Mr. Amin Adibi, University of British Columbia, Vancouver, BC

Chronic Obstructive Pulmonary Disease (COPD) is characterised by symptoms of breathlessness and cough, which worsen acutely during exacerbations. COPD is known to be a heterogeneous disorder with large variations in the risk of exacerbation across patients. In clinical practice, a history of two or more exacerbations and one severe exacerbation per year is used to guide therapeutic choices for exacerbation prevention. However, this approach is clinically limited owing to significant heterogeneity in risk even within those who frequently exacerbate.

In this talk, we will discuss development and validation of a personalised clinical prediction model to predict frequency and severity of COPD exacerbations. Using data from three randomized trials, we show that simple clinical and demographic variables in aggregate can be used to predict the exacerbation risk with improved accuracy. We discuss the performance of the model in an independent external cohort, and explain, using case studies, its potential clinical applications.

Learning Objectives
At the end of this presentation, attendees will be able to:

  • Describe the importance of exacerbation risk prediction in clinical management of COPD;
  • Compare the performance of different clinical prediction models; and
  • Use the Acute COPD Exacerbation Prediction Tool (ACCEPT) to obtain individualized prediction of exacerbation rate and severity in clinical settings.