Leveraging data from cross-over design that has different levels of correlation with parallel arm design in randomized controlled trial

In randomized controlled trials with parallel arms, it is often necessary and beneficial for the participants randomized to placebo arm to continue the trial by crossing over to the treatment arm after the primary endpoint measurement at the pre-specified timepoint is recorded. In scenarios like this, it is necessary to develop an analysis methodology to integrate data from the main period of analysis involving parallel arms with the data after crossing over. One of the problems that arises in the cross over design is that the underlying conditions could change after cross over and thus making it difficult to control for when comparing with the base period. The results from the cross over period may have to be adjusted in some ways to account for these differences. Also, the homogeneity of results between the parallel arms and the cross over arms after adjustment need to be evaluated and the extent to which heterogeneity can be tolerated is assessed. Multiple methodologies for performing the integrated analysis are proposed, and the power gained under different scenarios are provided here. Repeated measures with different levels of correlations due to multiple measurements of a participant are taken into consideration in the integrated analysis. Several simulated scenarios are performed to adequately evaluate the performance and robustness of different analysis. Practical considerations that need to be considered in the analysis are also provided here.

Randomized Controlled Trial (RCT)

parallel and cross-over design

integrated analysis

homogeneity

repeated measures correlation

power analysis 

Implementation and Analysis

Conference on Statistical Practice (CSP) 2024