On the inclusion of non-concurrent controls in platform trials with an interim analysis
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含期中分析的平台试验如何纳入非同期对照
- 研究问题
- 平台试验借用非同期对照并调整时间趋势时，先进入试验臂的期中分析会如何影响后进入试验臂的处理效应估计？
- 方法与思路
- 作者研究两个实验臂共享对照的设计，以阶梯函数调整时间趋势，分析期中决策引起的偏差，并提出新估计量进行模拟比较。
- 材料陈述的贡献
- 摘要称第一臂的期中分析可能使第二臂估计产生偏差；新估计量在模拟中减少偏差及一类错误膨胀，并较仅用同期对照提高功效。
- 阅读关注点
- 核对期中停止规则、边际与条件偏差的区别、时间阶梯划分，以及新估计量如何处理期中选择和时间趋势两类偏差。
- 阅读边界
- 这是 arXiv 预印本，同行评审和期刊接收均未核实；摘要未提供设计参数或误差控制条件，模拟结论不能直接推广到所有平台试验。
原文摘要
The analysis of platform trials can be enhanced by utilizing non-concurrent controls. Since including this data might also introduce bias in the treatment effect estimators if time trends are present, methods for incorporating non-concurrent controls adjusting for time have been proposed. However, so far their behavior has not been systematically investigated in platform trials that include interim analyses. To evaluate the impact of an interim analysis in trials utilizing non-concurrent controls, we consider a platform trial featuring two experimental arms and a shared control, with the second experimental arm entering later. We focus on a frequentist regression model that uses non-concurrent controls to estimate the treatment effect of the second arm and adjusts for time using a step function to account for temporal changes. We show that performing an interim analysis in Arm 1 may introduce bias in the point estimation of the effect in Arm 2, if the regression model is used without adjustment, and investigate how the marginal bias and bias conditional on the first arm continuing after the interim depend on different trial design parameters. Moreover, we propose a new estimator of the treatment effect in Arm 2, aiming to eliminate the bias introduced by both the interim analysis in Arm 1 and the time trends, and evaluate its performance in a simulation study. The newly proposed estimator is shown to substantially reduce the bias and type I error rate inflation while leading to power gains compared to an analysis using only concurrent controls.