It is a common practice in randomized clinical trials with the standard survival outcome to follow patients until a prespecified number of events have been observed, a type of trial known as the event-driven trial. The event-driven design ensures that the target power for a specified type 1 error rate is achieved to detect the target hazard ratio, regardless of the specification of other quantities. To understand the treatment effect for chronic conditions, the analysis of recurrent events has gained popularity in randomized controlled trials, particularly large-scale confirmatory trials. In the absence of within-subject correlation among multiple events, a similar event-driven design can be employed for recurrent event outcomes. On the other hand, in the presence of the within-subject correlation, one needs to model the correlation among recurrent events in evaluating power and setting the sample size. However, information useful in modeling the within-subject correlation is limited at the design stage. Failing to consider the correlation properly may lead to underpowered studies. We propose an event-driven type design for recurrent event outcomes. Our method ensures the target power for the target treatment effect, regardless of the specification of other quantities, by monitoring the robust variance under the marginal rates/means model in a blinded manner. We investigate the operating characteristics of the proposed monitoring procedure in simulation studies. The results of simulation studies showed that the proposed blinded monitoring procedure controlled the power well so that the test possessed the target power and did not lead to serious inflation of the type 1 error rate. Furthermore, we illustrate the proposed method using a real clinical trial dataset.

翻译：在采用标准生存结局的随机临床试验中，通常的做法是随访患者直至观察到预设数量的事件，此类试验被称为事件驱动型试验。事件驱动设计确保在指定的I类错误率下，无论其他量的设定如何，都能达到检测目标风险比所需的检验效能。为理解慢性疾病的治疗效果，复发事件分析在随机对照试验（尤其是大规模确证性试验）中日益普及。当多个事件之间不存在受试者内相关性时，可采用类似的事件驱动设计处理复发事件结局。另一方面，若存在受试者内相关性，则需在评估效能和设定样本量时对复发事件间的相关性进行建模。然而，在设计阶段可用于建模受试者内相关性的信息有限。未能恰当考虑相关性可能导致研究效能不足。本文针对复发事件结局提出一种事件驱动型设计。该方法通过在盲态下监测边际率/均值模型的稳健方差，确保无论其他量的设定如何，都能对目标治疗效果达到目标检验效能。我们通过模拟研究考察了所提监测方法的操作特征。模拟研究结果表明，所提出的盲态监测方法能良好控制检验效能，使检验具备目标效能且不会导致I类错误率的严重膨胀。此外，我们使用真实临床试验数据集对所提方法进行了示例说明。