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：临床试验往往涉及对多个终点的评估，以全面评价干预措施的有效性和安全性。本研究提出了一种基于多变量秩次的全局非参数检验方法，用于分析临床试验中的多终点数据。与现有其他依赖对每个单独终点进行两两比较的方法不同，所述方法直接纳入观测数据的多变量秩次。通过考虑所有终点的联合秩次，该方法对临床试验中常见的数据分布多样性和删失机制具有良好的稳健性。通过大量模拟研究，我们证明了基于多变量秩次的方法在控制I类错误和获得更高统计功效方面优于现有秩次方法。模拟结果展示了利用多变量秩次的优势，并突显了该方法在不同场景下的稳健性。所提出的方法为临床试验中多终点的分析提供了有效工具，增强了结局评估的可靠性与效率。