Statistical Considerations for Clinical Trials During COVID-19: An Adaptive Hybrid Design for Clinical Development in Rare Diseases

Qing Liu, Karl E. Peace

Research output: Contribution to journalArticlepeer-review

Abstract

Due to small population and subset heterogeneity in rare diseases, randomized controlled trials are generally not adequately powered for robust inference as are trials of common diseases. Depending on the disease and stages of progression, randomized controlled rare disease trials can vary considerably in study duration and length of time required for patient enrollment to reach the planned sample size. The unexpected COVID-19 pandemic exacerbates the issue when an ongoing randomized controlled rare disease trial is put on hold. This could substantially delay the completion of the trial to address the pressing unmet needs. There are several options. In this article we consider rare disease drug development with a robust clinical program consisting of a natural history study, a single arm trial and an ongoing severely affected randomized controlled trial. We describe a two-stage adaptive hybrid design developed by Liu, Hai, Holdbrook and Castelli (2019) to integrate data from a single arm trial and a natural history study in comparative analysis efficacy of a randomized controlled trial for rare disease applications.

Original languageAmerican English
JournalLinkedIn
StatePublished - Apr 6 2020

DC Disciplines

  • Biostatistics
  • Environmental Public Health
  • Epidemiology
  • Public Health

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