Bayesian Approaches for Handling Hypothetical Estimands in Longitudinal Clinical Trials With Gaussian Outcomes
Bayesian Approaches for Handling Hypothetical Estimands in Longitudinal Clinical Trials With Gaussian Outcomes
复制标题
在具有高斯结果的纵向临床试验中处理假设估计值的贝叶斯方法
DOI：
10.1080/19466315.2021.1924256
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发表时间：
2021
影响因子：
1.8
通讯作者：
K. Lu
中科院分区：
文献类型：
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作者：
G. Liu;Jiajun Liu;Fang Chen;R. Gutman;K. Lu
国际协调委员会（ICH）最近发布了E9（R1）附录，要求明确定义临床试验中与研究目标相关的评估。定义估计的挑战之一是估计对影响研究数据收集或解释的交互事件（ICEs）的处理。在处理ICEs的策略中，申办者可能更倾向于研究评估试验药物或生物制品的理论或归因疗效的假设策略。我们首先看看在不同的假设治疗条件下的几个估计。对于这些估计，ice之后的数据被忽略并视为缺失。在随机缺失、基于控制的假设和回归基线假设下，对缺失数据进行分析。根据这些假设估计的显式形式，我们研究了贝叶斯方法来获得相应的点和区间估计，并提出了避免信息正问题的贝叶斯灵敏度分析。并以三个临床试验为例说明了该方法的应用。
Abstract The International Council for Harmonisation (ICH) recently published an E9(R1) addendum that requires the estimand associated with the study objective in clinical trials to be clearly defined. One of the challenges in defining an estimand is the estimand’s handling of intercurrent events (ICEs) that affect the collection or interpretation of the data for the study. Among the strategies for handling ICEs, sponsors may prefer to examine hypothetical strategies that assess the theoretical or attributable efficacy of test drugs or biologic products. We first look at several estimands under different hypothetical treatment conditions of interest. For these estimands, the data after ICEs are ignored and treated as missing. Analyses are carried out with missing data assumptions under missing at random, control-based imputation, and return-to-baseline imputation. With the explicit forms of these hypothetical estimands derived, we investigate Bayesian approaches to obtain corresponding point and interval estimates and propose a Bayesian sensitivity analysis which avoids the information positive problem. The methods are illustrated with applications to three clinical trials.
使用多重插补方法的巢式病例对照研究。
DOI：
--
发表时间：
2014
期刊：
影响因子：
--
作者：
M. Yoshida;J. T. Ye;Y. J. Zhang;Y. Imai;S. Kimura;A. Fujiwara;T. Nishizaki;N. Kobayashi;M. Nakano;Y. Iwasa;野間久史
通讯作者：
野間久史