Department of Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA.
Biostatistics and Research Decision Sciences, Merck & Co, Inc, Philadelphia, USA.
Stat Med. 2018 Oct 15;37(23):3280-3292. doi: 10.1002/sim.7834. Epub 2018 Jun 11.
Two-period two-treatment (2×2) crossover designs are commonly used in clinical trials. For continuous endpoints, it has been shown that baseline (pretreatment) measurements collected before the start of each treatment period can be useful in improving the power of the analysis. Methods to achieve a corresponding gain for censored time-to-event endpoints have not been adequately studied. We propose a method in which censored values are treated as missing data and multiply imputed using prespecified parametric event time models. The event times in each imputed data set are then log-transformed and analyzed using a linear model suitable for a 2×2 crossover design with continuous endpoints, with the difference in period-specific baselines included as a covariate. Results obtained from the imputed data sets are synthesized for point and confidence interval estimation of the treatment ratio of geometric mean event times using model averaging in conjunction with Rubin's combination rule. We use simulations to illustrate the favorable operating characteristics of our method relative to two other methods for crossover trials with censored time-to-event data, ie, a hierarchical rank test that ignores the baselines and a stratified Cox model that uses each study subject as a stratum and includes period-specific baselines as a covariate. Application to a real data example is provided.
两周期两处理（2×2）交叉设计在临床试验中经常使用。对于连续终点，已经表明在每个治疗期开始前收集的基线（预处理）测量值可用于提高分析的功效。对于删失的生存时间终点，实现相应增益的方法尚未得到充分研究。我们提出了一种方法，其中将删失值视为缺失数据，并使用预指定的参数事件时间模型进行多重插补。然后，将每个插补数据集中的事件时间转换为对数，并使用适合具有连续终点的 2×2 交叉设计的线性模型进行分析，其中包含特定于时期的基线差异作为协变量。使用模型平均结合 Rubin 的组合规则，从插补数据集中综合获得治疗比值的几何均数事件时间的点估计和置信区间估计。我们使用模拟来说明我们的方法相对于交叉试验中具有删失生存时间数据的另外两种方法的有利操作特性，即忽略基线的层次秩检验和使用每个研究对象作为层并包含特定于时期的基线作为协变量的分层 Cox 模型。提供了对真实数据示例的应用。
