Treatable Traits in patients with Obstructive Lung Diseases in Dutch primary care

Study type

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

Non-interventional study

• Non-interventional study design:
  Other
• Non-interventional study design, other:
  Database

Study drug and medical condition

• Medical condition to be studied:
  Chronic obstructive pulmonary disease

  Asthma
• Additional medical condition(s):
  Asthma COPD Overlap

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:
  17000

Study design details

• Main study objective:
  To estimate the prevalence of eight treatable traits and the amount of overlap between these traits in patients with obstructive lung disease in Dutch general practice.
• Outcomes:
  Presence (and overlap) of the treatable traits in patients assessed for asthma and/or COPD at the AC-service for the first time: • Type 2 eosinophilic inflammation • Reversible airflow obstruction • Poor adherence to lung medication • Insufficient inhaler technique • Current smoking • Anxiety or depression • Physical inactivity • Obesity (BMI >=30 kg/m2) or underweight (BMI <18.5 kg/m2), Individual changes in treatable traits status from the first to the second assessment Individual changes in health status and exacerbation rates between the first and second assessment by management advice. Effect of a management advice given for a treatable trait on changes in health status and exacerbation rates at the next assessment (difference in ACQ/CCQ and rate ratios for exacerbations
• Data analysis plan:
  A list of potential confounders, including sex and age, will be constructed based on the information available in the dataset. For all analyses, confounding of effect sizes will be evaluated by testing whether the effect size changes with >=5% after inclusion of the variable into the model. Starting with the crude model, the bias potential (% change in the coefficient of the fixed effect under study) of each potential confounder will be assessed. After that, the confounders will be sorted by their bias potential in a descending order, and the bias will be assessed against the previous model. In case the bias is >=5%, the candidate confounder will be retained in the model.