Threshold dose for peanut: Risk characterization based upon published results from challenges of peanut-allergic individuals

Food and Chemical Toxicology 47 (2009) 1198–1204

Contents lists available at ScienceDirect

Food and Chemical Toxicology journal homepage: www.elsevier.com/locate/foodchemtox

Threshold dose for peanut: Risk characterization based upon published results from challenges of peanut-allergic individuals Steve L. Taylor a,*, Rene W.R. Crevel b, David Sheffield b, Jamie Kabourek a, Joseph Baumert a a b

Food Allergy Research & Resource Program, Department of Food Science & Technology, University of Nebraska-Lincoln, 255 Food Industry Complex, Lincoln, NE 68583-0919, USA Safety & Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedford, MK44 1LQ, United Kingdom

a r t i c l e

i n f o

Article history: Received 19 November 2008 Accepted 8 February 2009

Keywords: Peanut Allergy Threshold Modeling

a b s t r a c t Population thresholds for peanut are unknown. However, lowest- and no-observed adverse effect levels (LOAELs and NOAELs) are published for an unknown number of peanut-allergic individuals. Publications were screened for LOAELs and NOAELs from blinded, low-dose oral challenges. Data were obtained from 185 peanut-allergic individuals (12 publications). Data were analyzed by interval-censoring survival analysis and three probability distribution models fitted to it (Log-Normal, Log-Logistic, and Weibull) to estimate the ED10. All three models described the data well and provided ED10’s in close agreement: 17.6, 17.0, and 14.6 mg of whole peanut for the Log-Normal, Log-Logistic, and Weibull models, respectively. The 95% lower confidence intervals for the ED10’s were 9.2, 8.1, and 6.0 mg of whole peanut for the Log-Normal, Log-Logistic, and Weibull models, respectively. The modeling of individual NOAELs and LOAELs identified from three different types of published studies – diagnostic series, threshold studies, and immunotherapy trials – yielded significantly different whole peanut ED10’s of 11.9 mg for threshold studies, 18.0 mg for diagnostic series and 65.5 mg for immunotherapy trials; patient selection and other biases may have influenced the estimates. These data and risk assessment models provide the type of information that is necessary to establish regulatory thresholds for peanut. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction Among food allergies, allergic reactions to peanut are one of the most prevalent (Hourihane et al., 2007). Peanut allergies are also frequently severe, and deaths have resulted from the inadvertent ingestion of peanut among peanut-allergic individuals (Bock et al., 2007; Yunginger et al., 1988). Those with peanut allergy are advised to avoid the ingestion of peanuts (Taylor et al., 1986). Exposure to trace amounts of peanuts can be sufficient to elicit allergic reactions at least in some peanut-allergic individuals (Taylor et al., 2002). However, individual threshold doses exist below which those with peanut allergy will not experience allergic reactions (Taylor et al., 2002). Experimentally determined individual thresholds lie between the no observed adverse effect level (NOAEL), the highest dose observed not to produce any adverse effect and the lowest observed adverse effect level (LOAEL), the lowest dose that is observed to produce an adverse effect. However, a threshold dose is often operationally defined as the LOAEL or the minimum eliciting dose (MED) (Taylor and Hourihane, 2008) or the NOAEL. NOAELs and LOAELs can be defined on either an individual basis or a population basis. Individual NOAELs or LOAELs can be determined by clinical * Corresponding author. Tel.: +1 402 472 2833; fax: +1 402 472 5307. E-mail address: [email protected] (S.L. Taylor). 0278-6915/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.fct.2009.02.011

challenge trials. The establishment of individual NOAELs and LOAELs is dependent upon the selection of and spacing between doses selected in the clinical challenge trial design. The population threshold can be theoretically defined as the largest amount of peanut that would not cause a reaction in any individual within the total population of peanut-allergic individuals. Of course, since it is impossible to perform challenge tests on that entire population, the population threshold can be pragmatically defined as the largest dose of peanut that would not cause a reaction when tested clinically in a defined population of peanut-allergic individuals. Knowledge of individual and population-based peanut threshold doses would benefit peanut-allergic consumers, their physicians, the food industry, and public health authorities (Crevel et al., 2008). Food-allergic consumers benefit from knowledge of their own individual threshold because it determines the degree of care that must be exercised in implementation of their avoidance diet. Physicians benefit from the determination of individual thresholds for their patients because such knowledge allows them to provide optimal advice on avoidance diets. The food industry needs information on population threshold levels so that they can institute allergen control programs and labeling policies that will protect food-allergic consumers while allowing them to have access to all foods that are likely to be tolerated. Public health authorities also need information on population thresholds so that

S.L. Taylor et al. / Food and Chemical Toxicology 47 (2009) 1198–1204

they can institute regulatory thresholds that protect the vast majority of the population allergic to any specific food. If the population threshold is to be predictive for the entire population of all peanut-allergic individuals, then a representative population must be evaluated that would be weighted adequately to include both individuals who react to very low amounts as well as their counterparts who require large amounts to provoke a response. Public health and food industry measures to protect peanut-allergic individuals thus require the establishment of population thresholds, but also a description of their distribution in order to characterize the population’s response. Statistically based risk assessment provides the ideal approach to the establishment of a population threshold for allergenic foods including peanut (Threshold Working Group, 2008). The use of such risk assessment approaches requires individual threshold doses from a sufficiently large number of peanut-allergic individuals. This analysis of the clinical literature was conducted to determine if the quantity and quality of published data on individual peanut thresholds was sufficient to allow risk assessment modeling and the prediction of a population-based threshold for peanuts. Several types of clinical studies including diagnostic series (Morisset et al., 2003; Moneret-Vautrin et al., 1995, 1998; Atkins et al., 1985; Peeters et al., 2007), clinical threshold trials (Hourihane et al., 1997; Flinterman et al., 2006; Wensing et al., 2002; Lewis et al., 2005), and immunotherapy trials (Leung et al., 2003; Oppenheimer et al., 1992; Nelson et al., 1997) yielded data on individual LOAELs for peanut among peanut-allergic individuals. The reported LOAELs span a very wide range from 1 mg up to 8–10 g for elicitation of objective symptoms. However, NOAELs are not clearly reported in many of these studies. For purposes of assuring the safety of individual peanut-allergic patients and the population of peanut-allergic patients, knowledge of the NOAEL is critical to risk managers (food industry risk managers, governmental regulatory officials, and physicians). Furthermore, most of these previous studies identify doses that elicited mild objective reactions or both subjective and mild objective reactions. However, challenges in some of these studies were stopped in the majority of patients on the provocation of subjective reactions (Wensing et al., 2002; Peeters et al., 2007). Consensus recommendations generally suggest that challenges proceed to the elicitation of mild objective reactions, although more serious subjective reactions such as abdominal pain are also considered as sufficient to stop further challenges (Moneret-Vautrin et al., 1998; Taylor et al., 2004). Some clinical investigators have used the elicitation of reproducible subjective reactions as the outcome measure in food challenges (Flinterman et al., 2006).

2. Materials and methods The clinical literature was screened for publications providing LOAELs and/or NOAELs on individual peanut-allergic subjects. The literature was contained within a food allergy literature database maintained by the Food Allergy Research & Resource Program at the University of Nebraska; the key words, threshold and peanut, were used to identify publications for consideration. This food allergy literature database has been developed over the past 25 years by screening Current ContentsTM, other literature databases such as Medline, scanning content pages of specialty allergy journals, and cross-referencing of bibliographies of publications to identify all publications relevant to food allergy. A unique key word set has been applied to the publications in the database to make it easily searchable. Individuals in these published studies were deemed allergic to peanuts on the basis of clinical history and other diagnostic tests but had positive oral challenges as part of the published study. Publications were included on the basis of the use of double-blind, placebo-controlled challenges (DBPCFC) starting at low-doses that potentially allowed identification of NOAELs and LOAELs for individual patients. If a publication only presented individual LOAELs but also provided the dosing scheme, the NOAELs for individual patients were discerned using the assumption that all patients were subjected to the published dosing scheme. NOAELs and LOAELs for individual subjects were established for the maximum possible number of individuals from each study even if individual data were not available for all subjects in the particular

1199

study for all types of endpoints. Thus, from some studies, information is available only from a fraction of the subjects investigated. Individual NOAELs and LOAELs were expressed in terms of doses of either whole peanut (mg) or peanut protein (mg) eliciting either subjective or objective symptoms. Objective symptoms included any symptom that would have been discernable to clinical observers, e.g. vomiting, urticaria, rash, angioedema, etc. Subjective symptoms included any symptom that, by its nature, could not be confirmed by clinical observers, e.g. mild oral itching, nausea, etc. Because two different forms of challenge materials were used in the various trials (peanut flour or crushed peanuts), the assumption was made that peanuts contain 25% protein and peanut flour contains 50% protein (Taylor et al., 2002). An Interval-Censoring Survival Analysis (ICSA) approach was chosen to analyze the data (Collett, 1993, Chapter 9). The methodology is appropriate when the exact dose that provokes a reaction in an individual is not known but it is known to fall into a particular interval. Using ICSA, if an individual had an objective reaction at the first dose in a challenge trial, then left-censoring occurred, and the NOAEL was set to zero with the LOAEL set as that first dose. If an individual did not experience an objective reaction after the largest challenge dose, then right-censoring occurred, and the NOAEL was set to that largest challenge dose (if a subjective response occurred at that largest dose, this was also considered as the objective NOAEL), while the LOAEL was set to infinity. In all other cases, interval-censoring occurs bounded by the NOAEL and LOAEL. A statistical software package, the SAS procedure LIFEREG (SAS v9.1), was used to fit parametric models to the intervalcensored data. Because it was highly likely that the intervals for different individuals would overlap due to the use of data from different publications using different dosing schemes in challenge trials, an asynchronous approach is needed such as the one used in the SAS procedure LIFEREG (Radke, 2003). For more details on how this method works see Collett (1993). First, the intervals were redefined by taking all individual NOAEL and LOAEL values and arranging the lower and upper bounds in ascending dose order. The lower bounds were shifted slightly up to break any ties between lower and upper bounds and where a lower and upper bound were adjacent, with lower < upper, this formed a new interval. The step intervals were created using the expectation–maximization algorithm (Turnbull, 1976), that initially assigned equal probabilities to each interval and iteratively updated them until the set of probabilities produced a maximum log likelihood value. Because all the probabilities sum to 1, a known cumulative probability function, such as LogNormal, Log-Logistic or Weibull, could be fit to the data. The cumulative fraction of reactors was then plotted against dose and fitted to three probability distributions in line with the analysis of Crevel et al. (2007). Thus the Log-Normal, Log-Logistic, and Weibull models were evaluated to determine the model providing the best fit to these data. These models were used to estimate the ED10, the dose predicted to provoke reactions in 10% of the peanut-allergic population.

3. Results Twelve publications were identified with potentially useable information as outlined in Materials & Methods on individual NOAELs and LOAELs for peanut (Table 1). These publications were classified as diagnostic series (5, Study A–E, Table 1), clinical threshold (low-dose challenge) trials (4, Study H–K, Table 1), and immunotherapy trials (3, Study L–N, Table 1). Gleaning the desired information from these published studies required deductive reasoning in several cases. Since the oral challenges involved administration of successive, escalating doses at 15–40 min intervals, NOAELs and LOAELs were expressed as cumulative, rather than discrete doses for the purposes of this assessment. 3.1. Diagnostic series In Study A (Morisset et al., 2003), 103 peanut-allergic patients are presented in a diagnostic series but the information on individual patient LOAELs is provided in five dosage intervals making discernment of individual data points impossible for the majority of subjects. However, 4 patients were described as reacting to the first dose of 5 mg; this is therefore the objective LOAEL for these subjects and the objective NOAEL was set at zero for the purposes of the statistical analysis (left-censored). Since 10% of the total number of peanut-allergic subjects (or 10 individuals) were described as reacting within the first dosage interval of <15 mg and four subjects reacted to the first dose of 5 mg, then six additional subjects must have reacted to the 10 mg second dose. These subjects therefore had NOAELs of 5 mg and LOAELs of 10 mg of peanut since crushed peanut was the challenge material. No information on subjective NOAELs or LOAELs was available from this study.

1200

S.L. Taylor et al. / Food and Chemical Toxicology 47 (2009) 1198–1204

Table 1 Published studies yielding NOAELs and LOAELs for peanut-allergic individuals. Study designation

Type of study

Total no. of peanut-allergic patients

No. with objective symptoms (right-censored, left-censored)

No. with subjective responses

References

A B

Diagnostic series Diagnostic series

103 10

10(0, 4)a,b 2(0, 0)

Not known Not known

C D

Diagnostic series Diagnostic series

2 112

2(0, 0) 9(0, 0)

2(0)c Not known

E F G H I J

Diagnostic series Threshold study Threshold study Threshold study Threshold study Immunotherapy trial Immunotherapy trial Immunotherapy trial

22 14 26 40 22 84

22(16, 0) 13(11, 0) 26(20, 0) 40(0, 3) 22(12, 0) 23(8, 1)

22(0) 13(5) 26(0) Not known 17(3) Not known

Morisset et al. (2003) Moneret-Vautrin et al. (1995) Atkins et al. (1985) Moneret-Vautrin et al. (1998) Peeters et al. (2007) Hourihane et al. (1997) Wensing et al. (2002) Lewis et al. (2005) Flinterman et al. (2006) Leung et al. (2003)

4

4(0, 0)

Not known

12

12(0, 1)

Not known

451

185(67, 9)

80(8)

K L Totals a b c

Oppenheimer et al. (1992) Nelson et al. (1997)

Number of right-censored values (NOAEL = highest dose given; LOAEL indeterminate). Number of left-censored values (NOAEL set at zero; LOAEL = lowest challenge dose). Number of right-censored values (NOAEL = highest dose given; LOAEL indeterminate); no left-censored values were found for subjective responses.

Study B (Moneret-Vautrin et al., 1995) originated from the same French clinical center and was a diagnostic report that included information on 10 peanut-allergic individuals. However, information on an individual objective LOAEL is presented for only one of them; the NOAEL for this patient was discerned from the published dosing scheme. For another subject, no reaction occurred at the highest dose of 5 g in the DBPCFC but this subject did react in a single-blind, placebo-controlled food challenge to a 10 g dose of peanut with objective symptoms. The LOAEL for this individual of 10 g was included in the statistical evaluation together with the NOAEL of 5 g. The other subjects were not included because they were diagnosed on the basis of methods where the eliciting dose could not be quantified, including labial challenges (5), a reaction to peanut oil challenge involving an unknown amount of peanut protein (1), or by history or dietary elimination (2). No information on subjective NOAELs or LOAELs was available from this study. Study C (Atkins et al., 1985) presented objective LOAELs for two peanut-allergic subjects and NOAELs for these subjects could be discerned from the published dosing scheme. A third patient reacted positively only to an open peanut challenge administered after no responses to lower, blinded doses; this patient was discounted from the statistical analysis. Study D (Moneret-Vautrin et al., 1998) provides information on clinical diagnostic, oral challenges on 112 peanut-allergic individuals. However, these data are again presented as dosage intervals so that the individual objective LOAELs are only provided for 9 individuals. Objective NOAELs for these nine subjects were discerned on the basis of the published dosing scheme. No information on subjective NOAELs or LOAELs was available from this study. Study E (Peeters et al., 2007) involved 30 peanut-allergic subjects primarily evaluated to determine the correlation between diagnostic parameters and severity of reaction. Subjective LOAELs only were reported for 16 subjects; the doses were taken as the objective NOAELs for the purposes of the statistical analysis with the objective LOAEL being indeterminate (right-censored). Objective LOAELs were reported for 6 subjects and their objective NOAELs could be discerned based upon the published dosing scheme. For the other eight subjects, either no challenge trial was done (5) or no reaction to peanut was observed (3), thus these subjects were not confirmed as peanut-allergic on the basis of challenge results.

3.2. Low-dose challenge (threshold) studies Studies F–I (Hourihane et al., 1997; Wensing et al., 2002; Lewis et al., 2005; Flinterman et al., 2006) were clinical studies aimed at assessing threshold or LOAEL doses. Thus, more complete dosing information was available from these publications. Study F (Hourihane et al., 1997) involved 14 subjects but one reacted only to placebo and was discounted from the statistical analysis. Since placeboes were interspersed with peanut in this challenge study, the placebo response might have been a delayed response to a previous peanut challenge but this cannot be certain. Objective LOAELs and NOAELs were available for only two subjects in this trial since the uppermost dose was 50 mg peanut protein. For the remaining 11 subjects, the objective NOAEL was taken as the cumulative amount of peanut provided in the entire trial (355.72 mg) since objective reactions did not occur even at the uppermost challenge dose. The objective LOAEL for these 11 subjects was therefore indeterminate (right-censored). Subjective NOAELs and LOAELs were available for 8 subjects in this study based on symptoms of the oral allergy syndrome (OAS). Study G (Wensing et al., 2002) provided subjective NOAELs and LOAELs for 26 peanut-allergic subjects. However, an objective NOAEL and LOAEL were provided for only six of these subjects because challenges were terminated based upon the development of subjective symptoms in most cases. For the remaining 20 subjects, the objective NOAEL was taken as the subjective LOAEL and the objective LOAEL was indeterminate. Study H (Lewis et al., 2005) provided objective LOAELs for 40 peanut-allergic individuals. Objective NOAELs were discerned for 37 of the 40 subjects based on the published dosing scheme. Three subjects reacted to the initial dose of 1 mg of peanut flour so the objective NOAEL was set at zero for the purposes of statistical analysis. No information is available with respect to subjective responses in this challenge trial. While Study I (Flinterman et al., 2006) was a clinical threshold trial, it was conducted on 27 patients as part of a diagnostic workup. Thus, 10 subjects had no history of previous peanut allergy although all but 4 subjects were sensitized to peanut on the basis of skin prick tests or serum peanut IgE levels. However, five subjects must be dropped from further statistical consideration because they did not test positive to peanut in the DBPCFC. Objective LOAELs were clearly provided for 11 of the 22 remaining

1201

S.L. Taylor et al. / Food and Chemical Toxicology 47 (2009) 1198–1204

Cumulative Percentage of Responses

Studies J–L (Leung et al., 2003; Oppenheimer et al., 1992; Nelson et al., 1997) were immunotherapy trials primarily aimed at assessing the efficacy of various treatments of peanut allergy. As part of these trials, initial patient threshold doses to peanut were established so that comparisons could be done following the immunotherapy treatment. These initial threshold doses were usable in our analysis. Study J (Leung et al., 2003) evaluated the efficacy of anti-IgE therapy for the treatment of peanut allergy. While a total of 84 patients were included in this study, the data presentation allows discernment of the individual NOAELs and/or LOAELs at baseline for only 23 of these subjects. The overall range of individual threshold doses is provided for each of the four treatment groups in this study. Obviously, at least one patient in each group responded at the lowest dose indicated in the range. In one case, this individual reacted to the initial challenge dose of 0.5 mg of peanut protein (corresponds to 1.0 mg of peanut flour or 2 mg of whole peanut) during the baseline challenge trial; this dose is the objective LOAEL for that patient, and the objective NOAEL is set at zero for statistical analysis purposes. For the other three treatment groups, the lowest dose reactor responded to the 5.0 mg peanut dose so both objective LOAELs and NOAELs can be discerned for these three subjects. In this study, eight individuals assigned to the various treatment groups tolerated the highest dose (2000 mg) of peanut during the baseline DBPCFC. Thus, a cumulative dose of 1943 mg of peanut protein (7772 mg of peanut) was assigned as the objective NOAEL for these patients for statistical purposes, and their objective LOAELs are indeterminate. Additionally, objective NOAELs and LOAELs could be ascertained for 11 further individuals in the various treatment groups. No information is available regarding subjective LOAELs and NOAELs from this study. In Study K (Oppenheimer et al., 1992), a preliminary assessment of the efficacy of rush immunotherapy for the treatment of peanut allergy was done. Data were provided on the initial LOAEL for objective symptoms to peanut in four individuals, and objective NOAELs could be discerned from the dosing scheme. No information on subjective LOAELs or NOAELs was available from this study. In Study L (Nelson et al., 1997), an expanded assessment of the efficacy of rush immunotherapy for the treatment of peanut allergy was conducted. Initial LOAELs for the provocation of objective symptoms were reported for 12 subjects. NOAELs could be ascertained for 11 of these subjects from the published dosing scheme; one subject reacted to an initial dose of 100 mg so the objective NOAEL was set at zero for statistical analysis purposes in this case.

a

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0.1

1

10

100

1000

10000

100000

Dose of Peanut (mg) 95% Confidence Limits

Predicted

Actual

b 100% Cumulative Percentage of Responses

3.3. Immunotherapy studies

No information on subjective LOAELs or NOAELs was available from this study. Three common probability distribution models (Log-Normal, Log-Logistic and Weibull) were fitted to these data (Fig. 1a–c). No formal statistical tests exist to decide which model is the most appropriate distribution to use. Likelihood ratio tests can only be used to compare models based on the same distribution where,

90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0.1

1

10

100

1000

10000

100000

Dose of Peanut (mg) Predicted

Actual

95% Confidence Limits

c 100% Cumulative Percentage of Responses

subjects, and their objective NOAELs can be discerned from the dosing scheme. For a further nine subjects, the objective LOAEL is reported as greater than some dose (>3000 mg in 6 of 8 cases) in the dosing scheme (for 3000 mg, the next dose was an open challenge with 10,000 mg). For these subjects, these doses are actually the objective NOAELs and the objective LOAELs were indeterminate. For the other two subjects, challenges were terminated on the basis of development of subjective responses only. The objective NOAELs were taken as the subjective LOAELs for these two subjects while the objective LOAELs were indeterminate. Subjective LOAELs are provided for 14 of 22 subjects, and their subjective NOAELs could be discerned from the dosing scheme. Five subjects developed objective reactions without first developing subjective responses. For the remaining three subjects, the subjective NOAEL was set at the cumulative dose of peanut provided in the entire trial (8824 mg) since these individuals did not report reactions even at the uppermost challenge dose. For these individuals, the subjective LOAELs were indeterminate.

90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0.1

1

10

100

1000

10000

100000

Dose of Peanut (mg) Actual

Predicted

95% Confidence Limits

Fig. 1. Probability distribution models for individual peanut thresholds (expressed as whole peanut) for peanut-allergic individuals: (a) Log-Logistic, (b) Log-Normal, (c) Weibull.

1202

S.L. Taylor et al. / Food and Chemical Toxicology 47 (2009) 1198–1204

Table 2 ED10 doses for whole peanut as assessed by three probability distribution models. Distribution

ED10

95% CI

Log-Normal Log-Logistic Weibull

17.6 17.0 14.6

9.19, 33.7 8.10, 35.8 5.97, 35.5

for example, one model might drop a parameter such as the intercept. Instead, the residuals produced from fitting each distribution were checked to make sure that there was no over- or under-fitting of the data, especially in the low-dose region. Using these models, the dose predicted to elicit an allergic reaction in 10% of the overall peanut-allergic population can be estimated (ED10 and Table 2) and these ranged from 14.6 mg (95% confidence interval of 5.97 to 35.5 mg) of whole peanut using the Weibull fit to 17.6 mg (95% confidence interval of 9.19 to 33.7 mg) using the Log-Normal. However, given that the principal application of this methodology lay in low-dose estimations, goodness of fit in that part of the dose range is important and on that basis, the Log-Normal distribution appears to fit the lower doses very well (Fig. 1b) and has therefore been used in all further analyses. These models also allow for lowdose extrapolation, for instance the assessment of the ED05 and ED01 and below. However, an insufficient number of data points are available to make these estimates with adequate confidence (Crevel et al., 2007) and predictions in this range would need to be validated, for instance through a prospective cohort study on incidence which included an assessment of exposure. The NOAELs and LOAELs from peanut-allergic individuals were gleaned from three different types of published studies: diagnostic series, threshold studies, and immunotherapy trials. Since sufficient numbers of subjects were identified for all three types of studies, a comparison of the dose distributions for the various groups was conducted (Fig. 2). The shape of the Log-Normal distributions and corresponding ED10’s differed significantly between these groups. The ED10’s ranged from 11.9 mg of whole peanut for threshold studies to 65.5 mg for immunotherapy trials. 4. Discussion Thresholds constitute a critical piece of information in assessing the risk from allergenic foods at both the individual and population levels. Population thresholds in particular can help to assess the

Cumulative percentage of responses

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0.1

1

10

100

1000

10000

100000 1000000

Dose of Peanut (mg) Diagnostic (A-E)

Threshold (F-I)

Immunotherapy (J-L)

Fig. 2. Log-Normal probability distribution models of individual peanut thresholds (expressed as whole peanut) for peanut-allergic individuals in diagnostic studies, threshold studies, and immunotherapy studies.

public health risk and design appropriate food safety objectives to guide risk management. However, determining such thresholds experimentally is fraught with difficulties. To overcome these issues, approaches based on dose distribution modelling and lowdose extrapolation have been described (Bindslev-Jensen et al., 2002; Crevel et al., 2007). Reviews by food safety authorities, while supportive of the concept, have questioned whether enough data existed in order to derive values that could be used operationally (EFSA, 2004; FDA, 2006; Threshold Working Group, 2008). This paper demonstrates that for peanut at least enough valid data can be gleaned from publications to produce a model from which the doses predicted to elicit (mild) reactions (Perry et al., 2004) in 10% of the at-risk population can be determined with reasonable precision. The clinical literature on food challenges was searched and twelve publications were identified which contained useable information on individual NOAELs and LOAELs for peanut-allergic individuals. Only five publications provided useable information on subjective NOAELs and LOAELs involving a total of 80 subjects. Since three of these five publications and 65/80 patients were generated from the clinical allergy group at Utrecht, the Netherlands, further statistical assessment of the subjective thresholds was not performed. The 12 publications did yield objective NOAELs and LOAELs on between 2 and 40 peanut-allergic individuals per study. Useable information was obtained on the individual threshold doses for 185 peanut-allergic subjects from these 12 publications (Table 1). Clinical oral challenge trials involve administering progressively higher doses to the subjects over several hours. Each of these studies used a different dosing scheme with various dosage intervals. An interval-censoring approach is appropriate for data analysis when the exact dose falls within a defined interval between doses. For 109 of these subjects, both the individual NOAEL and LOAEL were published and/or discernable and the precise NOAEL is known to be within the interval between these two doses. In the cases of an additional 67 subjects, the highest dose administered in the challenge trial did not elicit an objective reaction. In these cases, this highest dose is considered as the NOAEL and the LOAEL is set at infinity for the purposes of the interval-censoring survival analysis; this is known as right-censoring. For the final 9 subjects, an objective reaction occurred at the first dose in the dosing scheme. In these cases, this first dose is set as the LOAEL and the NOAEL is set at zero; this is known as left-censoring. Interval censoring survival analysis (ICSA) is an optimal statistical approach to use when the precise threshold dose is known to fall within some interval but its exact value is unknown. An alternative approach would be to use an approximation of the exact eliciting dose by taking either the NOAEL values, the LOAEL values or the mid-point between the two. The problem with this approach is that the uncertainty about the true dose is ignored and the variance is underestimated leading to biased conclusions. This problem is magnified when the interval sizes are larger. A more detailed discussion of the various approaches can be found in Radke (2003). While ICSA allows the use of existing, published data on individual peanut thresholds, several difficulties were encountered. In many cases, only the LOAEL was published and the NOAEL had to be discerned from the dosing scheme. In the case of first dose reactors, the NOAEL is indeterminate and set at zero for statistical analysis. Data from many published diagnostic studies were discounted because the first dose was 400–500 mg of peanut (Sicherer et al., 2000) making the first interval quite large, which would have increased uncertainty around the low-dose estimates of ED, the ones which are of most interest in relation to management of allergen risks. In some cases where the uppermost challenge dose was quite high, the objective NOAEL was assumed to

S.L. Taylor et al. / Food and Chemical Toxicology 47 (2009) 1198–1204

be this highest dose but, in those cases, objective LOAELs were indeterminate and assumed to be infinity. Interestingly, lack of reactivity at the highest challenge dose was more commonly encountered than first dose reactors. Thus, the dosing schemes used in currently available published studies may not provide the ideal range of dosages and intervals. However, since challenge trials are often limited to several hours and the range of individual threshold doses is quite large, practical limitations exist in designing experiments that would ensure the identification of both NOAELs and LOAELs for all subjects. The determination of the ED10 and especially the ED05 and ED01 using statistical modeling would be strengthened if individual NOAELs and LOAELs were available from larger numbers of peanut-allergic subjects; this would be especially true if the dosage range for the challenge trials encompassed low-doses and more frequent dosage intervals (although practical limitations exist to the duration of a clinical challenge trial). The 12 publications used in this analysis included a total of 451 subjects but individual objective NOAELs and LOAELs could only be found or discerned for 185 subjects. Even fewer data points were found for subjective NOAELs and LOAELs. In many studies, the individual data were clearly available to investigators but just not published. Increasing recognition of the value of this information to risk assessment would likely result in it being made more widely available, perhaps as supplementary information filed electronically with the journal publishing the study. Predictions on the whole at-risk population made from dose distribution modeling, such as ED10 values, assume that the individual data points are obtained from a population of peanut-allergic individuals that is representative of the overall population. However, the purpose of the published studies we examined was such that no attempts were made to assure that the selected peanut-allergic subjects were representative and randomly chosen. Indeed, for some of these studies, such efforts would not have been either relevant or possible. Instead, the challenges were performed on subjects available to a particular clinic. This will likely have resulted in systematic bias because the subjects being investigated are those who seek clinical assistance and whose condition would tend to be more severe and difficult to manage. Furthermore, many of the clinics conducting these challenges are referral clinics where such cases would be over-represented. Thus, the published studies may have a bias toward selection of more sensitive and reactive individuals. Furthermore, published studies often have an inherent and almost unavoidable reporting bias toward describing the results of the more interesting, and thus more sensitive, cases in a more thorough fashion. Fig. 2 shows the existence of such biases. The lowest ED10 estimate (11.0 mg whole peanut) was obtained from the individual peanut NOAELs and LOAELs gleaned from the threshold studies (Table 3). Thus, the conclusion could be reached that these clinical investigators included subjects who were likely to be more sensitive on the basis of history and other factors. The highest ED10 estimate (65.5 mg of whole peanut) was obtained from the patients enrolled in the immunotherapy trials (Table 3). These clinical investigators apparently enrolled peanut-allergic subjects with higher NOAELs and LOAELs. While this observation may simply indicate a bias toward selection of less sensitive sub-

Table 3 ED10 doses for whole peanut as assessed by the Log-Normal probability distribution model for three groups of patients. Group

ED10

95% CI

Diagnostic series Threshold Immunotherapy

18.0 11.9 65.5

5.80, 55.8 4.80, 29.8 18.7, 229

1203

jects, the selection may have influenced the efficacy of the immunotherapy trial. Data gleaned from patients reported in diagnostic series resulted in an ED10 estimate of 18.0 mg of whole peanut (Table 3). Knowledge of the distribution of individual threshold doses for peanut for the peanut-allergic population allows comparisons to determine if clinical trials have selected representative groups of subjects. The use of statistical modeling approaches clearly has value for the potential establishment of regulatory population thresholds as noted previously by the US Food & Drug Administration (Threshold Working Group, 2008). The published clinical literature yielded data on the individual threshold doses for peanut in 185 peanutallergic subjects and allowed the determination of the ED10 for peanut with a high level of confidence using three probability distribution models. While the gleaning of these data from the published literature required considerable effort and the resulting dataset contained biases, this effort demonstrates that sufficient data likely exist for peanut to establish regulatory thresholds, which are sufficiently protective of the population at risk. However, the risk assessment approach would benefit from the inclusion of a larger number of data points from group(s) of subjects who are more likely to be clearly representative of the peanutallergic population. Future attempts will be made to obtain individual NOAEL and LOAEL information from larger numbers of peanut-allergic subjects by screening entire data sets from particular clinics. Conflict of interest statement Research funding has been obtained from more than 50 food and food ingredient companies but does not present a conflict of interest for this research. Study sponsors had no involvement. References Atkins, F.M., Steinberg, S.S., Metcalfe, D.D., 1985. Evaluation of immediate adverse reactions to foods in adult patients. II. A detailed analysis of reaction patterns during oral food challenges. J. Allergy Clin. Immunol. 75, 356–363. Bindslev-Jensen, C., Briggs, D., Osterballe, M., 2002. Can we determine a threshold level for allergenic foods by statistical analysis of published data in the literature? Allergy 57, 741–746. Bock, S.A., Munoz-Furlong, A., Sampson, H.A., 2007. Further fatalities caused by anaphylactic reactions to foods, 2001–2006. J. Allergy Clin. Immunol. 119, 1016–1018. Collett, D., 1993. Modeling Survival Data in Medical Research, second ed. Chapman & Hall/CRC Press, Boca Raton, FL. 391pp. Crevel, R.W.R., Briggs, D., Hefle, S.L., Knulst, A.C., Taylor, S.L., 2007. Hazard characterisation in food allergen risk assessment: the application of statistical approaches and the use of clinical data. Food Chem. Toxicol. 45 (5), 691–701. Crevel, R.W.R., Ballmer-Weber, B.K., Holzhauser, T., Hourihane, J.O.B., Knulst, A.C., Mackie, A.R., Timmermans, F., Taylor, S.L., 2008. Thresholds for food allergens and their value to different stakeholders. Allergy 63, 597–609. European Food Safety Authority, 2004. Opinion of the scientific panel on dietetic products, nutrition and allergies on a request from the commission relating to the evaluation of allergenic foods for labelling purposes. EFSA Journal 32, 1–197. FDA/CFSAN (2006) Report prepared by the Threshold Working Group. Approaches to establish thresholds for major food allergens and for gluten in food. . Flinterman, A.E., Pasmans, S.G., Hoekstra, M.O., Meijer, Y., van Hoffen, E., Knol, E.F., Hefle, S.L., Bruijnzeel-Koomen, C.A., Knulst, A.C., 2006. Determination of noobserved-adverse-effect levels and eliciting doses in a representative group of peanut-sensitized children. J. Allergy Clin. Immunol. 117, 448–454. Hourihane, J.O’B., Kilburn, S.A., Nordlee, J.A., Hefle, S.L., Taylor, S.L., Warner, J.O., 1997. An evaluation of the sensitivity of subjects with peanut allergy to very low doses of peanut protein: a randomized, double-blind, placebo-controlled food challenge study. J. Allergy Clin. Immunol. 100, 596–600. Hourihane, J.O’B., Aiken, R., Briggs, R., Gudgeon, L.A., Grimshaw, K.E.C., DunnGalvin, A., Roberts, S.R., 2007. The impact of government advice to pregnant mothers regarding peanut avoidance on the prevalence of peanut allergy in United Kingdome children at school entry. J. Allergy Clin. Immunol. 119, 1197–1202. Leung, D.Y.M., Sampson, H.A., Yunginger, J.W., Burks, A.W., Schneider, L.C., Wortel, C.H., Davis, F.M., Hyun, J.D., Shanahan, W.R., 2003. Effect of anti-IgE therapy in patients with peanut allergy. New Engl. J. Med. 348, 986–993. Lewis, S.A., Grimshaw, K.E.C., Warner, J.O., Hourihane, J. O.’B., 2005. The promiscuity of immunoglobulin E binding to peanut allergens, as determined by Western

1204

S.L. Taylor et al. / Food and Chemical Toxicology 47 (2009) 1198–1204

blotting, correlates with the severity of clinical symptoms. Clin. Exp. Allergy 35, 767–773. Moneret-Vautrin, D.A., Fremont, S., Kanny, G., Dejardin, G., Hatahet, R., Nicolas, J.P., 1995. The use of two multitests fx5 and fx10 in the diagnosis of food allergy in children: regarding 42 cases. Allergy Immunol. 27, 2–6. Moneret-Vautrin, D.A., Rance, F., Kanny, G., Olsewski, A., Gueant, J.L., Dutau, G., Guerin, L., 1998. Food allergy to peanuts in France – evaluation of 142 observations. Clin. Exp. Allergy 28, 1113–1119. Morisset, M., Moneret-Vautrin, D., Kanny, G., Geunard, L., Beaudouin, E., Flabbee, J., Hatahet, R., 2003. Thresholds of clinical reactivity of milk, egg, peanut and sesame in IgE-dependent allergies: evaluation by double-blind or single-blind placebo-controlled oral challenges. Clin. Exp. Allergy 33, 1046–1051. Nelson, H., Lahr, J., Rule, R., Bock, S., Leung, D., 1997. Treatment of anaphylactic sensitivity to peanuts by immunotherapy with injections of peanut extract. J. Allergy Clin. Immunol. 99, 744–751. Oppenheimer, J., Nelson, H., Bock, S., Christensen, F., Leung, D., 1992. Treatment of peanut allergy with rush immunotherapy. J. Allergy Clin. Immunol. 90, 256– 262. Peeters, K.A.B.M., Koppelman, S.J., van Hoffen, E., van der Tas, C.W.H., Jager, C.F.G., Penninks, A.H., Hefle, S.L., Bruijnzeel-Koomen, C.A.F.M., Knol, E.F., Knulst, A.C., 2007. Does skin prick test reactivity to purified allergens correlate with clinical severity of peanut allergy? Clin. Exp. Allergy 37, 108–115. Perry, T.T., Matsui, E.C., Conover-Walker, M.K., Wood, R.A., 2004. Risk of oral food challenges. J. Allergy Clin. Immunol. 114, 1164–1168. Radke, B.R., 2003. A demonstration of interval-censoring survival analysis. Prev. Vet. Med. 59, 241–256. Sicherer, S.H., Morrow, E.H., Sampson, H.A., 2000. Dose-response in double-blind, placebo-controlled oral food challenges in children with atopic dermatitis. J. Allergy Clin. Immunol. 105, 582–586.

Taylor, S.L., Hourihane, J.O’B., 2008. Food allergen thresholds of reactivity. In: Metcalfe, D.D., Sampson, H.A., Simon, R.A. (Eds.), Food Allergy – Adverse Reactions to Foods and Food Additives, fourth ed. Blackwell Publishing, Malden, MA, pp. 82–89. Taylor, S.L., Bush, R.K., Busse, W.W., 1986. Avoidance diets – how selective should we be? New Engl. Reg. Allergy Proc. 7, 527–532. Taylor, S.L., Hefle, S.L., Bindslev-Jensen, C., Bock, S.A., Burks, A.W., Christie, L., Hill, D.J., Host, A., Hourihane, J.O.B., Lack, G., Metcalfe, D.D., Moneret-Vautrin, D.A., Vadas, P.A., Rance, F., Skrypec, D.J., Trautman, T.A., Malmheden Yman, I., Zeiger, R.S., 2002. Factors affecting the determination of threshold doses for allergenic foods: how much is too much? J. Allergy Clin. Immunol. 109, 24–30. Taylor, S.L., Hefle, S.L., Bindslev-Jensen, C., Atkins, F.M., Andre, C., BruijnzeelKoomen, C., Burks, A.W., Bush, R.K., Ebisawa, M., Eigenmann, P.A., Host, A., Hourihane, J.O’B., Isolauri, E., Hill, D.J., Knulst, A., Lack, G., Sampson, H.A., Moneret-Vautrin, D.A., Rance, F., Vadas, P.A., Yunginger, J.W., Zeiger, R.S., Salminen, J.W., Madsen, C., Abbott, P., 2004. A onsensus protocol for the determination of the threshold doses for allergenic foods: how much is too much? Clin. Exp. Allergy 34, 689–695. Threshold Working Group, 2008. Approaches to establish thresholds for major food allergens and for gluten in foods. J. Food Prot. 71, 1043–1088. Turnbull, B.W., 1976. The empirical distribution function with arbitrarily grouped, censored and truncated data. J. Royal Statist. Soc., Ser. B 38, 290–295. Wensing, M., Penninks, A.H., Hefle, S.L., Koppelman, S.J., Bruijnzeel-Koomen, C.A.F.M., Knulst, A.C., 2002. The distribution of individual threshold doses eliciting allergic reactions in a population with peanut allergy. J. Allergy Clin. Immunol. 110, 915–920. Yunginger, J.W., Sweeney, K.G., Sturner, W.Q., Giannandrea, L.A., Teigland, J.D., Bray, M., Benson, P.A., York, J.A., Biedrzycki, L., Squillace, D.L., Helm, R.M., 1988. Fatal food-induced anaphylaxis. J. Am. Med. Assoc. 260, 1450–1452.