. "10 Scientific Principles for Integrating and Evaluating the Available Data." Dietary Supplements: A Framework for Evaluating Safety. Washington, DC: The National Academies Press, 2005.
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Dietary Supplements: A Framework for Evaluating Safety
AMOUNT OF INFORMATION NEEDED TO DRAW A CONCLUSION
GUIDING PRINCIPLE:In the absence of scientific studies designed specifically to test the safety of a dietary supplement, concern for public safety may be raised by the presence of even a few reports of possible safety concerns when viewed together and constituting the weight of available evidence.
Even if there are only one or two convincing reports of safety concerns about a dietary supplement, from either in vitro, animal, or human data, it may not be necessary to gather much additional information to raise concern about the implications for public health. However, in other cases, it may be necessary to assemble several data reports and reach a conclusion about risk based on the totality of available evidence, overall consistency, and biological plausibility of the evidence (a “weight of evidence” approach). In the absence of data on the safety of a specific ingredient, convincing information about safety of chemically or functionally related substances may be used to judge concern.
INTEGRATING INFORMATION
GUIDING PRINCIPLE:Integration of data across different categories of information and types of study design can enhance biological plausibility and identify consistencies, leading to conclusions regarding levels of concern for an adverse event that may be associated with use of a dietary supplement ingredient.
Individual pieces of information from any one of the categories of information (human, in vitro, animal, or related substances data) may sometimes be sufficiently compelling to both exceed a threshold level of concern and to justify focused evaluation or action. In many circumstances, however, data will need to be collated within the same category or across several categories to determine the appropriate level of concern. That is, even if concern raised by one category of data—for example, human data—does not meet a threshold for action, the body of evidence available across several categories may raise the level of concern. In integrating observations across categories of data, consistency and evidence of biological plausibility should raise the level of concern. In other words, available evidence from