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A minimum uncertainty factor of 10 is generally used to account for variation within the population when relying on human data and additional uncertainty factors may be included as appropriate. For example, the Food Quality Protection Act (FQPA) of 1996 requires, in certain cases, a 10-fold factor in addition to any other uncertainty factors to protect infants and children from exposure to pesticides (for information about FQPA see http://www.epa.gov/opppsps1/fqpa/). Similarly, the EPA uses uncertainty factors of 3 for inter-species differences,10 for variability among humans (intra-species variability), 10 for extrapolation from subcronic to chronic exposures, 10 for extrapolation from LOAELs to NOAELS, and 1 to 10 for data deficiencies in safety assessments related to continuous inhalation exposures (U.S. EPA, 2002; Jarabek, 2002). The assignment of uncertainty factors should be based on science but typically will include the application of expert judgment.

3. Data Quality. The FDA Information Quality Guidelines (available at http://aspe.hhs.gov/infoquality/Guidelines/fda.shtml) and the Agency for Healthcare Research and Quality (AHRQ) guidelines on systems for rating the strength of scientific evidence (available at http://www.ahrq.gov/clinic/epcsums/strengthsum.htm) were used in evaluating the scientific data contained in this report (West et al., 2002). The FDA guidelines describe policies and procedures for ensuring the quality of the information disseminated by FDA. In these guidelines, data quality is defined in terms of utility, objectivity, and integrity. Utility is defined as the usefulness of the information to its intended users; objectivity as presentation of the data in an accurate, clear, complete, and unbiased manner; and integrity as protecting the information from unauthorized access or revision. In particular, the guidelines provide transparency standards and ensure clarity. The AHRQ guidelines describe systems for evaluating the strength of scientific studies, including randomized clinical studies. In these guidelines, quality is defined as “the extent to which a study’s design, conduct, and analysis has minimized selection, measurement, and confounding biases.” In addition, the AHRQ guidelines suggest specific factors (called Domains and Elements) that should be considered in evaluating individual studies. These factors were considered in developing the criteria described below.

C. Allergen Thresholds: Evaluation and Findings This section provides an evaluation of the data needed to establish thresholds for the major food allergens. Based on the availability and quality of the data, the Threshold Working Group provides findings that can be applied to establish such thresholds.

  • 1.

    Evaluation of Data Availability and Data Quality

    • a.

      Sensitive Populations. Individuals within an allergic population express a wide

degree of sensitivity to low dose allergen exposures. Moreover, the individuals who react to low dose allergen exposures may also have the most severe reactions following these exposures. Thus, there may be a distinct, highly sensitive population within the general population of food allergic individuals. Because most clinical studies exclude patients who have had previous anaphylactic reactions or who have high specific IgE titers, it is possible that the most sensitive individuals within the allergic population may be systematically excluded from these studies. Therefore, it is possible that the doses

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