Juarez-Colunga Elizabeth, Dean C B, Balshaw Robert
Department of Biostatistics and Informatics, University of Colorado Denver, Aurora, CO 80045, USA.
Biostatistics. 2014 Apr;15(2):234-50. doi: 10.1093/biostatistics/kxt054. Epub 2013 Dec 3.
Many clinical trials are designed to study outcome measures recorded as the number of events occurring during specific intervals, called panel data. In such data, the intervals are specified by a planned set of follow-up times. As the collection of panel data results in a partial loss of information relative to a record of the actual event times, it is important to gain a thorough understanding of the impact of panel study designs on the efficiency of the estimates of treatment effects and covariates. This understanding can then be used as a base from which to formulate appropriate designs by layering in other concerns, e.g. clinical constraints, or other practical considerations. We compare the efficiency of the analysis of panel data with respect to the analysis of data recorded precisely as times of recurrences, and articulate conditions for efficient panel designs where the focus is on estimation of a treatment effect when adjusting for other covariates. We build from the efficiency comparisons to optimize the design of panel follow-up times. We model the recurrent intensity through the common proportional intensity framework, with the treatment effect modeled flexibly as piecewise constant over panels, or groups of panels. We provide some important considerations for the design of efficient panel studies, and illustrate the methods through analysis of designs of studies of adenomas.
许多临床试验旨在研究作为特定时间段内发生的事件数量记录的结局指标，即所谓的面板数据。在这类数据中，时间段由一组计划好的随访时间指定。由于相对于实际事件时间的记录，面板数据的收集会导致部分信息丢失，因此全面了解面板研究设计对治疗效果和协变量估计效率的影响非常重要。然后，这种理解可作为一个基础，在此基础上通过纳入其他关注点（如临床限制或其他实际考虑因素）来制定合适的设计。我们将面板数据分析的效率与精确记录为复发时间的数据的分析效率进行比较，并阐明在调整其他协变量时专注于治疗效果估计的高效面板设计的条件。我们从效率比较出发，优化面板随访时间的设计。我们通过常见的比例强度框架对复发强度进行建模，将治疗效果灵活地建模为在各个面板或面板组上的分段常数。我们为高效面板研究的设计提供了一些重要的注意事项，并通过对腺瘤研究设计的分析来说明这些方法。
