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Cell pathways in lung inflammation and injury
S83 Repeatability and inter-relationships of small airway biomarkers
  1. S Gonem1,
  2. I Ball2,
  3. S Corkill1,
  4. D Desai1,
  5. A Singapuri1,
  6. P Gustafsson3,
  7. J Owers-Bradley2,
  8. C Brightling1,
  9. S Siddiqui1
  1. 1Glenfield Hospital, Leicester, UK
  2. 2University of Nottingham, Nottingham, UK
  3. 3Queen Silvia Children's Hospital, Göteborg, Sweden

Abstract

Introduction and objectives There is evidence that the small airways may have an important role in asthma, and a number of physiological techniques have been developed to assess small airway dysfunction. We aimed to determine the within-visit and between-visit repeatability of putative small airway biomarkers, and explore the inter-relationships between them.

Methods We recruited 17 patients with moderate asthma (GINA 3/4), twelve patients with severe asthma (GINA 5) and fifteen healthy control subjects. Participants attended baseline, 2-week and 3-month visits. At each visit, participants undertook standard pulmonary function tests, multiple breath washout (MBW), impulse oscillometry (IOS) and measurement of exhaled nitric oxide at multiple flow rates. Five healthy subjects and 10 patients with asthma also undertook hyperpolarised helium-3 MRI at the baseline and 3-month visits. This was used to calculate the apparent diffusion coefficient (ADC), a measure of alveolar airspace size.

Results Sacin, a MBW marker of acinar airspace disease, showed excellent repeatability in patients with asthma, with intraclass correlation coefficients (ICC) of 0.914, 0.897 and 0.879 for within-visit, 2-week and 3-month repeatability respectively. The IOS small airway markers R5-R20 and AX displayed similarly good repeatability (0.966 [within-visit], 0.905 [2-week] and 0.844 [3-month] for R5-R20, and 0.977 [within-visit], 0.875 [2-week] and 0.855 [3-month] for AX). The 3-month repeatability for ADC was 0.682. Principal components analysis was used to explore the inter-relationships between the small airway biomarkers. Four components were extracted, as shown in Abstract S83 table 1. The highest loading variables on each component were FeNO200, NOalv and MEF on component 1, R5-R20 and AX on component 2, FVC and RV/TLC on component 3, and Kco (% predicted) and ADC on component 4. Thus, components 1–4 corresponded broadly to the concepts of “airway inflammation”, “frequency dependence of small airway resistance and elastance”, “air trapping” and “alveolar disease” respectively.

Abstract S83 Table 1

Principal components analysis of small airway biomarkers

Conclusions The putative small airway markers under investigation are robust and repeatable. Principal components analysis has revealed that the information obtained from multiple tests of airway function may be condensed down to four primary concepts, and that there is significant redundancy among the measurements.

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