Group of Clinical and Experimental Allergy, "IPS University" Clinic, University of Antioquia, Medellín, Colombia.
Internal Medicine Department, "San Vicente" Clinic, University of Antioquia, Medellín, Colombia.
PLoS One. 2024 Feb 23;19(2):e0295791. doi: 10.1371/journal.pone.0295791. eCollection 2024.
Early detection of CSU patients with low probability of a clinical response with antihistamines could undergo prompt initiation of therapeutic alternatives. The aim of the study was to develop and internally validate a model for predicting the clinical response to antihistamines in adult patients with chronic spontaneous urticaria (CSU), who consult allergology and dermatology care centers. A cohort of CSU patients, recruited from four participating centers, were followed up for 12 months. Fifteen candidate variables were selected to be included in the multivariate model and then internal validation was done with bootstrap analysis with 1000 simulations. The outcome variable, clinical response to antihistamines, was evaluated with the UAS (Urticaria Activity Score) scale for seven days: "No response to antihistamines" was defined as UAS7 ≥7 points after at least one month with a maximum dose of antihistamines, while "Response to antiH1" was defined as UAS7 ≤6 points for at least three months with the use of antiH1. A total of 790 patients were included. Among the different models analyzed, the model that included age, angioedema, anxiety/depression, time with the disease, NSAIDs (Non-steroidal anti-inflammatory drugs) intolerance, and UAS7 baseline was considered the one with the best performance (accuracy 0.675, HL 0.87, AUC 0.727). The internal validation analyses demonstrated good consistency of the model. In conclusion, this prediction model identifies the probability of response to antihistamines in patients with chronic spontaneous urticaria. The model could be useful for a personalized therapeutic approach according to individual patient risk.
早期发现抗组胺药物治疗反应可能性低的 CSU 患者可以迅速开始治疗替代方案。本研究旨在为成人慢性自发性荨麻疹（CSU）患者开发和内部验证一种预测抗组胺药物临床反应的模型，这些患者在过敏和皮肤科就诊。从四个参与中心招募了一组 CSU 患者，对他们进行了 12 个月的随访。选择了 15 个候选变量来纳入多变量模型，然后使用 bootstrap 分析进行内部验证，模拟次数为 1000 次。使用 UAS（荨麻疹活动评分）量表评估抗组胺治疗的临床反应，为期 7 天：“抗组胺治疗无反应”定义为在至少一个月内使用最大剂量抗组胺药物后 UAS7≥7 分，而“抗 H1 反应”定义为至少三个月内使用抗 H1 时 UAS7≤6 分。共纳入 790 例患者。在分析的不同模型中，包含年龄、血管性水肿、焦虑/抑郁、疾病持续时间、非甾体抗炎药（NSAIDs）不耐受和 UAS7 基线的模型被认为是性能最佳的模型（准确性 0.675、HL 0.87、AUC 0.727）。内部验证分析表明该模型具有良好的一致性。总之，该预测模型可识别慢性自发性荨麻疹患者对抗组胺药物的反应概率。该模型可根据个体患者的风险进行个性化治疗。
