Clinical trials often involve the assessment of multiple endpoints to comprehensively evaluate the efficacy and safety of interventions. In the work, we consider a global nonparametric testing procedure based on multivariate rank for the analysis of multiple endpoints in clinical trials. Unlike other existing approaches that rely on pairwise comparisons for each individual endpoint, the proposed method directly incorporates the multivariate ranks of the observations. By considering the joint ranking of all endpoints, the proposed approach provides robustness against diverse data distributions and censoring mechanisms commonly encountered in clinical trials. Through extensive simulations, we demonstrate the superior performance of the multivariate rank-based approach in controlling type I error and achieving higher power compared to existing rank-based methods. The simulations illustrate the advantages of leveraging multivariate ranks and highlight the robustness of the approach in various settings. The proposed method offers an effective tool for the analysis of multiple endpoints in clinical trials, enhancing the reliability and efficiency of outcome evaluations.

翻译：临床试验常涉及多个终点的评估，以全面评价干预措施的有效性和安全性。本研究提出一种基于多元秩的全局非参数检验方法，用于分析临床试验中的多个终点。与依赖每个单独终点进行配对比较的现有方法不同，本方法直接纳入观测值的多元秩。通过考虑所有终点联合排序，该方法对临床试验中常见的数据分布异质性和删失机制具有稳健性。通过大量模拟研究，我们证明了基于多元秩的方法在控制I类错误和获得更高统计功效方面优于现有秩方法。模拟结果展示了利用多元秩的优势，并强调了该方法在各种场景下的稳健性。本方法为临床试验多终点分析提供了有效工具，提升了结局评估的可靠性与效率。