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.

已提出使用具有优先权的多个结果进行收益风险分析，以用于具有两个治疗组的随机对照试验。这项研究将两组比较扩展到测试多个治疗组（例如，多剂量）的趋势，方法是根据综合结局得出的综合结果，综合结局是根据组之间受试者的成对比较得出的，或者通过对合并组的受试者进行排名而得出的。他们的优先结果。研究了Tukey趋势检验，Wilcoxon秩和检验和Jonkheere-Terpstra（JT）检验以及基于排列的趋势检验，以检测相对于复合受益风险终点而言，随着剂量增加的趋势。仿真研究表明，在各种仿真设置下，基于置换的Tukey和JT测试在类型I错误控制和功耗方面均优于其他测试。为了说明的目的，将六种方法应用于偏头痛示例数据，以确定在四个剂量组之间是否存在由四个优先结果衡量的复合受益风险终点的增加趋势。