Sample size reestimation can be a powerful tool to ensure that a clinical trial meets its prespecified power requirements when uncertainty regarding a design parameter exists at the planning stage. However, long term primary endpoints can be harmful to the efficiency of this trial design. If recruitment is continued while treatment outcomes are awaited, long delay can potentially lead to a large number of pipeline participants being recruited in the trial that do not contribute to the interim analysis. This may lead to a larger number of recruited participants than are actually deemed required, resulting in an overpowered trial with high cost. This paper studies the exact impact of such outcome delay on the efficiency of internal pilot type SSR designs. The distribution of the final sample size post SSR is obtained under various delay lengths for both continuous and binary outcome data, how delay impacts the precision of the final sample size estimate is then discussed. Precisely, the impact of delay on this precision is assessed through RMSE, as well as two more novel metrics, termed the delay impact and cost. The results indicate that with increase in delay length, the delay impact increases, inflating average sample size and power. However, the severity of the effect of delayed outcomes depends highly on the exact trial setting. Trials where the reestimated sample size is smaller than originally planned suffer the most from delayed outcomes, often leading to an overpowered trial. However, the impact of delay is substantially less if the original planned sample size remains smaller than the reestimated sample size.

翻译：样本量重估计是一种强有力的工具，可确保在规划阶段存在设计参数不确定性时，临床试验满足预设的检验效能要求。然而，长期主要终点可能损害此类试验设计的效率。若在等待治疗结果期间继续招募受试者，长期延迟可能导致试验中招募大量未纳入期中分析的流水线参与者，使得实际招募人数超出实际所需，从而产生检验效能过高且成本高昂的试验。本文研究了这种结果延迟对内部预试验型SSR设计效率的确切影响。针对连续型和二分类结局数据，推导了不同延迟时长下SSR后最终样本量的分布，进而讨论了延迟如何影响最终样本量估计的精确度。具体而言，通过均方根误差以及两种新的衡量指标（称为延迟影响和成本）评估延迟对该精确度的作用。结果表明，随着延迟时长增加，延迟影响增大，导致平均样本量和检验效能膨胀。但延迟结果的严重程度高度依赖于具体的试验设置。当重估计样本量小于原计划时，试验受延迟结果影响最大，往往导致检验效能过高。然而，若原计划样本量仍小于重估计样本量，则延迟的影响显著降低。