Bayesian Hierarchical Models for Subgroup Analysis.

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Yun Wang, Wenda Tu, William Koh, James Travis, Robert Abugov, Kiya Hamilton, Mengjie Zheng, Roberto Crackel, Pablo Bonangelino, Mark Rothmann
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Abstract

In conventional subgroup analyses, subgroup treatment effects are estimated using data from each subgroup separately without considering data from other subgroups in the same study. The subgroup treatment effects estimated this way may be heterogenous with high variability due to small sample sizes in some subgroups and much different from the treatment effect in the overall population. A Bayesian hierarchical model (BHM) can be used to derive more precise, and less heterogenous estimates of subgroup treatment effects that are closer to the treatment effect in the overall population. BHM assumes exchangeability in treatment effect across subgroups after adjusting for effect modifiers and other relevant covariates. In this article, we will discuss the technical details for applying one-way and multi-way BHM using summary-level statistics, and patient-level data for subgroup analysis. Four case studies based on four new drug applications are used to illustrate the application of these models in subgroup analyses for continuous, dichotomous, time-to-event, and count endpoints.

用于分组分析的贝叶斯层次模型。
在传统的亚组分析中,亚组治疗效果是使用每个亚组的数据单独估算的,而不考虑同一研究中其他亚组的数据。由于某些亚组的样本量较小,这种方法估算出的亚组治疗效果可能是异质性的,变异性较大,与总体人群的治疗效果相差甚远。贝叶斯分层模型(BHM)可用于得出更精确、异质性更小的亚组治疗效果估计值,这些估计值更接近总体人群的治疗效果。BHM 假定在调整效应修饰因子和其他相关协变量后,各亚组的治疗效果具有可交换性。在本文中,我们将讨论使用汇总级统计数据和患者级数据进行单向和多向 BHM 应用于亚组分析的技术细节。我们将通过四个基于新药申请的案例研究来说明这些模型在连续终点、二分终点、时间到事件终点和计数终点亚组分析中的应用。
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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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