Journal of Allergy and Clinical Immunology-In Practice最新文献

Isolated episodes and epidemic outbreaks of thunderstorm asthma have now been documented for over 40 years, with global geographical reach across Europe, North America, Middle East, Asia, Oceania and Africa. This phenomenon encompasses specific environmental and meteorological factors, interacting with aeroallergen propagation and exposure in susceptible allergen-sensitized individuals and populations. There is a likely contribution from climate change with prolonged allergenic pollen seasons combined with increased pollen allergenicity, as well as heightened likelihood of extreme weather events. Differential population susceptibility to thunderstorm asthma presentations, hospitalizations and deaths with increased vulnerability of certain ethnic groups suggest a gene-environment interaction. This Clinical Commentary reviews the characteristics and updates the epidemiology of thunderstorm asthma; examines the role of aerobiology and climate change; discusses risk factors for emergency presentations, hospital admissions and deaths; considers latest research and predictors of thunderstorm asthma, and proposes strategies to manage and mitigate risk.

Background: Aspirin-exacerbated respiratory disease (AERD) is a chronic eosinophilic inflammatory disorder characterized by asthma, chronic rhinosinusitis with nasal polyps (CRSwNP), and intolerance to cyclooxygenase-1 inhibitors. Intranasal aspirin challenge (IAC) is increasingly used for AERD diagnosis due to its practicality and safety. However, the lack of standardized symptom score criteria and optimal dosage complicates its diagnostic utility.

Objective: To establish symptom score criteria and determine the optimal cumulative dosage for IAC in diagnosing AERD.

Methods: A total of 116 patients with CRSwNP were enrolled, including 58 with AERD and 58 without AERD. Group A (n=70, 35 AERD, 35 non-AERD) was used to establish the symptom score criteria, which were validated in Group B (n=46, 23 AERD, 23 non-AERD). Symptom severity was assessed using a visual analog scale (VAS), and diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curve analysis. The safety and optimal dosage of IAC were also investigated.

Results: The optimal cutoff value for the increase in total VAS (T-VAS) was 7.5 points, with a sensitivity of 80.0% and specificity of 97.1%. A maximal cumulative dosage of 70 mg achieved the highest diagnostic accuracy (91.3%) and sensitivity (87.0%). Nasal congestion and rhinorrhea were the most pronounced symptoms during IAC in AERD patients. IAC was generally well-tolerated, with 4.3% of participants experiencing acute worsening of asthma.

Conclusion: This study identifies a T-VAS increase of 7.5 points and a maximal cumulative dosage of 70 mg as optimal for diagnosing AERD via IAC, providing a reliable, safe, and practical diagnostic approach.

Inborn errors of immunity (IEIs) are a heterogenous group of genetic disorders with long diagnostic delay that negatively impacts patient outcomes. To combat delay, 8 multidisciplinary experts from different disciplines convened to generate 11 consensus-based statements that address approaches that could reduce the diagnostic journey of patients with IEIs. Nine of these statements relate to the development and implementation of automated decision support tools to improve rapidity of diagnosis by augmenting clinical decision making for practitioners with or without IEI experience. Strengths and limitations of such tools as well as considerations for development and implementation are discussed. Two consensus statements were generated to support the development of successful multidisciplinary care teams to facilitate optimal evaluation of patients identified to be at risk of IEI. We discuss essential components for developing a multidisciplinary care team, including clinical interest, institutional and financial support, and crucial team members. Both of these approaches may increase diagnostic accuracy for patients with IEIs and lead to improvements in care.

Background: Studies comparing biological therapies for severe asthma usually have a selection bias considering that some of these therapies are indicated for allergic asthma and others for eosinophilic asthma. Severe mixed asthma (SMA) was considered in patients with both allergic and eosinophilic (mixed) severe asthma. In SMA, dupilumab, omalizumab, mepolizumab, and benralizumab, can be used. Currently there are no head-to-head studies comparing the clinical response of biological therapies in this group of patients.

Objective: To compare the effectiveness of four biological therapies in SMA.

Methods: Prospective study with one year of follow-up. Severe asthma patients with markers for allergic asthma (total IgE >100IU/L and sIgE to aeroallergens) and eosinophilic asthma (Eosinophils >150 cells/ml) were recruited. Sociodemographic and clinical characteristics were evaluated at baseline to assess significant differences between groups. The primary outcome was the proportion of patients achieving > 20 points in the Asthma Control Test (ACT), and as secondary outcomes we evaluated the number of severe exacerbations of asthma per year and change in FEV1.

Results: A total of 133 patients participated in the study (dupilumab n=43, omalizumab=32, mepolizumab=32, benralizumab=26). At baseline, the groups did not have significant differences in sociodemographic or clinical characteristics. After one year with biological therapies, the four groups presented a significant improvement in clinical outcomes with few between groups differences. There was no difference for the main outcome (ACT) in the four groups. Dupilumab and mepolizumab demonstrated a higher interval improvement in FEV1 than omalizumab. Dupilumab users had the highest proportion of patients who achieved a 200 ml improvement in FEV1 over omalizumab and benralizumab. The greatest adherence was observed among benralizumab users.

Conclusion: In SMA the four biological therapies offer similar symptom control according to ACT but there are some differences according to FEV1 and adherence. Therefore, the selection of these therapies in SMA must be based on particular aspects of each patient.