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Updated: May 12, 2026

Basophil Activation Test for Allergy Diagnosis
Published on: May 31, 2021
Factors that predict the clinical reactivity and tolerance in children with cow's milk allergy
S Tolga Yavuz1, Betul Buyuktiryaki, Umit M Sahiner
1Faculty of Medicine, Department of Pediatric Allergy and Asthma, Hacettepe University, Ankara, Turkey.
Background:
Specific IgE (sIgE) may be used for the diagnosis of cow's milk allergy (CMA) and as a guide to perform food challenge tests in patients with CMA. The effect of genetic variants on the prognosis of food allergy is largely unknown.
Objective:
To examine the performance of sIgE analysis and the utility of the genetic variants of CD14, STAT6, IL13, IL10, SPINK5, and TSLP in predicting the clinical course in children with CMA.
Methods:
Serum sIgE levels of 94 children who underwent open food challenges and 54 children with anaphylaxis due to cow's milk (CM) were retrospectively analyzed between January 2002 and May 2009. The genetic polymorphisms were determined in 72 children.
Results:
A total of 148 children were followed up for a median of 3.5 years, and 42 of the 94 challenge results were positive. The probability curves with 95% decision points were 2.8 kU/L for younger than 1 year, 11.1 for younger than 2 years, 11.7 for younger than 4 years, and 13.7 for younger than 6 years. Sixty-six children outgrew CMA during follow-up. Children with initial an CM sIgE level less than 6 kU/L outgrew CMA earlier than children with an initial CM sIgE level of 6 kU/L or higher (P < .001). The age of tolerance development for CM was significantly higher in children with the GG genotype at rs324015 of the STAT6 gene compared with those with the AA+AG genotype (2 years [range, 1.5-3.9 years] vs 1.2 years [range, 1.0-2.2 years]) (P = .02).
Conclusion:
The decision points of sIgE obtained in different age groups may help to determine the likelihood of clinical reactivity more precisely. The results suggest that sIgE levels and STAT6 gene variants may be important determinants to predict longer persistence of CMA.
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