Prevalence and healthcare utilization of eosinophilic chronic obstructive pulmonary disease in the UK – an observational data linkage study

Study type

• Study topic:
  Disease /health condition
• Study type:
  Non-interventional study
• Scope of the study:
  Disease epidemiology

  Healthcare resource utilisation
• Data collection methods:
  Secondary use of data

Non-interventional study

• Non-interventional study design:
  Cohort

  Cross-sectional

Study drug and medical condition

• Medical condition to be studied:
  Chronic obstructive pulmonary disease

Population studied

• Short description of the study population:
  The study population are adult patients registered with Optimum Patient Care Research Database (OPCRD) with a diagnostic code indicative of COPD.
• 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)

Study design details

• Study design:
  We will identify all patients with COPD in OPCRD. Within that population, we will identify (a) those with active COPD; (b) those diagnosed eosinophilic; (c) with an asthma comorbidity; (d) on triple therapy and (e) with >1 and >2 exacerbations. Cohorts will be followed up in 2024 for health outcomes
• Main study objective:
  To estimate the number and proportion of patients with COPD stratified by eosinophil count, asthma comorbidity, exacerbations and current therapy. To calculate the annual rate of different health outcomes in patients who are potentially eligible for biologic therapy and patients who are not .
• Setting:
  Inclusion criteria are all adult patients registered within OPCRD (approximately 10% of the general population in the UK) with a diagnostic code for COPD. Patients need to be continuously registered between 1.1.2021 and 1.1.2024. and have valid information available for age and sex.
• Outcomes:
  (1) Number and proportion in the different cohorts; (2) risk factors associated with membership to the different cohorts (odds ratios); (3) hazards and hazard-ratios of disease progression; (4) number of exacerbations (measure for disease progression)
• Data analysis plan:
  Logistic regression for the risk factors; full-parametric survival analysis for the hazards of disease progression; negative binomial regression for the number of exacerbations. Data management and analysis in MS-SQL Server and R, respectively. All classification will be based on the linked electronic health records, using published code lists and code lists generated by OPCRD.