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Activity Number:
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73
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Type:
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Contributed
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Date/Time:
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Sunday, August 6, 2006 : 4:00 PM to 5:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #307606 |
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Title:
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Optimal Adaptive Designs in Phase II Trials
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Author(s):
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Anindita Banerjee*+ and Anastasios A. Tsiatis
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Companies:
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North Carolina State University and North Carolina State University
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Address:
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2311 Champion Court, Raleigh, NC, 27606,
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Keywords:
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two-stage adaptive design ; backward induction ; Bayesian decision theory ; simulated annealing
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Abstract:
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Phase-II trials provide a platform where, on the basis of the efficacy of the drugs, ineffective drugs are screened out and promising drugs move to the next phase. Simon (1989) proposed optimal fixed two-stage designs which minimize the expected sample size under the null hypothesis. We have derived optimal adaptive designs at the null that perform better than Simon's design, although the gains are modest (Banerjee and Tsiatis 2006). We further explore optimal adaptive designs that minimize the expected sample size at the alternative hypothesis, at a probability midpoint between the null and alternative hypothesis and a weighted combination of the response probabilities. We also construct an envelope function that gives the lowest expected sample size for any possible value of the response probability. The different designs are compared to each other as well as the envelope function.
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