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Area of Science:

  • Clinical Trials and Evidence Synthesis
  • Pharmacoeconomics and Health Technology Assessment
  • Regulatory Science

Background:

  • Randomized controlled trials (RCTs) are crucial for regulatory decisions, clinical practice, and patient outcomes.
  • Significant under-representation of certain patient groups in RCTs creates evidence gaps.
  • This limits the generalizability of trial findings to diverse patient populations.

Purpose of the Study:

  • To review methods for extrapolating evidence from RCT participants to different target populations after market approval.
  • To discuss practical implementation of these extrapolation methods for regulatory and health technology assessment (HTA) decisions.
  • To address the evidence gap during the early post-market period.

Main Methods:

  • Review of three established methods for evidence extrapolation from existing clinical trial data.
  • Discussion of practical implementation strategies for regulatory agencies and HTA bodies.
  • Analysis of the role of real-world data in conjunction with extrapolation methods.

Main Results:

  • Extrapolation methods can help bridge evidence gaps for under-represented groups in the early post-market phase.
  • These methods are not replacements for pre-approval RCTs or robust post-approval observational studies.
  • Successful implementation requires clear articulation of assumptions and limitations.

Conclusions:

  • Extrapolation methods offer valuable tools to inform regulatory and HTA decisions when direct trial data is limited.
  • Transparency regarding assumptions and limitations is paramount for the credible use of extrapolated evidence.
  • Further research and practical application are needed to refine these methods for diverse patient populations.