The Predictive Value of Serum Total IgE for Antihistamine Treatment Outcomes in Chinese Patients with Chronic Spontaneous Urticaria.

Journal: Acta dermato-venereologica
Published Date:

Abstract

Chronic spontaneous urticaria is a common skin disorder with variable treatment responses. Second-generation H1-antihistamines are the first-line treatment for chronic spontaneous urticaria, yet many patients fail to respond to licensed doses. Predictors of treatment response to second-generation H1-antihistamines could help optimize disease management and minimize unnecessary healthcare costs. In this retrospective cohort study of 99 Chinese chronic spontaneous urticaria patients, higher log-transformed serum total IgE levels were significantly associated with poor response to standard-dose antihistamines (aOR = 2.09, 95% CI: 1.29-3.38, p = 0.003). However, this association was not observed in the subgroup of patients who required dose escalation, suggesting a more complex relationship in later treatment stages. Machine learning analysis further supported total IgE as one of the top predictors of poor response to standard-dose second-generation H1-antihistamines. While serum total IgE may not serve as a diagnostic tool, it appears to be a helpful risk indicator for anticipating refractoriness to standard-dosed antihistamines in chronic spontaneous urticaria, particularly at the initial treatment stage.

Authors

  • Yingyi Li
    Department of Dermatology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China; Photomedicine Laboratory, Institute of Precision Medicine, Tsinghua University, Beijing, China.
  • Rui Peng
    Affiliated Nanhua Hospital, University of South China, Hengyang, People's Republic of China.
  • Jingwen Xue
    Department of Dermatology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China; Photomedicine Laboratory, Institute of Precision Medicine, Tsinghua University, Beijing, China. wendyxue92@163.com.
  • Yi Zhao
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine.