Hilgers Ralf-Dieter, Manolov Martin, Heussen Nicole, Rosenberger William F
Department of Medical Statistics, RWTH Aachen University, Aachen, Germany.
Department of Biostatistics, Sigmund Freud University, Vienna, Austria.
Stat Methods Med Res. 2020 Jun;29(6):1715-1727. doi: 10.1177/0962280219846146. Epub 2019 May 10.
Among various design aspects, the choice of randomization procedure have to be agreed on, when planning a clinical trial stratified by center. The aim of the paper is to present a methodological approach to evaluate whether a randomization procedure mitigates the impact of bias on the test decision in clinical trial stratified by center.
We use the weighted test to analyze the data from a clinical trial stratified by center with a two-arm parallel group design, an intended 1:1 allocation ratio, aiming to prove a superiority hypothesis with a continuous normal endpoint without interim analysis and no adaptation in the randomization process. The derivation is based on the weighted test under misclassification, i.e. ignoring bias. An additive bias model combing selection bias and time-trend bias is linked to different stratified randomization procedures.
Various aspects to formulate stratified versions of randomization procedures are discussed. A formula for sample size calculation of the weighted test is derived and used to specify the tolerated imbalance allowed by some randomization procedures. The distribution of the weighted test under misclassification is deduced, taking the sequence of patient allocation to treatment, i.e. the randomization sequence into account. An additive bias model combining selection bias and time-trend bias at strata level linked to the applied randomization sequence is proposed. With these before mentioned components, the potential impact of bias on the type one error probability depending on the selected randomization sequence and thus the randomization procedure is formally derived and exemplarily calculated within a numerical evaluation study.
The proposed biasing policy and test distribution are necessary to conduct an evaluation of the comparative performance of (stratified) randomization procedure in multi-center clinical trials with a two-arm parallel group design. It enables the choice of the best practice procedure. The evaluation stimulates the discussion about the level of evidence resulting in those kind of clinical trials.
在临床试验设计的各个方面中,当计划进行一项按中心分层的临床试验时,必须就随机化程序的选择达成一致。本文的目的是提出一种方法,以评估在按中心分层的临床试验中,随机化程序是否能减轻偏倚对检验决策的影响。
我们使用加权检验来分析一项按中心分层的临床试验数据,该试验采用双臂平行组设计,预期分配比例为1:1,旨在通过连续正态终点证明优效性假设,且无期中分析,随机化过程无调整。该推导基于误分类情况下的加权检验,即忽略偏倚。一个结合选择偏倚和时间趋势偏倚的加性偏倚模型与不同的分层随机化程序相关联。
讨论了制定分层随机化程序版本的各个方面。推导了加权检验样本量计算的公式,并用于确定一些随机化程序允许的可容忍不平衡。推导了误分类情况下加权检验的分布,同时考虑了患者分配到治疗组的顺序,即随机化序列。提出了一个在分层水平上结合选择偏倚和时间趋势偏倚并与应用的随机化序列相关联的加性偏倚模型。借助上述这些组成部分,正式推导了偏倚对一类错误概率的潜在影响,该影响取决于所选的随机化序列以及随机化程序,并在数值评估研究中进行了示例性计算。
所提出的偏倚策略和检验分布对于评估双臂平行组设计的多中心临床试验中(分层)随机化程序的比较性能是必要的。它有助于选择最佳实践程序。该评估引发了关于这类临床试验证据水平的讨论。