The use of a spacer in the delivery of large (Fluticasone Propionate) and small particle (Qvar®) inhaled corticosteroid (ICS) in asthma (FP and Qvar Spacer vs Non-Spacer in Asthma)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Drug utilisation

Non-interventional study

• Non-interventional study design:
  Other
• Non-interventional study design, other:
  Retrospective database study

Study drug and medical condition

• Name of medicine, other:
  Qvar
• Anatomical Therapeutic Chemical (ATC) code:
  (R01AD08) fluticasone

  fluticasone
• Medical condition to be studied:
  Asthma

Population studied

• Age groups:
  Adolescents (12 to < 18 years)

  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:
  18500

Study design details

• Main study objective:
  The objective of this study is to investigate the real life effectiveness of ICS delivery of Fluticasone Propionate (FP) and Qvar® (beclomethasone dipropionate HFA) by pMDI with spacer compared to pMDI alone.
• Outcomes:
  ATS exacerbations, Clinical exacerbationsRisk domain asthma controlOverall asthma controlTreatment successSABA useHospitalisationsAdherenceIncidence of oral thrush
• Data analysis plan:
  Summary statistics will highlight differences in baseline variable distributions between treatment groups. These differences will be quantified using conditional logistic regression models. Treatment arms will be compared using t-test / Mann Whitney U-test (depending on distribution) for variables measured on the interval/ratio scale and using a chi square test for categorical variables.If the exploratory analysis shows significant differences between the cohorts prior to IPD, patients will be matched at IPD for key baseline characteristics, the matching criteria and matching ratio will be determined once the baseline data have been examined. Any residual differences between the treatment arms after matching that are considered to be potentially significant (p<0.10) and any variables predictive of the outcome will be adjusted for through further statistical modelling.