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首页> 外文期刊>Communications in Statistics >Sample Size Determination and Rational Partition for A Multi- Regional Trial for Survival (Time-To-Event) Data with Unrecognized Heterogeneity that Interacts with Treatment
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Sample Size Determination and Rational Partition for A Multi- Regional Trial for Survival (Time-To-Event) Data with Unrecognized Heterogeneity that Interacts with Treatment

机译:具有无法识别的异质性并与治疗相互作用的生存期(事件发生时间)数据的多区域试验的样本量确定和合理划分

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摘要

To shorten the drug lag or the time lag for approval, simultaneous drug development, submission, and approval in the world may be desirable. Recently, multi-regional trials have attracted much attention from sponsors as well as regulatory authorities. Current methods for sample determination are based on the assumption that true treatment effect is uniform across regions. However, unrecognized heterogeneity among patients as ethnic or genetic factor will effect patients' survival. In this article, we address the issue that the treatment effects with unrecognized heterogeneity that interacts with treatment are among regions to design a multi-regional trial. The log-rank test is employed to deal with the heterogeneous effect size among regions. The test statistic for the overall treatment effect is used to determine the total sample size for a multi-regional trial and the consistent trend is used to rationalize partition for sample size to each region.
机译:为了缩短药物滞后或批准的时间滞后,可能需要同时开发,提交和批准药物。最近,多区域试验吸引了申办者和监管机构的广泛关注。当前用于样品确定的方法是基于以下假设:真实的治疗效果在各个区域之间是一致的。然而,由于种族或遗传因素,患者之间无法识别的异质性会影响患者的生存。在本文中,我们解决了一个问题,即与治疗相互作用的具有无法识别的异质性的治疗效果属于区域间,以设计多区域试验。使用对数秩检验来处理区域之间的异质效应大小。总体治疗效果的检验统计量用于确定多区域试验的总样本量,一致的趋势用于合理化每个区域的样本量分配。

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