (food or food component) of interest (intervention group), typically either in the form of a conventional food or dietary supplement. The quality and quantity of the substance should be controlled for. In randomized controlled trials, subjects are assigned to an intervention group by chance. Individual subjects may not be similar to each other, but the intervention and control groups should be similar after randomization. Randomized controlled trials offer the best assessment of a causal relationship between a substance and a disease because they control for known confounders of results (i.e., other factors that could affect risk of disease). Through random assignment of subjects to the intervention and control groups, these studies avoid selection bias—that is, the possibility that those subjects most likely to have a favorable outcome, independent of an intervention, are preferentially selected to receive the intervention. Potential bias is also reduced by “blinding” the study so that the subjects do not know whether they are receiving the intervention, or “double blinding,” in which neither the subjects nor the researcher who assesses the outcome knows who is in the intervention group and who is in the control group. By controlling the test environment, including the amount and composition of substance consumed and all other dietary factors, these studies also can minimize the effects of variables or confounders on the results. Therefore, randomized, controlled intervention studies provide the strongest evidence of whether or not there is a relationship between a substance and a disease.
Furthermore, such studies can provide convincing evidence of a cause and effect relationship between an intervention and an outcome. Randomization, however, may result in unequal distribution of the characteristics of the subjects between the control and treatment groups (e.g., baseline age or blood [serum or plasma] LDL cholesterol levels are significantly different). If the baseline values are significantly different, then it is difficult to determine if differences at the end of the study were due to the intervention or to differences at the beginning of the study. When the substance is provided as a supplement, a placebo should be provided to the control group. When the substance is a food, it may not be possible to provide a placebo and therefore subjects in such a study may not be blinded. Although the study may not be blinded in this case, a control group is still needed to draw conclusions from the study.
Randomized controlled trials typically have either a parallel or cross‐over design. Parallel design studies involve two groups of subjects, the test group and the control group, which simultaneously receive the substance or serve as the control, respectively. Crossover design involves all subjects crossing over from the intervention group to the control group, and vice versa, after a defined time period.
Although intervention studies are the most reliable category of studies for determining a cause‐and effect relationship, generalizing from the studies conducted on selected populations to different populations may not be scientifically valid. For example, if the evidence consists of studies showing an association between intake of a substance and reduced risk of juvenile diabetes, then such studies should not be extrapolated to the risk of diabetes in adults.
Observational Studies
Observational studies measure associations between the substance and disease. Observational studies lack the controlled setting of intervention studies. Observational studies are most reflective of free‐living populations and may be able to establish an association between the substance and the disease. In contrast to intervention studies, observational studies cannot determine whether an observed relationship represents a relationship in which the substance caused a reduction in disease risk or is a coincidence. Because the subjects are not randomized based on various disease risk factors at the beginning of the study, known confounders of disease risk need to be collected and adjusted for to minimize bias. For example, information on each subject’s risk factors, such as age, race, body weight, and smoking, should be collected and used to adjust the data so that the substance/disease relationship is accurately measured. Risk factors that need to be adjusted for are determined for each disease being studied. For example, the risk of cardiovascular disease increases with age; therefore, an adjustment for age is needed in order to eliminate potential confounding.
In determining whether the substance that is the subject of the claim has been measured appropriately, it is important to critically evaluate the method of assessment of dietary intake. Many observational studies rely on self‐reports of diet (e.g., diet records, 24‐hour recalls, diet histories, and food frequency questionnaires), which are estimates of food intake. Diet 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. A food frequency questionnaire is the most common dietary assessment tool used in large observational studies of diet and health. Validated food frequency questionnaires are more reliable in estimating “usual” intake of foods than diet records or 24‐hour recall methods. The questionnaire asks participants to report the frequency of consumption and portion size from a list of foods over a defined period of time. One problem with the dietary intake assessment methods described above is that there may be bias in the self‐reporting of certain foods. For example, individuals who are overweight tend to under‐report their portion sizes and therefore the actual amount of substances consumed is often underestimated. If there are reliable biomarkers of intake of a substance, these biomarkers are often measured rather than using self‐reported intakes….
Well‐designed observational studies can provide useful information for identifying possible associations to be tested by intervention studies. In contrast to intervention studies, even the best‐designed observational studies cannot establish cause and effect between an intervention and an outcome… . [However, observational studies] in some situations, can be support for a substance/disease relationship for an SSA or qualified health claim….
Research Synthesis Studies
Reports that discuss a number of different studies, such as review articles, do not provide sufficient information on the individual studies reviewed for FDA to determine critical elements such as the study population characteristics and the composition of the products used. Similarly, the lack of detailed information on studies summarized in review articles prevents FDA from determining whether the studies are flawed in critical elements such as design, conduct of studies, and data analysis. FDA must be able to review the critical elements of a study to determine whether any scientific conclusions can be drawn from it… . Most meta‐analyses, because they lack detailed information on the studies summarized, will only be used to identify reports of additional studies that may be useful to the health claim review and as background about the substance–disease relationship….
Animal and In Vitro Studies
FDA intends to use animal and in vitro studies as background information regarding mechanisms that might be involved in any relationship between the substance and disease. The physiology of animals is different than that of humans. In vitro studies are conducted in an artificial environment and cannot account for a multitude of normal physiological processes such as digestion, absorption, distribution, and metabolism that affect how humans respond to the consumption of foods and dietary substances. Animal and in vitro studies can be used to generate hypotheses, investigate biological plausibility of hypotheses, or to explore a mechanism of action of a specific food component through controlled animal diets; however, these studies do not provide information from which scientific conclusions can be drawn regarding a relationship between the substance and disease in humans.
C. Identifying Surrogate Endpoints of Disease Risk
Surrogate endpoints are risk biomarkers that have been shown to be valid predictors of disease risk and therefore may be used in place of clinical measurements of the onset of the disease in a clinical trial. Because a number of diseases develop over a long period of time, it may not be possible to carry out the study for a long enough period to see a statistically meaningful difference in the incidence of disease among study subjects in the treatment and control groups.
These are examples of surrogate endpoints of disease risk accepted by the National Institutes of Health and/or FDA’s Center for Drug Evaluation and Research: (1) serum low‐density lipoprotein (LDL) cholesterol concentration, total serum cholesterol concentration, and blood pressure for cardiovascular disease; (2) bone mineral density for osteoporosis; (3) adenomatous colon polyps for colon cancer; and (4) elevated blood sugar concentrations and insulin resistance for type 2 diabetes….
D. Evaluating Human Studies
Under the evidence‐based review approach set out in this guidance, FDA intends to evaluate each individual human study to determine whether any scientific conclusions about the substance/disease relationship can be drawn from the study. Certain critical elements of a study, such as design, data collection, and data analysis, may be so seriously flawed that they make it impossible to draw scientific conclusions from the study. FDA does not intend to use studies from which it cannot draw any scientific conclusions about the substance/disease relationship, and plans to eliminate such studies from further review. Below are examples of questions that the agency intends to consider whether scientific conclusions can be drawn from an intervention or observational study about the substance/disease relationship….
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