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随机分组篮子试验中信息借用的贝叶斯建模策略。

Bayesian modelling strategies for borrowing of information in randomised basket trials.

作者信息

Ouma Luke O, Grayling Michael J, Wason James M S, Zheng Haiyan

机构信息

Population Health Sciences Institute Newcastle University Newcastle upon Tyne UK.

MRC Biostatistics Unit University of Cambridge Cambridge UK.

出版信息

J R Stat Soc Ser C Appl Stat. 2022 Nov;71(5):2014-2037. doi: 10.1111/rssc.12602. Epub 2022 Oct 28.

DOI:10.1111/rssc.12602
PMID:36636028
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9827857/
Abstract

Basket trials are an innovative precision medicine clinical trial design evaluating a single targeted therapy across multiple diseases that share a common characteristic. To date, most basket trials have been conducted in early-phase oncology settings, for which several Bayesian methods permitting information sharing across subtrials have been proposed. With the increasing interest of implementing randomised basket trials, information borrowing could be exploited in two ways; considering the commensurability of either the treatment effects or the outcomes specific to each of the treatment groups between the subtrials. In this article, we extend a previous analysis model based on distributional discrepancy for borrowing over the subtrial treatment effects ('treatment effect borrowing', TEB) to borrowing over the subtrial groupwise responses ('treatment response borrowing', TRB). Simulation results demonstrate that both modelling strategies provide substantial gains over an approach with no borrowing. TRB outperforms TEB especially when subtrial sample sizes are small on all operational characteristics, while the latter has considerable gains in performance over TRB when subtrial sample sizes are large, or the treatment effects and groupwise mean responses are noticeably heterogeneous across subtrials. Further, we notice that TRB, and TEB can potentially lead to different conclusions in the analysis of real data.

摘要

篮子试验是一种创新的精准医学临床试验设计,用于评估针对具有共同特征的多种疾病的单一靶向治疗。迄今为止,大多数篮子试验都在肿瘤学早期阶段进行,针对此类试验,已经提出了几种允许在子试验间共享信息的贝叶斯方法。随着开展随机篮子试验的兴趣日益增加,可以通过两种方式利用信息借用;考虑子试验间治疗效果的可比性,或每个治疗组特定结果的可比性。在本文中,我们将基于分布差异的先前分析模型从子试验治疗效果借用(“治疗效果借用”,TEB)扩展到子试验组反应借用(“治疗反应借用”,TRB)。模拟结果表明,这两种建模策略都比不借用的方法有显著优势。TRB尤其在所有操作特征上子试验样本量较小时优于TEB,而当子试验样本量较大时,或者子试验间治疗效果和组平均反应明显异质时,后者在性能上比TRB有相当大的提升。此外,我们注意到,在实际数据分析中,TRB和TEB可能会得出不同的结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/fd6b339033fd/RSSC-71-2014-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/e6f04519e255/RSSC-71-2014-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/1c757cec27e3/RSSC-71-2014-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/68de877e91c9/RSSC-71-2014-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/fd6b339033fd/RSSC-71-2014-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/e6f04519e255/RSSC-71-2014-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/1c757cec27e3/RSSC-71-2014-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/68de877e91c9/RSSC-71-2014-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdfb/9827857/fd6b339033fd/RSSC-71-2014-g001.jpg

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