Assessing the Utility of Peak Inspiratory Flow as a Predictor for COPD Exacerbations (PIF in COPD)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Disease epidemiology

Non-interventional study

• Non-interventional study design:
  Other
• Non-interventional study design, other:
  Observational, non-interventional study

Study drug and medical condition

• Medical condition to be studied:
  Chronic obstructive pulmonary disease

Population studied

• Age groups:
  • Adult and elderly population (≥18 years)

    • Adults (18 to < 65 years)

      • Adults (18 to < 46 years)
      • Adults (46 to < 65 years)
    • Elderly (≥ 65 years)

      • Adults (65 to < 75 years)
      • Adults (75 to < 85 years)
      • Adults (85 years and over)
• Estimated number of subjects:
  400

Study design details

• Main study objective:
  A) Determine the prevalence of suboptimal Peak Inspiratory Flow (PIF) and inadequate inhaler choice and assess the baseline characteristics of these groups. B) Assess the clinical role of PIF and inhaler choice in predicting COPD exacerbations and symptom burden. C) Assess the variability and correlation of PIF with other lung function measurements and CAT score in stable COPD.
• Outcomes:
  1) Prevalence of suboptimal PIF and inadequate inhaler choice. 2) Annual exacerbation rate, exacerbation risk and time to first exacerbation and all-cause hospitalization and mortality associated with different levels of PIF. 3) Association between PIF and symptom burden i.e. CAT score. 4) Annual mortality rate associated with different PIF levels. 5) Variability of PIF over time and the correlation between PIF and other lung function measures (including FEV1, FVC, Inspiratory capacity), CAT scores, T2 markers (nasal polyps and dermatitis) and where available blood biomarkers.
• Data analysis plan:
  Comparison of demographic and clinicals characteristics between those with optimal and suboptimal PIF, and those with adequate vs inadequate inhalers. We will analyse: ; • Time to first/ risk of exacerbation using Cox regression. ; • Rates of exacerbation using multivariate negative binomial regression. ; • The variability of PIF measurements will be assessed with repeated measures and coefficient of variation; • The correlation of PIF with other lung function measurements, CAT scores and blood biomarkers will be assessed using Spearman’s rank correlation coefficient. ; ; The analyses will control for the effects of age, sex, previous exacerbation history, ICS use, lung function, smoking status, time since last smoking and seasonality (month of the year).