Group sequential tests for delayed responses
Group sequential tests for delayed responses
复制标题
DOI：
10.1111/j.1467-9868.2012.01030.x
复制
发表时间：
2013-01-01
影响因子：
5.8
通讯作者：
Jennison, Christopher
中科院分区：
文献类型：
--
作者：
Hampson, Lisa V.;Jennison, Christopher
常规使用组序贯方法来监测临床试验，并在有证据表明治疗效果、缺乏效果或担心患者安全时提前停止。在许多研究中，临床关注的缓解是在治疗开始后一段时间测量的，并且在每次中期分析时都有受试者接受了治疗但尚未缓解。我们制定了一种新的形式的组序贯检验，它给出了一个适当的治疗这些“管道”的主题，这些测试可以应用，即使在决定停止试验后继续积累的数据是出乎意料的。我们通过一系列示例来说明我们的方法。我们定义这些新设计的错误支出版本，处理不可预测的组大小，并提供一个信息监控框架，可以容纳滋扰参数，如未知的响应方差。通过研究我们的新设计的最佳版本，我们展示了如何降低预期样本量的好处，通常是由一组序贯检验时，有一个延迟响应减少。较大延迟的效率损失可以通过在相关的短期终点上合并数据来改善，为两个终点拟合联合模型，但仍然对原始的长期终点进行推断。我们在新检验终止时获得p值和置信区间。
Group sequential methods are used routinely to monitor clinical trials and to provide early stopping when there is evidence of a treatment effect, a lack of an effect or concerns about patient safety. In many studies, the response of clinical interest is measured some time after the start of treatment and there are subjects at each interim analysis who have been treated but are yet to respond. We formulate a new form of group sequential test which gives a proper treatment of these 'pipeline' subjects; these tests can be applied even when the continued accrual of data after the decision to stop the trial is unexpected. We illustrate our methods through a series of examples. We define error spending versions of these new designs which handle unpredictable group sizes and provide an information monitoring framework that can accommodate nuisance parameters, such as an unknown response variance. By studying optimal versions of our new designs, we show how the benefits of lower expected sample size that are normally achieved by a group sequential test are reduced when there is a delay in response. The loss of efficiency for larger delays can be ameliorated by incorporating data on a correlated short-term end point, fitting a joint model for the two end points but still making inferences on the original, longer-term end point. We derive p-values and confidence intervals on termination of our new tests.