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Supremum weighted log-rank test and sample size for comparing two-stage adaptive treatment strategies
Authors:Feng, Wentao   Wahed, Abdus S.
Affiliation:Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania 15261, U.S.A. wentao.feng{at}novartis.com wahed{at}pitt.edu
Abstract:In two-stage adaptive treatment strategies, patients receivean induction treatment followed by a maintenance therapy, giventhat the patient responded to the induction treatment they received.To test for a difference in the effects of different inductionand maintenance treatment combinations, a modified supremumweighted log-rank test is proposed. The test is applied to adataset from a two-stage randomized trial and the results arecompared to those obtained using a standard weighted log-ranktest. A sample-size formula is proposed based on the limitingdistribution of the supremum weighted log-rank statistic. Thesample-size formula reduces to Eng and Kosorok's sample-sizeformula for a two-sample supremum log-rank test when there isno second randomization. Monte Carlo studies show that the proposedtest provides sample sizes that are close to those obtainedby standard weighted log-rank test under a proportional hazardsalternative. However, the proposed test is more powerful thanthe standard weighted log-rank test under non-proportional hazardsalternatives.
Keywords:Adaptive treatment strategy    Brownian motion    Censoring distribution    Counting process    Proportional hazard    Sample-size formula    Supremum log-rank statistic    Survival function    Two-stage design
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