Multi-component assessment systems and predicting future risk in chronic obstructive pulmonary disease

Study type

• Study topic:
  Disease /health condition
• Study type:
  Non-interventional study
• Scope of the study:
  Effectiveness study (incl. comparative)
• Data collection methods:
  Secondary use of data

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:
  Primary care COPD patients
• 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)
• Special population of interest:
  Other
• Special population of interest, other:
  Chronic obstructive pulmonary disease (COPD) patients
• Estimated number of subjects:
  5116

Study design details

• Main study objective:
  To evaluate the Dyspnoea, Obstruction, Smoking, Exacerbation (DOSE) and the Age, Dyspnoea, Obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients.
• Outcomes:
  DOSE and ADO associations with health status measured by the CCQ and SGRQ, Current symptoms, exacerbations and hospital admissions, Future events of exacerbations, admissions and mortality, Distribution of GOLD categories according to different methods of calculation
• Data analysis plan:
  Spearmans rank correlation was used to assess the association between each of the DOSE and ADO indices and the health status measures and markers of healthcare consumption in each of the 3 datasets. Logistic regression analysis was used to calculate the unadjusted odds ratio for 1 or more hospital admissions and for 1 or more exacerbations in the subsequent year for a unit increase in the DOSE or ADO indices. ROC analyses and AUC were produced for DOSE and ADO indices in relation to the prediction of future risk of exacerbations and admissions. Negative binomial regression models and Cox regression were also used.