The Win Ratio at the Design Stage of Clinical Trials
临床试验设计阶段的胜率比AI 解读 ↓
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临床试验设计阶段的胜率比
- 研究问题
- 对具有优先层级的复合临床结局，胜率比分析何时具有较高检验功效，如何按置信区间宽度规划样本量？
- 方法与思路
- 作者通过案例和模拟比较胜率比、单终点及首次事件时间分析，并提出基于目标区间宽度的样本量公式。
- 材料陈述的贡献
- 摘要称胜率比的功效收益取决于各层级结局的效应结构，并提出精度导向设计公式，也指出高位连续结局的局限。
- 阅读关注点
- 应核对胜负与平局的规则、结局排序、样本量公式的适用条件，以及功效比较采用的数据生成机制和检验水平。
- 阅读边界
- 这是预印本，同行评审及接收未核实。摘要报告的功效优势依赖模拟场景，且作者明确提出需扩展结局类型与机制。
原文摘要
The win ratio offers a flexible approach to incorporate the hierarchy of clinical outcomes into the analysis of a composite endpoint, enabling simultaneous consideration of multiple outcome types, unlike traditional time-to-first-event (TTFE) analysis or focus on a single outcome. We examined the statistical power of the win ratio compared to single-endpoint analyses and TTFE analysis through a case study and simulation studies. Furthermore, we provide a novel formula to estimate the required sample size for win ratio analysis based on the desired width of its confidence interval, facilitating precision-based trial design. Our results indicate that win ratio analysis generally outperforms single-endpoint analyses when treatment effects on lower-ranked outcomes are moderate compared to those on higher-ranked outcomes. The win ratio can provide greater power than TTFE analysis, especially when the effect on the highest-ranked outcome is substantial, reaching increases in power up to 50\%. Further, even for moderate treatment effects on the highest-ranked outcome, win ratio analysis achieved higher power. Future work should expand our simulations to additional data-generating mechanisms and outcome types, particularly ordinal outcomes, where the win ratio provides an alternative to existing non-parametric and parametric methods. Our findings highlight the potential of the win ratio to improve statistical efficiency in pharmaceutical and other clinical trial designs using composite endpoints, particularly when no single component dominates the treatment effect. However, when continuous outcomes occupy the top of the hierarchy, these tend to drive overall analysis, sidelining contributions of lower-ranked outcomes and limiting benefits of hierarchical win ratio analysis.