Development, validation, utility and economic assessment of a flexible, individualized risk prediction e-tool for exacerbation in patients with severe asthma (Severe asthma risk prediction)

Study type

• Study type:
  Not applicable
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness
• If ‘Not applicable’, further details on the study type:
  Predictive risk modeling, 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:
  103000

Study design details

• Main study objective:
  1.Develop and validate an individualized prediction model for exacerbations in severe asthma. 2.eHealth implementation through an interactive web app, voice interface, and web Application Programming Interfaces(APIs). 3.Assess the clinical utility and cost-effectiveness of individualized risk prediction model in informing advanced treatment such as generic biologics.
• Outcomes:
  Individualized prediction of frequency of severe exacerbations in patients with severe asthma in a time period. Individualized prediction of frequency of serious exacerbations in patients with severe asthma in a time period.
• Data analysis plan:
  First, we will develop a mixed-effect regression model that jointly parameterizes exacerbation rate and severity to predict rate of exacerbation at any time window as well as its severity level, which enables prediction of the number of exacerbations and the risk of having certain number of exacerbations in a given time period. Second, we will externally validate the final prediction model in the ISAR cohort, the endpoints include model calibration (i.e. the agreement between observed and predicted outputs) and model discrimination (i.e. the extent to which the model can distinguish between high- and low-risk individuals). Third, we will implement the individualized prediction models, once validated, into a user-friendly, freely-accessible Web App. Finally, we will perform the decision curve analyses and cost-effectiveness analysis to determine the clinical usefulness and value for money of this prediction tool in guiding asthma specialist referral and prescribing biologics.