Journal of Asthma and Allergy最新文献

Objective: To investigate the significance of VISTA in bronchial asthma and its impact on the disease.

Methods: Human peripheral blood of asthma children was gathered. The expression concentrations of VISTA, IL-4, IL-6, CD25, CD40L, and PD-L2 in peripheral blood plasma were detected by ELISA. We established the mouse model of asthma and intervened with agonistic anti-VISTA mAb (4C11) and VISTA fusion protein. ELISA, flow cytometry, and Western blotting were performed to detect the expression levels of Th1, Th2, and Th17 cell subsets and related characteristic cytokines, as well as the protein levels of MAPKs, NF-κB, and TRAF6 in lung tissues. In addition, the infiltration of eosinophils and inflammatory cells, airway mucus secretion, and VISTA protein expression in lung histopathological sections of different groups of mice were analyzed.

Results: The concentration of VISTA in human asthma group decreased significantly (p < 0.05); A positive correlation was observed between VISTA and CD40L. The intervention of 4C11 mAb and fusion protein respectively during the induction period increase the differentiation of Th1 cells and the secretion of IFN-γ, and inhibit the differentiation of Th2 and Th17 cells, as well as the secretion of IL-4, IL-5, IL-13 and IL-17, partially reduce the pathological changes of asthma in mouse lungs and correct the progress of asthma. The MAPK, NF-κB, and TRAF6 protein levels were the middle range in the 4C11 mAb and fusion protein groups (p < 0.05).

Conclusion: The findings suggest VISTA may play a negative regulatory role in the occurrence and development of bronchial asthma.

Purpose: Decentralized clinical trials, where trial-related activities occur at locations other than traditional clinical sites(eg participant homes, local healthcare facilities), have the potential to improve trial access for people for whom time and/or distance constraints may impede participation. Albuterol-budesonide 180/160 µg pressurized metered-dose inhaler (pMDI) is FDA approved for the as-needed treatment or prevention of bronchoconstriction and to reduce the risk of exacerbations in patients with asthma 18 years or older. BATURA (NCT05505734) is a fully decentralized study, investigating as-needed albuterol-budesonide in participants with mild asthma.

Methods: BATURA is a fully decentralized, phase 3b, randomized, double-blind, event-driven exacerbation study conducted in the United States. Participants aged ≥12 years using as-needed short-acting β₂-agonist (SABA), alone or with low-dose inhaled corticosteroid or leukotriene receptor antagonist maintenance, are randomized 1:1 to as-needed albuterol-budesonide 180/160 µg or albuterol 180 µg pMDI for up to 52 weeks (minimum 12 weeks). Participants continue their current maintenance therapy, if applicable. Participants must have used SABA for ≥2 days in the 2 weeks pre-enrollment and have an Asthma Impairment Risk Questionnaire score ≥2 at screening and randomization. All trial-related visits, including screening and consent, are conducted virtually, with study medication shipped directly to each participant's residence. The primary objective is to evaluate the efficacy of as-needed albuterol-budesonide versus albuterol on severe asthma exacerbation risk, measured by time-to-first severe asthma exacerbation (primary endpoint). Secondary endpoints include annualized rate of severe asthma exacerbation and total systemic corticosteroid exposure. Study medication use is captured via a Hailie sensor attached to the study medication pMDI. The intended sample size is 2500 participants.

Conclusion: BATURA evaluates as-needed albuterol-budesonide in participants with mild asthma. The decentralized study model enables the trial to move out of research sites into participant homes, reducing participant burden and improving access.

Introduction: Even if mild forms of atopic dermatitis (AD) are usually well controlled with topical prescription drugs and emollients, the management of severe forms of the disease may be challenging, especially in special populations (SPs). These patients include groups of disadvantaged people (elderly, patients with disabilities and serious medical conditions) who are usually excluded from clinical trials. As a consequence, most of the data about the efficacy and safety of a drug in these patients derives from post-marketing experiences. In this context, the aim of our study was to retrospectively investigate the effectiveness and safety of tralokinumab in the management of AD in SPs.

Methods: A 24-weeks retrospective, dual-center study was performed enrolling patients with a diagnosis of moderate-to-severe AD undergoing treatment with tralokinumab at labelled dosage. Disease severity was assessed using Eczema Area Severity Index (EASI), Pruritus-Numerical Rating Scale (P-NRS), and Dermatology Life Quality Index (DLQI) score at baseline and after 4 weeks (W4), W16, and W24. Adverse events (AEs) were monitored at the same timepoints. Statistical significance of clinical improvement (EASI, P-NRS, DLQI) at week 4, week 16, and week 24 as compared with baseline was evaluated by using Student's t-test, considering significant a p-value <0.05.

Results: Our study enrolling 27 SPs patients showed a significant improvement in EASI and P-NRS since week 4, continuing to improve up to week 24. Similarly, DLQI significantly decreases at each timepoint as compared with baseline. Finally, no AEs were reported during the study period. Of interest, our cohort included oncologic patients, a patient with a history of severe infection, as well as subjects affected by severe neurological, psychiatric, pulmonary, and/or cardiovascular disease.

Discussion: Our experience showed that tralokinumab is effective and safe in elderly patients and subjects affected by severe comorbidities.

Asthma is a chronic inflammatory airway disease with significant burden; exacerbations can severely affect quality of life and healthcare costs. Advances in big data analysis and artificial intelligence have made it easier to predict future exacerbations more accurately. This study used an integrated dataset of Korean National Health Insurance, meteorological, air pollution, and viral data from national public databases to develop a model to predict asthma exacerbations on a daily basis in South Korea. We merged these sources and applied random forest, AdaBoost, XGBoost, and LightGBM machine learning models to compare their performances at predicting future exacerbations. Of the models, XGBoost (AUROC of 0.68 and accuracy of 0.96) and LightGBM (AUROC of 0.67 and accuracy of 0.96) were the most promising. Common important variables were the number of visits and exacerbations per year, and medical resource utilization, including the prescription of asthma medications. Comorbid diabetes, hypertension, gastroesophageal reflux, arthritis, metabolic syndrome, osteoporosis, and ischemic heart disease were also associated with elevated exacerbation risk. The models examined in this study highlight the importance of previous exacerbations, use of medical resources, and comorbidities in the prediction of future exacerbations in patients with asthma.