Redefining severe asthma to high-risk asthma: Analysis of real-world data to investigate patients who are at high risk of exacerbations, worsening of symptoms, and a loss of asthma control over time.

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness

  Disease epidemiology

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Medical condition to be studied:
  Asthma

Population studied

• 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)
• Estimated number of subjects:
  2000000

Study design details

• Main study objective:
  To investigate patients with asthma to determine what characteristics, co-morbidities, treatments, and other clinical characteristics are associated with higher risk of exacerbations, worsening of symptoms and loss of asthma control.
• Outcomes:
  Change in patients’ asthma symptoms measured by changes in patients’ treatments, clinical markers, and frequency and severity of exacerbations. These will be associated to patient’s characteristics, and comorbidities to determine patients that are at high risk of worsening asthma outcomes.
• Data analysis plan:
  Patient’s characteristics will be measured at initial asthma diagnosis (ID) and over time and will include, but not be limited to, patient characteristics, clinical measures at baseline and over time, asthma treatments, and comorbidities. Statistical analysis for the baseline variables for each of the OCS prescribing categories will be descriptive in nature. They will provide the absolute and relative number of subjects, mean, median, standard deviation (SD), and interquartile range (IQG) for continuous variables for the baseline variables. Perform predictive analysis on variables thought to be predictive of a worsening of asthma symptoms/increase in exacerbations. Incident rate ratios for exacerbations will be calculated by baseline population types. Missing data for BMI, smoking status and PEF % predicted will be imputed using multiple imputation techniques.