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[Chinese expert consensus on the evaluation of allergen-specific immunotherapy outcomes(Wuhan, 2025)].

过敏原 变应原免疫治疗 免疫疗法 医学 免疫学 过敏 免疫系统
作者
Yuqin Deng,Luo Xi,Zhuofu Liu,Shuguang Sun,Jing Ye,Tiansheng Wang,Jianjun Chen,Meiping Lu,Yao Yin,Ying Wang,Wei Zhou,Bei Liu,Qingxiang Zeng,Yuanteng Xu,Qintai Yang,Yucheng Yang,Feng Liu,Chengli Xu,Yanan Sun,Haiyu Hong
出处
期刊:PubMed 卷期号:39 (11): 1075-1085
标识
DOI:10.13201/j.issn.2096-7993.2025.11.015
摘要

Allergen-specific immunotherapy(AIT) remains the only therapeutic approach with the potential to modify the natural course of allergic rhinitis(AR). Nevertheless, considerable inter-individual variability exists in patients'responses to AIT. To facilitate more reliable assessment of treatment efficacy, the China Rhinopathy Research Cooperation Group(CRRCG) convened young and middle-aged nasal experts in China to formulate the present consensus. The recommended subjective outcome measures for AIT comprise symptom scores, medication scores, combined symptom and medication scores, quality-of-life assessments, evaluation of disease control, and assessment of comorbidities. Objective indicators may supplement these measures. Currently available objective approaches include skin prick testing, nasal provocation testing, and allergen exposure chambers. However, these methods remain constrained by practical limitations and are not yet appropriate for routine implementation in clinical efficacy evaluation. In addition, several biomarkers, including sIgE and the sIgE/tIgE ratio, sIgG4, serum IgE-blocking activity, IgA, cytokines and chemokines, as well as immune cell surface molecules and their functional activity, have been shown to have associations with AIT outcomes. While these biomarkers may complement subjective assessments, they are subject to significant limitations. Consequently, large-scale multicenter trials and real-world evidence are required to strengthen the evidence base. The present consensus underscores the necessity of integrating patients'subjective experiences with objective testing throughout the treatment process, thereby providing a more comprehensive and accurate framework for efficacy evaluation. Looking forward, future investigations should prioritize the incorporation of multi-omics data and artificial intelligence methodologies, which hold promise for overcoming current limitations in assessment strategies and for advancing both the standardization and personalization of AIT.
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