ORACLE II – Optimal Rules for Adaptive Designs with reCalculation of sampLE size

在标准的临床试验设计中，所有设计参数都必须在计划阶段确定。因此，特别是样本量的选择是一个至关重要的问题。它是基于假设的治疗效果大小、选择的显著水平、期望的功率和应用测试统计的分布。然而，试验规划阶段对真实潜在效应大小的普遍不确定性可能会导致错误的规划假设，因此意味着对样本量的错误说明。适应性设计提供了在正在进行的试验期间修改试验设计的可能性，并允许纠正错误的规划假设。在中期分析中，决定是否应分别以无效或有效为由停止试验，或试验是否进入第二阶段。在后一种情况下，可以调整许多设计参数，特别是所需的样本量。因此，第二阶段的样本量通常由预先定义的规则确定，并且通常作为中期结果的函数提供。与适应性设计相关的挑战有几个。海德堡和柏林的这项联合提案的总体目标是继续DFG资助的甲骨文项目的成功工作。在正在进行的甲骨文项目中，针对不同的优化和性能标准改进和优化了重新计算规则。在新的甲骨文II项目中，前一个项目的结果和方法应进一步改进和推广，特别是在非正态分布的结果、具有一项以上中期分析的设计和两组以上的设计方面。甲骨文项目只关注适应性设计中的样本量方面，而新项目甲骨文II的关注点更广：只有在同时解决与适应性设计相关的其他挑战的情况下，足够的样本量重新计算规则才会对实际应用产生相关影响。最突出的要求是足够的、无偏的治疗效果估计器和可信区间以及相应的p值。上述目标将在以下工作包和时间范围内处理：·工作包1(1-12月，柏林)：评估样本量重新计算的性能·工作包2(1-12个月，海德堡)：样本量调整的自适应设计的点估计数、可信区间、p值·工作包3(13-24月，柏林和海德堡)：具有两个以上手臂或阶段的设计的样本量重新计算·工作包4(25-36个月，柏林和海德堡)：二进制和事件间隔时间终点的扩展

In standard clinical trial designs, all design parameters must be fixed during the planning stage. Thereby, in particular the choice of the sample size is a crucial issue. It is based on the assumed treatment effect size, the chosen level of significance, the desired power, and the distribution of the applied test statistic. However, the common uncertainty on the true underlying effect size in the planning stage of a trial may result in wrong planning assumptions and, therefore, imply misspecification of the sample size. Adaptive designs provide the possibility to modify the trial design during the ongoing trial and allow correcting for wrong planning assumptions. At the interim analysis, it is decided whether the trial should be stopped for futility or efficacy, respectively, or whether the trial enters the second stage. In the latter case, many design parameters can be adapted, in particular the required sample size. Thereby, the second stage sample size is usually determined by predefined rules and is usually provided as a function of the interim result.The question of a sensible choice of the specific adaptive trial design arises intuitively. There are several challenges related to adaptive designs. The overall aim of this joint proposal between Heidelberg and Berlin is to continue the successful work of the previous DFG-funded project ORACLE. Within the ongoing ORACLE project, recalculation rules were improved and optimized with respect to different optimization and performance criteria. Within the new ORACLE II project, the results and methods of the previous project should be further improved an extended, in particular with respect to non-normally distributed outcomes, designs with more than one interim analysis, and designs with more than two groups. Whereas the ORACLE project exclusively focused on the aspect of sample size in adaptive designs, the focus of the new project ORACLE II is broader: An adequate sample size recalculation rule only has a relevant impact for practical applications if other challenges related to adaptive designs are addressed simultaneously. The most prominent requirements are adequate, unbiased treatment effect estimators and confidence intervals along with corresponding p-values. The above objectives will be addressed within the following work packages and time frames:• Work package 1 (Month 1-12, Berlin): Assessing performance of sample size recalculation • Work package 2 (Months 1-12, Heidelberg): Point estimators, confidence intervals, p-values for adaptive designs with sample size adaptions• Work package 3 (Months 13-24, Berlin & Heidelberg): Sample size recalculation in designs with more than two arms or stages• Work package 4 (Months 25-36, Berlin & Heidelberg): Extensions to binary and time-to-event endpoints