A clinical pathway for the diagnosis of sesame allergy in children

Abstract

Background: Sesame allergy (SA) is a common cause of life-threatening, persistent food allergy, not only in the Middle East and Asia, but increasingly worldwide. Commercially available tests such as extracts for skin testing or specific IgE for sesame or its components in serum, have very limited predictive values. Therefore the diagnosis is dependent on the performance of oral food challenges (OFC), frequently avoided in children, due to time and resource constraints, as well as the risk of anaphylaxis. In the current study we aimed to develop a simple, readily available, clinical tool, able to predict sesame OFC outcomes in children. Methods: Children with a history of SA were evaluated in the outpatient allergy clinic. All children underwent natural sesame OFC, with an additional baked-sesame challenge offered to children with SA. Clinical data were compared between the sesame tolerant (ST) and SA groups. Machine-learning tools were applied, to create a simple, clinically driven, decision tree analysis (DTA), predicting the outcome of sesame OFCs and the diagnosis of SA. Results: One hundred four children, mean age 47.2 months, 58% boys were included, with a high prevalence of additional food allergies, atopic dermatitis, asthma, and rhinitis. Following OFC, 56 (54%) were diagnosed as ST and 48 (46%) SA. Among SA children, 85% were able to consume baked-sesame in equal or higher protein amounts compared to natural sesame paste. Compared to ST, SA children had a tendency towards a higher incidence of allergic rhinitis (5% Vs 17%, p = 0.062), multiple food allergies (3.6% vs 12.5%, p = 0.09) and requiring medical treatment after the initial SA reaction (27% vs 41%, p = 0.022). As a group, skin tests with both commercial and natural tahini paste differed significantly between ST and SA (mean wheal in mm, for extract 4.2 vs 13.4, p < 0.001 and for natural sesame paste 6.7 vs 24.4, p < 0.001), However, the PPV of any individual test was only between 60%–85%. Our exploratory, clinical DTA, predicted OFC outcomes and the presence or absence of Sesame Allergy, with ≥96% positive (PPV) and negative (NPV) predictive values. Conclusion: OFCs remain the gold standard for the diagnosis of Sesame Allergy and are indicated to define ST/SA status even in highly atopic patients with previous immediate allergic reactions to sesame. A decision-tree analysis based on clinical parameters easily available in every allergy clinic, can predict the outcome of sesame OFC in the vast majority of children, increasing the safety and availability of such diagnostic procedures.

Keywords

• Food allergy
• Sesame
• Anaphylaxis
• Skin prick test (SPT)
• Machine learning