Owzar Kouros, Jung Sin-Ho
Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27705, USA.
Clin Trials. 2008;5(3):209-21. doi: 10.1177/1740774508091748.
The primary clinical endpoint in many phase II studies in cancer is a time-to-event outcome subject to potential censoring. The decision in favor of abandoning or continuing investigation of the protocol regimen is typically based on the amount of statistical evidence suggesting an improvement compared to a given historical control. The primary statistical endpoint would typically be the median of the time-to-event distribution of the clinical endpoint. For the purpose of sample size or power calculations, software implementing parametric and nonparametric median tests, is freely available. The main assumptions are those of Exponential survival and a Uniform right-censoring mechanism.
The performance of the parametric and nonparametric methods is compared to that of using a binomial endpoint based on dichotomizing the event time at a clinically relevant landmark. As sufficient details on the various methods and related designs for phase II clinical design with survival endpoints are provided, this article should also serve as a comparative reference on these three methods for designing phase II studies in cancer with time-to-event endpoints.
The statistical performance, by virtue of considering the type I and II error rates, of the three methods is compared by carrying out a comprehensive simulation study.
The parametric method may fail to control the type I error rate if the underlying survival distribution is not Exponential, while the nonparametric method may fail to control the type I error rate as the sample sizes for phase II studies are typically small. Both of these methods may be sensitive to the distribution of the censoring variable.
The results provided in this article are mostly discussed in the framework of specific examples and by using specific implementations of the tests. As such the results may not be universally generalizable. The recommended method has some drawbacks if patients are censored before the landmark of interest.
A method that should be considered for the purpose of the statistical design and decision rule for phase II studies in cancer is the employment of a binomial endpoint based on dichotomizing the event time at a clinically relevant landmark.
在许多癌症的II期研究中,主要临床终点是一个可能受到删失影响的事件发生时间结局。支持放弃或继续对方案治疗进行研究的决策通常基于与给定历史对照相比表明有改善的统计证据量。主要统计终点通常是临床终点事件发生时间分布的中位数。为了进行样本量或效能计算,可免费获得实现参数化和非参数化中位数检验的软件。主要假设是指数生存和均匀右删失机制。
将参数化和非参数化方法的性能与基于在临床相关界标处对事件时间进行二分的二项式终点的性能进行比较。由于提供了关于生存终点的II期临床设计的各种方法和相关设计的充分细节,本文也应作为这三种用于设计具有事件发生时间终点的癌症II期研究方法的比较参考。
通过进行全面的模拟研究,比较这三种方法在考虑I型和II型错误率方面的统计性能。
如果潜在生存分布不是指数分布,参数化方法可能无法控制I型错误率,而非参数化方法可能由于II期研究的样本量通常较小而无法控制I型错误率。这两种方法可能对删失变量的分布敏感。
本文提供的结果大多在特定示例框架内并通过使用检验的特定实现进行讨论。因此,结果可能无法普遍推广。如果患者在感兴趣的界标之前被删失,推荐的方法有一些缺点。
对于癌症II期研究的统计设计和决策规则,应考虑的一种方法是基于在临床相关界标处对事件时间进行二分的二项式终点。