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Supremum weighted log-rank test and sample size for comparing two-stage adaptive treatment strategies

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  • Wentao Feng
  • Abdus S. Wahed

Abstract

In two-stage adaptive treatment strategies, patients receive an induction treatment followed by a maintenance therapy, given that the patient responded to the induction treatment they received. To test for a difference in the effects of different induction and maintenance treatment combinations, a modified supremum weighted log-rank test is proposed. The test is applied to a dataset from a two-stage randomized trial and the results are compared to those obtained using a standard weighted log-rank test. A sample-size formula is proposed based on the limiting distribution of the supremum weighted log-rank statistic. The sample-size formula reduces to Eng and Kosorok's sample-size formula for a two-sample supremum log-rank test when there is no second randomization. Monte Carlo studies show that the proposed test provides sample sizes that are close to those obtained by standard weighted log-rank test under a proportional hazards alternative. However, the proposed test is more powerful than the standard weighted log-rank test under non-proportional hazards alternatives. Copyright 2008, Oxford University Press.

Suggested Citation

  • Wentao Feng & Abdus S. Wahed, 2008. "Supremum weighted log-rank test and sample size for comparing two-stage adaptive treatment strategies," Biometrika, Biometrika Trust, vol. 95(3), pages 695-707.
    • Handle: RePEc:oup:biomet:v:95:y:2008:i:3:p:695-707
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    File URL: http://hdl.handle.net/10.1093/biomet/asn025
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    Cited by:

    1. Tang, Xinyu & Melguizo, Maria, 2015. "DTR: An R Package for Estimation and Comparison of Survival Outcomes of Dynamic Treatment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i07).
    2. Lu Tian & Haoda Fu & Stephen J. Ruberg & Hajime Uno & Lee†Jen Wei, 2018. "Efficiency of two sample tests via the restricted mean survival time for analyzing event time observations," Biometrics, The International Biometric Society, vol. 74(2), pages 694-702, June.

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