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Comparisons of competing interventions are essential to determine value of medicines, both from clinical and societal perspective. With head-to-head studies rare, HTA bodies rely on NMA techniques to derive the necessary estimates and incorporate them into cost-effectiveness models. The use of RWD for head-to-head comparison purposes was often challenged due to data limitations and difficulty to draw causal conclusions.

Recent developments are challenging this status quo. The increased availability of regulatory-grade RWD helps. We can now also avoid some of the biases that used to plague the use of observational data.

Head to head comparisons using RWD through emulation of target trials successfully deal with most of these biases. We have recently completed and initiated several studies to document that we can do so successfully.

During this presentation, we will review the pilots but focus on applications. Specifically, we will discuss how H2H comparisons using RWD helps:

  • Generate efficacy or safety evidence for conditional regulatory approval or post-market assessment
  • Provide a comparison when network meta analysis is not possible
  • Expand the scope of a randomized trial
  • Refine aspects of an existing treatment protocol
  • Enable a comparison to identifying optimal treatment regimes

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