Bayesian Methods for Sample Size Re-estimation

样本量重新估计的贝叶斯方法

• 批准号: 2884699
• 金额: --
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2884699
• 关键词: Bayesian; Methods; Sample; Size; Re

This project will develop and evaluate new Bayesian approaches for re-estimating the sample size needed for a clinical trial as it progresses.There are always assumptions made to determine the sample size of a trial, such as the variability or size of treatment effect. These assumptions are used to decide the number of participants needed for a specified probability of success (PoS) for the definitive trial. PoS is used directly by pharmaceutical companies to make optimal decisions. When design assumptions are incorrect then the sample size may not be sufficient. Sample size reestimation approaches introduce an interim analysis to assess assumptions and alter the sample size using actual trial data.Bayesian Sample Size Reestimation (SSR) can allow incorporating other sources of data, in conjunction with the trial data, to improve the re-estimation.Areas of particular interest are:1) Can Bayesian SSR handle blinded reestimation approaches (i.e. where arm assignment is not used)?2) Would a Bayesian SSR approach improve the probability of a successful phase 3 study ascompared to frequentist approaches?3) How do methods extend to other endpoint types like binary and time-to-event?4) How can we adapt approaches to consider more complex designs such as platform, umbrellaand basket?

该项目将开发和评估新的贝叶斯方法，以重新估计其进行临床试验所需的样本量。始终有假设确定试验的样本量，例如治疗效果的可变性或大小。这些假设用于决定确定试验的指定概率（POS）所需的参与者数量。 POS由制药公司直接使用来做出最佳决策。当设计假设不正确时，样本量可能不够。样本量重新估计方法引入了临时分析，以评估假设并使用实际的试验数据更改样本量。bayesian样本量重新估计（SSR）可以允许合并其他数据来源，并结合试验数据，以改善重新估计的重新估计。特定利益的ears can bayesian ssr can bayess ssr by bay ssr a Baysian doment a doment a doment in doment in doment in doment doment doment in doment doment doment doment doment。 SSR方法提高了成功的3阶段研究的概率。3）3）方法如何扩展到诸如二进制和事件时间之类的其他端点类型？4）我们如何适应方法来考虑更复杂的设计，例如平台，伞形篮子？