Objectives
Bridge the efficacy to effectiveness gap, for optimal pragmatic trial design
Identify and characterize drivers of effectiveness.
Project efficacy endpoints to efficacy outcomes.
Optimize negotiations with payers and study design accordingly.
Methods & solution
Building a predictive disease model in real-world of asthma accounting for the drivers of effectivness of drugs in development and from the standard of care
Using a long term cohort studies on asthma patients.
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Definition of prescriptions, 3-level GINA control scores and exacerbations adjusted on the basis of hospital admissions.
Drug possession ratios, used as an indicator of compliance.
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Identification and quantification of effectiveness factors such as adherence.
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Development of a Bayesian dynamic inhomogeneous Markov model at the patient level to jointly describe prescriptions and outcomes over time.
Results
Adherence and related factors significantly improve long-term effectiveness
Association of treatment changes with disease severity while adherence was significantly improved when patients had treatment changes.
The risk of exacerbation depended on the control score and season.
Control was significantly improved by better adherence.
Impact
Succesful pragmatic trials and postmarketing studies guided by such real-world simulations
- Adherence and related factors were shown to be highly interacting with long-term efficacy (eg on relapse rate).
Reference: A Bayesian Dynamic Model of Asthma in the Real Life – https://doi.org/10.1016/j.jval.2013.08.1665