Composite endpoints are widely used as primary endpoints in clinical trials. Designing trials with time-to-event endpoints can be particularly challenging because the proportional hazard assumption usually does not hold when using a composite endpoint, even when the premise remains true for their components. Consequently, the conventional formulae for sample size calculation do not longer apply. We present the R package CompAREdesign by means of which the key elements of trial designs, such as the sample size and effect sizes, can be computed based on the information on the composite endpoint components. CompAREdesign provides the functions to assess the sensitivity and robustness of design calculations to variations in initial values and assumptions. Furthermore, we describe other features of the package, such as functions for the design of trials with binary composite endpoints, and functions to simulate trials with composite endpoints under a wide range of scenarios.

翻译：在临床试验中,广泛将复合端点作为主端点。设计有时间到活动端点的试验可能特别具有挑战性,因为在使用复合端点时,即使其组成部分的前提仍然不变,相称的危险假设通常并不有效。因此,用于计算样本大小的传统公式不再适用。我们提出R包Comparedesign,据此可以根据复合端点组成部分的信息计算试验设计的关键要素,如样本大小和影响大小。Compaderdection提供功能,评估设计计算对初始值和假设变化的敏感性和稳健性。此外,我们描述了该包的其他特征,例如用二元复合端点设计试验的功能,以及在各种假设情况下以复合端点模拟试验的功能。