External Controls to Study Treatment Effects in Rare Diseases: Challenges and Future Directions

Janick Weberpals1, Shirley V Wang1

  • 1Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

PubMed

Insights

External control arms from real-world data help evaluate rare disease therapies. Methodological challenges exist, but this review explores solutions for valid comparisons.

Area of Science:

  • Pharmacovigilance
  • Clinical Trial Design
  • Real-World Evidence

Background:

  • Regulatory agencies increasingly use real-world evidence (RWE) from routine healthcare data for novel therapy evaluation.
  • External control arms derived from RWE are crucial for augmenting single-arm clinical trials in rare diseases.
  • Methodological limitations can impact the validity of RWE-based external control arm comparisons.

Purpose of the Study:

  • To review common methodologies for utilizing external control arms in rare disease research.
  • To identify and discuss critical methodological challenges associated with these approaches.
  • To propose future directions for enhancing the validity of RWE-based external control arms.

Main Methods:

  • Literature review of frequently employed methods for constructing external control arms.
  • Analysis of key criticisms and limitations reported in existing studies.
  • Synthesis of potential solutions and best practices for future research.

Main Results:

  • Summarized common approaches for RWE-derived external control arms.
  • Highlighted significant methodological concerns impacting data interpretation.
  • Identified areas requiring further research and development.

Conclusions:

  • External control arms offer valuable insights but require careful methodological consideration.
  • Addressing identified criticisms is essential for reliable RWE utilization in rare disease drug evaluation.
  • Future research should focus on robust methodologies to ensure the validity of real-world data comparisons.

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