| 摘要(英) |
This study presents a statistical method for planning and evaluating sample sizes for non-inferiority clinical trials using a gold-standard design for time-to-event data with right-censored data, where the gold-standard design includes an experimental treatment, an active control and a placebo. Additionally, in the right-censored data, both administrative and lost to follow-up were taken into account. The purpose of this study is to calculate the optimal sample size for a three-arm non-inferiority trial and the optimal allocation to each treatment group, and at the same time, a desired power can be attained under the alternative hypothesis. The method used is a semiparametric approach, and the model used is the AFT model. It is assumed that the endpoints of the trial are Weibull, Loglogistic, and Lognormal distribution, which are commonly used in medical research. In addition, we also compare with the method proposed by Karola et al. in 2013. The model they used is Cox proportional hazards model, which has a proportional hazards assumption and assumes that the endpoints to be Weibull distributed. According to our results, it is found that the optimal number of sample size of the Cox proportional hazards model under the fixed proportion sample size of each treatment will not be affected by the shape parameter of Weibull; conversely, the AFT model will be changed by the change of the shape parameter of Weibull. Finally, we applied the proposed method to a clinical trial of bladder cancer recurrence and compared it with a parametric model and a Cox proportional hazards model. |
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