Seamless phase II/III design: a useful strategy to reduce the sample size for dose optimization

Liyun Jiang, Ying Yuan

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

BACKGROUND: The traditional more-is-better dose selection paradigm, originally developed for cytotoxic chemotherapeutics, can be problematic when applied to the development of novel molecularly targeted agents. Recognizing this issue, the US Food and Drug Administration initiated Project Optimus to reform the dose optimization and selection paradigm in oncology drug development, emphasizing the need for greater attention to benefit-risk considerations. METHODS: We identify different types of phase II/III dose-optimization designs, classified according to trial objectives and endpoint types. Through computer simulations, we examine their operating characteristics and discuss the relevant statistical and design considerations for effective dose optimization. RESULTS: Phase II/III dose-optimization designs are capable of controlling family-wise type I error rates and achieving appropriate statistical power with substantially smaller sample sizes than the conventional approach while also reducing the number of patients who experience toxicity. Depending on the design and scenario, the sample size savings range from 16.6% to 27.3%, with a mean savings of 22.1%. CONCLUSIONS: Phase II/III dose-optimization designs offer an efficient way to reduce sample sizes for dose optimization and accelerate the development of targeted agents. However, because of interim dose selection, the phase II/III dose-optimization design presents logistical and operational challenges and requires careful planning and implementation to ensure trial integrity.

Original languageEnglish (US)
Pages (from-to)1092-1098
Number of pages7
JournalJournal of the National Cancer Institute
Volume115
Issue number9
DOIs
StatePublished - Sep 7 2023

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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