Clustering the Clinical Course of Chronic Urticaria Using a Longitudinal Database: Effects on Urticaria Remission

Allergy Asthma Immunol Res. 2021 May;13(3):390-403. doi: 10.4168/aair.2021.13.3.390.

Abstract

Purpose: Little is known about the clinical course of chronic urticaria (CU) and predictors of its prognosis. We evaluated CU patient clusters based on medication scores during the initial 3 months of treatment in an attempt to investigate time to remission and relapse rates for CU and to identify predictors for CU remission.

Methods: In total, 4,552 patients (57.9% female; mean age of 38.6 years) with CU were included in this retrospective cohort study. The K-medoids algorithm was used for clustering CU patients. Kaplan-Meier survival analysis with Cox regression was applied to identify predictors of CU remission.

Results: Four distinct clusters were identified: patients with consistently low disease activity (cluster 1, n = 1,786), with medium-to-low disease activity (cluster 2, n = 1,031), with consistently medium disease activity (cluster 3, n = 1,332), or with consistently high disease activity (cluster 4, n = 403). Mean age, treatment duration, peripheral neutrophil counts, total immunoglobulin E, and complements levels were significantly higher for cluster 4 than the other 3 clusters. Median times to remission were also different among the 4 clusters (2.1 vs. 3.3 vs. 6.4 vs. 9.4 years, respectively, P < 0.001). Sensitization to house dust mites (HDMs; at least class 3) and female sex were identified as significant predictors of CU remission. Around 20% of patients who achieved CU remission experienced relapse.

Conclusions: In this study, we identified 4 CU patient clusters by analyzing medication scores during the first 3 months of treatment and found that sensitization to HDMs and female sex can affect CU prognosis. The use of immunomodulators was implicated in the risk for CU relapse.

Keywords: Chronic urticaria; cluster analysis; cohort studies; database; house dust mites; prognosis; recurrence; survival analysis.