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390 – Clinical Trials: Some Recent Development on the Design and Statistical Analysis

Adaptive and Repeated Cumulative Meta-Analyses for Safety Signal Detection During a New Drug Development Process

Sponsor: Biopharmaceutical Section
Keywords: conditional power, combined test, Type I error rate control, fixed and random effect models, adaptive Bayesian design, non-inferiority

Meehyung Cho

Sanofi

Yingqiu Ma

Sanofi

Hui Quan

Sanofi

Yan Zheng

Sanofi

During a new drug development process, it is desirable to use cumulative data from all completed studies sequentially to timely detect potential safety signals. For this purpose, repeated meta-analyses can be performed on combined data from multiple completed studies. Moreover, if data from the originally planned program are not enough for ensuring power to test a specific hypothesis, adaptation in total sample size to increase the amount of safety data by adding new studies into the program can also be conducted. Without appropriate adjustment, Type I error rate will be inflated because of the repeated analyses and sample size adaptation. In this paper, we provide a systematic discussion on potential issues associated with adaptive and repeated cumulative meta-analyses conducted during a drug development process. We consider both frequentist and Bayesian approaches. Simulation results are provided to compare the performances of different methods. A new drug development example is used to demonstrate the application of the methods.

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