Two-stage screened selection designs for randomized phase II trials with time-to-event endpoints

Jianrong Wu1, Haitao Pan2, Chia-Wei Hsu2

  • 1Biostatistics Shared Resource Facility, Comprehensive Cancer Center University of New Mexico, Albuquerque, NM, USA.

Insights

This study introduces a new screened selection design (SSD) for phase II clinical trials, specifically for time-to-event data. This method efficiently identifies superior treatment arms while controlling statistical errors, benefiting areas like pediatric cancer research.

Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Oncology Research

Background:

  • Phase II multiarm studies are valuable for exploring new treatments, especially in areas of unmet need like pediatric cancer.
  • Existing screened selection designs (SSD) are limited to binary endpoints, necessitating new methods for time-to-event data.
  • Faster patient recruitment and more treatment options are advantages of multiarm over traditional two-arm trials.

Purpose of the Study:

  • To propose and evaluate novel two-stage screened selection designs (SSD) for randomized phase II trials with time-to-event endpoints.
  • To provide methods that ensure a high probability of selecting superior treatment arms.
  • To maintain control over the type I error rate when comparing treatments against a common external control.

Main Methods:

  • Development of two-stage SSD and its variant for time-to-event data in phase II randomized trials.
  • Derivation of sample size calculations tailored for the proposed designs.
  • Validation through simulation studies to assess operating characteristics.

Main Results:

  • The proposed SSD methods demonstrate a high probability of identifying superior treatment arms.
  • Effective control of the type I error rate was confirmed in simulations.
  • The design was successfully applied to three real-world clinical trials.

Conclusions:

  • The novel two-stage SSD offers an efficient approach for phase II randomized trials with time-to-event outcomes.
  • This methodology enhances the selection of promising treatments in areas with unmet needs.
  • An accessible R package, frequentistSSD, has been developed for practical application.

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