Melbourne Medical School, University of Melbourne, Melbourne, Australia.
Department of Medicine and Neurology, Melbourne Brain Centre and Royal Melbourne Hospital, University of Melbourne, Melbourne, Australia.
Stat Methods Med Res. 2023 Mar;32(3):609-625. doi: 10.1177/09622802221146306. Epub 2022 Dec 26.
The win ratio is a novel approach for handling complex patient outcomes that have seen considerable interest in the medical statistics literature, and operates by considering all-to-all pairwise statements of preference on outcomes. Recent extensions to the method have focused on the two-group case, with few developments made for considering the impact of a well-ordered explanatory variable, which would allow for dose-response analysis or the analysis of links between complex patient outcomes and prognostic variables. Where such methods have been developed, they are semiparametric methods that can only be applied to survival outcomes. In this article, we introduce the generalised pairwise comparison for trend, a modified form of Agresti's generalised odds ratio. This approach is capable of considering arbitrary statements of preference, thus enabling its use across all types of outcome data. We provide a simulation study validating the approach and illustrate it with three clinical applications in stroke research.
胜率是一种处理复杂患者结局的新方法,在医学统计学文献中受到了相当大的关注,它通过考虑对结局的所有两两偏好陈述来运作。该方法的最新扩展集中在两组情况,很少有针对有序解释变量影响的开发,这将允许进行剂量反应分析或复杂患者结局与预后变量之间关系的分析。在开发此类方法的地方,它们是半参数方法,只能应用于生存结局。在本文中,我们引入了广义配对趋势比较,这是阿格雷蒂广义优势比的一种修正形式。这种方法能够考虑任意的偏好陈述,从而使其能够用于所有类型的结果数据。我们提供了一项模拟研究来验证该方法,并通过中风研究中的三个临床应用来说明它。