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Activity Number:
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418
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #308581 |
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Title:
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A Supremum Log-Rank Test for Adaptive Two-Stage Treatment Strategies and Corresponding Sample Size Formula
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Author(s):
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Wentao Feng*+ and Abdus S. Wahed+
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Companies:
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University of Pittsburgh and University of Pittsburgh
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Address:
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3754 Allendale Circle, Pittsburgh, PA, 15204, , , ,
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Keywords:
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Adaptive treatment strategies ; Counting process ; Proportional hazards ; Sample size formula ; Supremum log rank statistics ; Survival Function
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Abstract:
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In two-stage adaptive treatment strategies, patients receive one of the induction treatments, followed by a maintenance therapy given that the patient responded to the induction therapy. To test the difference in the effect of different induction and maintenance treatment combinations, a modified supremum weighted log-rank test is proposed. The test is applied to the data from a two-stage randomized trial for illustration and compared with standard weighted log rank test. A sample size formula is proposed based on the limiting distribution of the supremum weighted log-rank statistic. Monte Carlo simulation studies show that the proposed test provides sample sizes which are close to that obtained by standard weighted log-rank test under proportional hazard alternative. The test is more powerful than standard weighted log-rank test under non-proportional hazard alternatives.
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