Modelling is commonly used to support decision-making by health technology assessment (HTA) agencies, particularly to predict treatment effects beyond the timeframe in the existing RCTs.
GetReal has examined two uses of modelling to address the potential gap between the efficacy of a treatment observed in RCTs and effectiveness in the real world:
- Extrapolating treatment effects to the long-term, using real-world data (RWD).
- Predicting effectiveness of treatments in a real-world population.
The figure below summarises how modelling can be used to extend RCT data over time or across populations.
Figure. Use of modelling to extend RCT data.
For more information on methods for predicting outcomes to bridge the efficacy-effectiveness gap, including a review of the existing literature and a summary of the approaches examined by GetReal see Overview of Methods for Predicting Outcomes, including Approaches to Bridge the Efficacy-Effectiveness Gap.