Journal of biopharmaceutical statistics
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Multiregional clinical trials provide the potential to make safe and effective medical products simultaneously available to patients globally. As regulatory decisions are always made in a local context, this poses huge regulatory challenges. In this article we propose two conditional decision rules that can be used for medical product approval by local regulatory agencies based on the results of a multiregional clinical trial. We also illustrate sample size planning for such trials.
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Multiregional clinical trials including Japanese subjects are playing a key role in new drug development in Japan. In addition to the consideration of differences in intrinsic and extrinsic ethnic factors, deciding the sample size of Japanese subjects is an important issue when a multiregional clinical trial is intended to be used for Japanese submission. Accumulated experience suggests that there are several points to consider, such as the basic principles described in the guidance document, drug development strategy, trial phase, and disease background. The difficulty of interpreting the results of Japanese trials should also be considered.
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Comparative Study
A Bayesian inference of P(π1 > π2) for two proportions.
The statistical inference concerning the difference between two independent binominal proportions is often discussed in medical and statistical literature. However, such discussions are often based on the frequentist viewpoint rather than the Bayesian viewpoint. ⋯ We also present the results of actual clinical trials to show the utility of θ. Our findings suggest that θ can potentially provide useful information in a clinical trial.
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The main purpose of a Phase I trial of a new antitumor agent is to determine the appropriate dosing regimen and characterize the safety profile of a new molecular or monoclonal antibody. Phase II cancer clinical trials are conducted to assess the efficacy of a new anticancer therapy and to determine whether it has sufficient activity against a specific type of tumor to warrant further development. In this paper, commonly used statistical designs, based on either frequentist approaches or Bayesian methods, for Phase I and Phase II cancer clinical trials are reviewed and discussed. Future directions of designing more efficient trial are explored.