RegionSizeR--用于 MRCT 中区域样本量规划的新型应用程序。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-11-01 Epub Date: 2024-08-08 DOI:10.1007/s43441-024-00679-6
Guannan Sun, Xin Sun, Huijuan Su, Yuqin Liao, Di Wei, Hanqing Ma, Xinyu Li, Ran Fan, Xiaowei Ren
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引用次数: 0

摘要

在多地区临床试验中,规划参与地区的样本量对于评价各地区治疗效果的一致性至关重要。根据 MRCT 的设计和各地区样本量的分配,一致性概率通常用于预测各地区与总体之间的一致性趋势,同时保留一定比例的总体治疗效果。在规划样本量时,还应考虑相关地区的具体入组特征。为了促进高效、统一的地区样本量规划,我们开发了 RegionSizeR,这是一个全面、用户友好的交互式网络 R 闪应用程序,可从 https://github.com/rsr-ss/RegionSizeR 上获取。这一基于模拟的应用程序可作为讨论样本量分配计划的初始点,并遵循 ICH E17 中的治疗效果保留方法。该应用程序适用于各种类型的终点和设计,包括连续终点、二元终点和时间到事件终点,适用于优效、非劣效和 MCP-Mod 设计。为确保该应用程序的有效性,我们进行了独立测试,在考虑各种情况的所有结果中,允许差异不超过 1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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RegionSizeR- A Novel App for Regional Sample Size Planning in MRCTs.

In multi-regional clinical trials, planning the sample size for participating regions is essential for the evaluation of the treatment effect consistency across regions. Based on the MRCT design and sample size allocation to regions, consistency probability is usually used to predict the consistent trend between regions and the overall population, while preserving a certain proportion of the overall treatment effect. Specific enrollment characteristics in a region of interest should also be considered during the time of the sample size planning. To facilitate efficient and harmonized regional sample size planning, we have developed RegionSizeR, a comprehensive and user-friendly interactive web-based R shiny application that can be obtained from https://github.com/rsr-ss/RegionSizeR . This simulation-based app can serve as an initial point for discussions on sample size allocation plans, following preservation of treatment effect method in ICH E17. The app accommodates various types of endpoints and designs, including continuous, binary, and time-to-event endpoints, for superiority, non-inferiority, and MCP-Mod designs. To ensure the validity of this app, independent testing is conducted allowing a discrepancy of no more than 1% across all results considering various scenarios.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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