TB Research

Clinical utility of sputum cell count in severe asthma

Sharron Gilbey, Anita Cass, Sunera Khan, Heather Stephens, Jessica Shingler, Anilkumar Pillai, Adel Mansur

Abstract

<bold>Background:</bold> Sputum cell count is used for phenotyping airway inflammation. However, its clinical use is limited due to technical limitations and lack of evidence for its role in severe asthma. <bold>Aim:</bold> To assess clinical utility of sputum cytology in phenotyping airway inflammation and impact on clinical decision-making in severe asthma. <bold>Methods:</bold> Patients with severe asthma uncontrolled on standard and biologic treatment provided supervised spontaneous sputum samples. Samples were processed and reported by hospital pathology department using standardised protocol. The asthma multidisciplinary team used results to guide treatment decisions. Phenotypic categories included eosinophilic (eosinophil count ≥3%), neutrophilic (neutrophil count ≥60%), mixed eosinophilic & neutrophilic, or pauci-granulocytic. <bold>Results:</bold> Of 78 patients, sputum quality was sufficient for differential cell count in 43 (55.1%) - 23 (53.5%) female, mean age 54.93±16.27 years. Mean eosinophil sputum count was 10.88±22.02, mean neutrophil count 59.44±29.76. Correlation was negligible between blood and sputum eosinophils (r=0.2226, p=0.1565), and between sputum eosinophils and FeNO (r=0.2572, p=0.1139). Of those on biologics (n=16), sputum was eosinophilic in 18% (n=3), neutrophilic in 38% (n=6), mixed in 38% (n=6), and pauci-granulocytic in 6% (n=1). Following sputum results, 7 out of 43 patients (16.3%) were started on a biologic, 6 (14%) had treatment switched or extended, and 6 (14%) either commenced or stopped long-term macrolide antibiotics. <bold>Conclusion:</bold> Spontaneous sputum analysis in clinical service was successful in 55% of samples, allowing airway phenotyping that guided treatment. Further standardisation and exploration of inducible sputum analysis is required.

MeSH terms

  • Sputum
  • Asthma
  • Medicine
  • Computer science