Impact of exacerbations on lung function, resource utilization, and productivity: results from an observational, prospective study in adults with uncontrolled asthma

Predicting Asthma Exacerbation Risk in the Adult South Korean Population Using Integrated Health Data and Machine Learning Models

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.

Suboptimal Response to Biologics in Severe Asthma-A Marker of Humoral Immunodeficiencies

BACKGROUND

Asthmatic patients with antibody deficiencies (AD) have more severe disease and higher risk of exacerbations. No data exist about the efficacy of biologics in severe asthma (SA) patients with AD.

OBJECTIVE

To evaluate the efficacy of biologics in SA patients with and without AD.

METHODS

A case-control real-life study was conducted including 68 patients divided into 2 groups: group 1 with SA-AD and group 2 with SA.

RESULTS

Treatment with biologics for 6 months was effective for decreasing the number of exacerbations, hospitalizations, and emergency department (ED) visits and improving the Asthma Control Questionnaire (ACQ) score; biologics also proved a systemic corticosteroid-sparing effect. Despite benefits, the number of exacerbations, hospitalizations, and ED visits, the mean ACQ score, and the cumulative dose of systemic corticosteroids remain higher in group 1 than in group 2, with lower lung function parameters. The rates of responses in group 1 were inferior to those in group 2, with a decrease by ≥50% of exacerbation rate in 76% versus 97% of patients (P = .006), no hospitalization in 44% versus 91% of patients (P < .001), no ED visit in 56% versus 82% of patients (P = .018), a significant improvement of the ACQ score by ≥0.5 in 68% versus 100% of patients (P < .001), and an increase of forced expiratory volume in the first second by >10% in 32% versus 65% of patients (P = .007).

CONCLUSIONS

Despite evident benefits, SA patients with AD have suboptimal responses to biologics compared with those immunocompetent. A multidisciplinary approach is necessary to optimize the management of these patients in practice.

Outcome measures in asthma attack trials: can't see the good for the wheeze

A systematic review highlights limitations and variability in outcome measures for trials in asthma attack treatment. Now is the time to adopt a consistent approach to ensure best patient care in a precision medicine future. https://bit.ly/3O4zDHY.