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A Practical Simulation Method to Calculate Sample Size of Group Sequential Trials for Time-to-Event Data under Exponential and Weibull Distribution

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  • Zhiwei Jiang
  • Ling Wang
  • Chanjuan Li
  • Jielai Xia
  • Hongxia Jia

Abstract

Group sequential design has been widely applied in clinical trials in the past few decades. The sample size estimation is a vital concern of sponsors and investigators. Especially in the survival group sequential trials, it is a thorny question because of its ambiguous distributional form, censored data and different definition of information time. A practical and easy-to-use simulation-based method is proposed for multi-stage two-arm survival group sequential design in the article and its SAS program is available. Besides the exponential distribution, which is usually assumed for survival data, the Weibull distribution is considered here. The incorporation of the probability of discontinuation in the simulation leads to the more accurate estimate. The assessment indexes calculated in the simulation are helpful to the determination of number and timing of the interim analysis. The use of the method in the survival group sequential trials is illustrated and the effects of the varied shape parameter on the sample size under the Weibull distribution are explored by employing an example. According to the simulation results, a method to estimate the shape parameter of the Weibull distribution is proposed based on the median survival time of the test drug and the hazard ratio, which are prespecified by the investigators and other participants. 10+ simulations are recommended to achieve the robust estimate of the sample size. Furthermore, the method is still applicable in adaptive design if the strategy of sample size scheme determination is adopted when designing or the minor modifications on the program are made.

Suggested Citation

  • Zhiwei Jiang & Ling Wang & Chanjuan Li & Jielai Xia & Hongxia Jia, 2012. "A Practical Simulation Method to Calculate Sample Size of Group Sequential Trials for Time-to-Event Data under Exponential and Weibull Distribution," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-12, September.
    • Handle: RePEc:plo:pone00:0044013
    DOI: 10.1371/journal.pone.0044013
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    References listed on IDEAS

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    1. Shen Y. & Cai J., 2003. "Sample Size Reestimation for Clinical Trials With Censored Survival Data," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 418-426, January.
    2. Lu Chi & H. M. James Hung & Sue-Jane Wang, 1999. "Modification of Sample Size in Group Sequential Clinical Trials," Biometrics, The International Biometric Society, vol. 55(3), pages 853-857, September.
    3. Zhiguo Li & Susan A. Murphy, 2011. "Sample size formulae for two-stage randomized trials with survival outcomes," Biometrika, Biometrika Trust, vol. 98(3), pages 503-518.
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    Cited by:

    1. Deborah Plana & Geoffrey Fell & Brian M. Alexander & Adam C. Palmer & Peter K. Sorger, 2022. "Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Dominic Magirr & Thomas Jaki & Franz Koenig & Martin Posch, 2016. "Sample Size Reassessment and Hypothesis Testing in Adaptive Survival Trials," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-14, February.

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