Phenotyping of asthma population based on inflammatory blood biomarkers and characterisation of phenotypes depending on asthma control, frequency of exacerbations, and associated comorbidities.
Bony Francis, Deepak Phalgune, Sanjay Mehendale, Jai Mullerpattan
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引用次数: 0
Abstract
Background and objective: There are very few studies in the Indian population on the prevalence of phenotypes in asthma patients. To phenotype patients with bronchial asthma and characterise the phenotypes based on asthma control, exacerbation frequency, and associated comorbidities.
Methods: The current cross-observational study was conducted between January 2022 and June 2022 in the department of pulmonary medicine in a tertiary care hospital. One hundred and seventeen patients aged 13 or above of both genders diagnosed with asthma as per Global Initiative for Asthma guidelines were enrolled. The blood eosinophil count and serum immunoglobulin E were measured. The Asthma Control Test (ACT) Questionnaire was used to calculate the ACT score. The patients were categorised into various asthma phenotypes such as atopic asthma, eosinophilic asthma, overlap phenotype, and biomarker-negative.
Results: Phenotypes such as atopic, eosinophilic, overlap, and both negative were observed in 33.3%, 20.5%, 42.7%, and 3.4% patients, respectively. The mean BMI was significantly lower in both negative patients. There was no statistically significant association observed between allergic rhinitis, chronic rhinosinusitis, and eczema with various phenotypes, whereas nasal polyposis had a significant association with eosinophilic phenotype and overlap. The median asthma exacerbations per year were significantly higher in patients of bronchial asthma, atopic and overlap phenotypes. The percentage of patients who required baseline corticosteroid support was significantly less in both negative phenotypes.
Conclusion: There is a substantial overlap of inflammatory blood biomarkers, suggesting that a more comprehensive approach is needed to identify the optimal therapy for individual patients.