Testing for Trend in Benefit-Risk Analysis with Prioritized Multiple Outcomes
Benefit-risk analysis using prioritized multiple outcomes has been proposed for use in randomized controlled trials with two treatment groups. This research extends the two-group comparison to testing for a trend over multiple treatment groups, for example, multiple doses, in terms of a composite outcome that is derived from pairwise comparisons of subjects between groups or by ranking subjects of pooled groups, according to their prioritized outcomes. Tukey’s trend test, Wilcoxon rank-sum test and Jonkheere-Terpstra (JT) test and their permutation-based trend tests are investigated for detection of an increasing trend over doses with respect to the composite benefit-risk endpoint. Simulation studies show that the permutation-based Tukey’s and JT tests outperform the others in terms of Type I error control and power under various simulation settings. For illustrative purpose, the six approaches are applied to a migraine example data to determine whether an increasing trend exists among four dose groups in terms of a composite benefit-risk endpoint that are measured by four prioritized outcomes.