THE RELIABILITY AND UTILITY OF BLOOD EOSINOPHILS AS A MARKER OF DISEASE BURDEN, HEALTHCARE RESOURCE UTILISATION IN CHRONIC OBSTRUCTIVE PULMONARY DISEASE (BLOOD EOSINOPHIL COUNT AND COPD)

Study type

• Study topic:
  Disease /health condition
• Study type:
  Non-interventional study
• Scope of the study:
  Disease epidemiology
• Data collection methods:
  Combined primary and secondary data collection

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Medical condition to be studied:
  Chronic obstructive pulmonary disease

Population studied

• Short description of the study population:
  All patients with a physician diagnosis of COPD rather than a strict, spirometrically-defined COPD population.; Patients with following criteria were included:; • Have ≥1 recorded blood eosinophil count; • ≥2 years of continuous medical records; o ≥1 baseline year immediately prior to the first recorded blood eosinophil count; o ≥1 outcome years immediately following the first recorded blood eosinophil count; • Aged ≥40 years2; • Have physician-diagnosed COPD i.e. Read coded diagnosis.
• Age groups:
  Adults (18 to < 46 years)

  Adults (46 to < 65 years)

  Adults (65 to < 75 years)

  Adults (75 to < 85 years)

  Adults (85 years and over)
• Special population of interest:
  Other
• Special population of interest, other:
  Chronic obstructive pulmonary disease (COPD) patients
• Estimated number of subjects:
  35000

Study design details

• Main study objective:
  To establish the relationship between blood eosinophil count and future COPD exacerbations.
• Outcomes:
  COPD exacerbations:1. Unscheduled hospital admission or A&E attendance for either COPD or lower respiratory events,2. An acute course of oral steroids prescribed with evidence of respiratory review, OR3. Antibiotics prescribed with evidence of respiratory review.
• Data analysis plan:
  Phase 1: will assess whether a rasied eosinophil count can predict future COPD exacerbations. The expected number of exacerbations will be modelled with a Poisson regression model. Significant predictors of rasised eosinophil count will be included in the model, as well as other potential baseline confounders.Phase 2: will evaluate the presence and nature of change between successive blood eosinophil counts. A multinomial logistic regression will be used to compare the probability of decreasing/increasing the eosinophil count as function of therapy and exacerbationLogistic regression modeling will be used to evaluate the effect of different characteristics on probability of having a raised COPD eosinophil count.

Documents

Study publications

Kerkhof, M., Sonnappa, S., Postma, D.S., Brusselle, G., Agusti, A., Anzueto, A…