Department of Epidemiology and Biostatistics (G.Z., Y.-H.C.), Western University, London, Canada.
Robarts Research Institute (G.Z.), Western University, London, Canada.
Stroke. 2022 Oct;53(10):3025-3031. doi: 10.1161/STROKEAHA.121.037744. Epub 2022 Aug 17.
Many methods have been suggested for analyzing the modified Rankin Scale (mRS). However, there lacks a unified approach to analysis and sample size determination that properly uses the ordinal nature of the data. We propose a simple method for CI estimation and corresponding sample size determination.
We quantify treatment effect by the win probability (WinP) that a randomly selected patient in the treatment group has an equal or a better mRS score than a patient in the control group. Thus, a win probability of 0.5 means no effect, likened to a draw in competitive sports. We estimate the win probability and its SE based on the ranks of mRS scores, where tied scores are handled by average ranks. Corresponding methods for hypothesis testing, CI estimation, and sample size determination are derived. The methods are evaluated with a simulation study based on real data from 10 randomized stroke trials that used mRS as the outcome measure.
Simulation results demonstrated that the methods performed very well in terms of CI coverage, tail errors, and assurance to achieving the prespecified precision. Because the methods are very simple, we implemented them in an Excel spreadsheet, requiring only user inputs on frequencies of mRS scores in 2 comparison groups.
Sound statistical methods are important for the success of randomized stroke trials. The proposed methods and associated spreadsheet should prove useful for stroke researchers in the planning and analysis of randomized trials. Meta-analysis has also been made easy for trials with ordinal scores.
已有多种方法被提出用于分析改良 Rankin 量表（mRS）。然而，目前缺乏一种统一的分析和样本量确定方法，这种方法恰当地利用了数据的有序性质。我们提出了一种简单的置信区间（CI）估计和相应的样本量确定方法。
我们通过治疗组中随机选择的患者的 mRS 评分与对照组患者相等或更好的赢概率（WinP）来量化治疗效果。因此，赢概率为 0.5 意味着没有效果，类似于竞技体育中的平局。我们根据 mRS 评分的秩来估计赢概率及其 SE，其中平局分数通过平均秩处理。导出了用于假设检验、CI 估计和样本量确定的相应方法。该方法通过基于 10 项随机脑卒中试验的真实数据的模拟研究进行了评估，这些试验均使用 mRS 作为结局测量。
模拟结果表明，该方法在 CI 覆盖范围、尾部误差和保证达到预定精度方面表现非常出色。由于方法非常简单，我们将其在 Excel 电子表格中实现，用户只需在 2 个比较组的 mRS 评分频率上输入。
合理的统计方法对于随机脑卒中试验的成功至关重要。所提出的方法和相关电子表格应该对脑卒中研究人员在随机试验的规划和分析中非常有用。对于使用等级评分的试验，也可以轻松进行荟萃分析。
