Department of Methodology and Statistics, Utrecht University, 3508 TC Utrecht, The Netherlands.
Clin Trials. 2013 Feb;10(1):32-42. doi: 10.1177/1740774512464831. Epub 2012 Nov 30.
In many fields of science, event status is often recorded in intervals or at discrete points in time and can be investigated in experimental settings. Conducting such trials requires thorough planning before they are actually performed.
To investigate accrual by groups in a trial with discrete-time survival endpoints and to describe how to choose the number of accrual groups, the size of the accrual groups, and the duration of the trial to achieve a sufficient power level.
In trials with multiple time periods, the event status is recorded at the end of each period, but the event may occur at any time between the time points the measurements are taken. Therefore, time is recorded discretely, but the underlying process is continuous. To find the risk of event occurrence in each time interval, a continuous-time survival function is used and the generalized linear model is applied.
It is observed that the combination of the number of accrual groups, the size of the accrual groups, and the duration of the trial that gives a sufficient power level depends on the shape of the continuous-time survival function, the proportion of subjects who have experienced the event after a fixed number of time periods, and the size of the treatment effect.
The results of the study are only presented graphically, because there is no simple closed-form expression for finding the variance of the treatment effect. The authors provide MATLAB software to perform the power calculations.
More subjects should be recruited in each accrual group or more accrual groups should be included if the effect size or the proportion of the subjects who have experienced the event after a fixed number of time periods decreases, or the probability of the event occurrence is concentrated toward the end of the study duration.
在许多科学领域，事件状态通常以时间间隔或离散时间点记录，并可在实验环境中进行研究。进行此类试验需要在实际进行之前进行彻底的规划。
调查具有离散时间生存终点的试验中按组的累计情况，并描述如何选择累计组的数量、累计组的大小以及试验的持续时间，以达到足够的效力水平。
在具有多个时间段的试验中，事件状态在每个时间段结束时记录，但事件可能发生在测量时间点之间的任何时间。因此，时间以离散方式记录，但基础过程是连续的。为了找到每个时间间隔内事件发生的风险，使用连续时间生存函数并应用广义线性模型。
观察到，在累计组的数量、累计组的大小和试验持续时间的组合，以达到足够的效力水平，取决于连续时间生存函数的形状、在固定时间段后经历事件的受试者比例以及治疗效果的大小。
研究结果仅以图形方式呈现，因为没有简单的封闭形式表达式来找到治疗效果的方差。作者提供了 MATLAB 软件来执行效力计算。
如果效果大小或在固定时间段后经历事件的受试者比例降低，或者事件发生的概率集中在研究持续时间的最后，或者事件发生的概率集中在研究持续时间的最后，则应在每个累计组中招募更多的受试者，或者应包括更多的累计组。
