Sample size re-estimation in adaptive enrichment design

Ruitao Lin, Zhao Yang, Ying Yuan, Guosheng Yin

Research output: Contribution to journalArticlepeer-review

Abstract

Clinical trial participants are often heterogeneous, which is a fundamental problem in the rapidly developing field of precision medicine. Participants heterogeneity causes considerable difficulty in the current phase III trial designs. Adaptive enrichment designs provide a flexible and intuitive solution. At the interim analysis, we enrich the subgroup of trial participants who have a higher likelihood to benefit from the new treatment. However, it is critical to control the level of the test size and maintain adequate power after enrichment of certain subgroup of participants. We develop two adaptive enrichment strategies with sample size re-estimation and verify their feasibility and practicability through extensive simulations and sensitivity analyses. The simulation studies show that the proposed methods can control the overall type I error rate and exhibit competitive improvement in terms of statistical power and expected sample size. The proposed designs are exemplified with a real trial application.

Original languageEnglish (US)
Article number106216
JournalContemporary Clinical Trials
Volume100
DOIs
StatePublished - Jan 2021

Keywords

  • Conditional power
  • Enrichment strategies
  • Patient heterogeneity
  • Phase III trial designs
  • Sample size re-estimation

ASJC Scopus subject areas

  • Pharmacology (medical)

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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