Changes in Immunologic Indicators During Allergen-Specific Immunotherapy for Allergic Rhinitis and Determinants of Variability: A Systematic Review and Meta-analysis of Randomized Controlled Trials

• Published in: American Journal of Rhinology & Allergy 2021-11, Vol.35 (6), p.910-922
• Main Authors: Jiang, Zihan, Xiao, Hao, Liu, Shixi, Meng, Juan
• Format: Article
• Language: English
• ISSN: 1945-8924; 1945-8932
• DOI: 10.1177/1945892421999649

Background To date, there are no generally recognized biomarkers for allergen immunotherapy (AIT) and even the changes in immunological indicators during AIT are inconsistent in different publications. Objective This study was conducted to quantify the immunological changes that occur during AIT and identify the determinants of heterogeneity. Methods Randomized controlled trials of AIT published in the past 10 years were searched in Medline, Embase and Cochrane CENTRAL. Data on immunological indicators were extracted, and the characteristics of the included studies were collected. Meta-analysis and meta-regression were conducted for each indicator. The study was registered on the PROSPERO website (CRD42020176127). Results We reviewed 1898 studies. Forty-six studies met the inclusion criteria, and 31 studies were included in the quantitative analyses. Subset analyses by time demonstrated that serum allergen-specific IgE (sIgE) of AIT patients increased in the first 12 months, then decreased and became slightly lower than that of control patients. Allergen-specific IgG4 (sIgG4) was elevated in the AIT group during and after treatment. IgE-blocking factor (IgE-BF) was increased and IgE-facilitated allergen binding (IgE-FAB) was reduced in AIT patients. Both of them of the 2 factors were associated with clinical efficacy in the multivariate regression analysis. sIgE/sIgG4 decreased in AIT patients, while there was no change in total IgE. Conclusion The levels of serum sIgE and sIgG4 during AIT showed a time-dependent pattern. IgE-BF and IgE-FAB should be further investigated as biomarkers for predicting and monitoring AIT efficacy.