A non-invasive simplified scoring system to predict airway mucus plugs in asthma

Abstract

Abstract Background Airway mucus plugs are a core pathological feature of severe asthma and are closely associated with airflow limitation and poor prognosis. However, rapid and efficient clinical screening tools for identifying airway mucus plugs in asthma are currently lacking. Objective This study aimed to develop and evaluate meta‑analysis‑weighted scores for estimating the presence and severity of airway mucus plugs in adults with asthma. Methods A systematic review and meta-analysis of six major databases (up to February 2025) were conducted to identify significant risk factors for mucus plugs. Subsequently, a mathematical equation-based score and a simplified scoring system were constructed based on the converted standardized effect-size weights (β). Internal validation of the scoring system was then performed using a cohort of 105 asthma patients from Tongji Hospital, Huazhong University of Science and Technology (2024∼2026). Results The meta-analysis included 10 studies (837 patients) and identified age, pulmonary function parameters (FEV 1 %, FVC%, FEV 1 /FVC%), and type 2 inflammatory markers (FeNO, blood eosinophil count, IgE) as key associated factors. In the internal validation cohort, the simplified scoring system showed an AUC of 0.864 (95% CI: 0.785–0.943) for estimating mucus plug presence, with a specificity of 0.941 and sensitivity of 0.718. For estimating higher mucus plug burden, the AUC was 0.859 (95% CI: 0.777–0.941), with a sensitivity of 0.917 and specificity of 0.684. Conclusion The meta-analysis-weighted scores showed promising preliminary discrimination for mucus plug presence and higher burden. These scores may assist in prioritizing patients for HRCT, though external validation is required.