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AI 根据所提供的论文材料归类:摘要重点是临床试验的序贯监测、停试和延迟响应推断,未明确讨论因果识别方法,所列细分缺少直接对应方向。

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关注这篇论文的作者
Lisa V. Hampson

延迟响应的组序贯检验(附讨论)

研究问题
临床试验中部分受试者在中期分析或停试后才产生结局,如何将这些延迟响应纳入组序贯设计并完成有效推断?
方法与思路
作者构造处理尚未响应受试者的组序贯检验,结合误差花费与信息监测,并通过长短期结局联合建模缓解延迟带来的效率损失。
材料陈述的贡献
摘要称,新设计可处理不可预测的组大小和干扰参数,分析延迟对预期样本量节约的影响,并给出终止时的 p 值和置信区间。
阅读关注点
应核对停止决策后数据的纳入规则、误差控制条件、未知方差的处理,以及短期结局联合模型如何支持长期结局推断。
阅读边界
仅依据所给 Crossref 摘要;摘要未列出误差控制条件、最优设计细节或数值结果,也未提供题名所指讨论部分的内容。

原文摘要

Summary 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.

笔记与分组
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