Liu Y, et al. Allergy Asthma Immunol Res. 2022 Jul;14(4):393-411. https://doi.org/10.4168/aair.2022.14.4.393

Current guidelines recommend a single inhaler maintenance and reliever therapy (SMART) regimen for moderate to severe asthma. However, evidence for the inhaled corticosteroid plus fast-onset-acting β2-agonist (ICS/FABA) as reliever therapy in management of intermittent and mild asthma patients is lacking. To systematically explore efficacy and safety of the proof-of-concept of the ICS plus FABA regimen in a single inhaler as reliever therapy across children and adults with intermittent and mild persistent asthma. We searched online bibliographic databases for randomized controlled trials (RCTs) involving the as-needed use of ICS/FABA as monotherapy in intermittent or mild asthma patients. The primary outcomes were exacerbations and the hazard ratio (HR) of the time to first exacerbation. Six RCTs (n = 1300) met the inclusion criteria. Compared with the as-needed FABA regimen, the as-needed use of ICS/FABA as monotherapy statistically reduced exacerbations (RR = 0.56, P = 0.001). Compared with regular ICS regimen, the as-needed ICS/FABA therapy had slightly higher risk of exacerbations (RR = 1.39, P = 0.011). The HR for time to first exacerbations in the ICS/FABA regimen was significant lower when compared with FABA regimen (HR = 0.52, P = 0.002) but had no difference when compared with ICS regimen (HR = 1.30, P = 0.286). The corticosteroid exposure in the daily ICS regimen was 2- to 5-fold compared with as-needed use of ICS/FABA regimen. Our analysis shows that the ICS/FABA as a symptom-driven therapy may be a promising alternative regimen for the patients with intermittent or mild asthma, but it needs further real-world RCTs to confirm these findings.

Background: Skeletal muscle mass (SMM) has been suggested to be associated with multiple health-related outcomes. However, the potential influence of SMM on asthma has not been largely explored. Objective: To study the association between SMM and clinical features of asthma, including asthma control and exacerbation, and to construct a model based on SMM to predict the risk of asthma exacerbation (AEx). Methods: In this prospective cohort study, we consecutively recruited patients with asthma (n = 334), classified as the SMM ^Normal group (n = 223), SMM ^Low group (n = 88), and SMM ^High group (n = 23). We investigated the association between SMM and clinical asthma characteristics and explored the association between SMM and asthma control and AEx within a 12-month follow-up period. Based on SMM, an exacerbation prediction model was developed, and the overall performance was externally validated in an independent cohort (n = 157). Results: Compared with the SMM ^Normal group, SMM ^Low group exhibited more airway obstruction and worse asthma control, while SMM ^High group had a reduced eosinophil percentage in induced sputum. Furthermore, SMM ^Low group was at a significantly increased risk of moderate-to-severe exacerbation compared with the SMM ^Normal group (relative risk _adjusted 2.02 [95% confidence interval (CI), 1.35–2.68]; p = 0.002). In addition, a model involving SMM was developed which predicted AEx (area under the curve: 0.750, 95% CI: 0.691–0.810). Conclusions: Low SMM was an independent risk factor for future AEx. Furthermore, a model involving SMM for predicting the risk of AEx in patients with asthma indicated that assessment of SMM has potential clinical implications for asthma management.

Background: Previous studies have indicated the limitations of body mass index for defining disease phenotypes. The description of asthma phenotypes based on body composition (BC) has not been largely reported. Objective: To identify and characterize phenotypes based on BC parameters in patients with asthma. Methods: A study with two prospective observational cohorts analyzing adult patients with stable asthma (n = 541 for training and n = 179 for validation) was conducted. A body composition analysis was performed for the included patients. A cluster analysis was conducted by applying a 2-step process with stepwise discriminant analysis. Logistic regression models were used to evaluate the association between identified phenotypes and asthma exacerbations (AEs). The same algorithm for cluster analysis in the independent validation set was used to perform an external validation. Results: Three clusters had significantly different characteristics associated with asthma outcomes. An external validation identified the similarity of the participants in training and the validation set. In the training set, cluster Training (T) 1 (29.4%) was “patients with undernutrition”, cluster T2 (18.9%) was “intermediate level of nutrition with psychological dysfunction”, and cluster T3 (51.8%) was “patients with good nutrition”. Cluster T3 had a decreased risk of moderate-to-severe and severe AEs in the following year compared with the other two clusters. The most important BC-specific factors contributing to being accurately assigned to one of these three clusters were skeletal muscle mass and visceral fat area. Conclusion: We defined three distinct clusters of asthma patients, which had distinct clinical features and asthma outcomes. Our data reinforced the importance of evaluating BC to determining nutritional status in clinical practice.