Tanaka Shiro
Department of Clinical Biostatistics, Graduate School of Medicine, Kyoto University.
J Epidemiol. 2024 Dec 5;34(12):595-599. doi: 10.2188/jea.JE20240063. Epub 2024 Oct 31.
Despite the fact that competing risks are inevitable in epidemiological and clinical studies, distinctions between the hazard ratio estimated by handling competing risks as censoring and the subditribution hazard ratio are often overlooked.
We derived quantitative relationships between subdistribution hazard ratio and cause-specific hazard ratio and derive an approximate calculation method to transform the two into each other. Numerical examinations of hypothetical six scenarios and published information of a randomized clinical trial of cholesterol-lowering therapy and a registry of acute myeloid leukemia were provided.
General and approximate relationships under rare event assumptions between the two types of hazard ratio were given. The approximation formula is based on a survival ratio and has two possible applications. First, one can calculate a subdistribution hazard ratio from published information. Second, this formula allows sample size estimation that takes the presence of competing risks into account.
The distinction between the two types of hazard ratio can be addressed by focusing on two quantities. One is how the event of interest and competing risk is rare, and the other is the survival ratio.
尽管在流行病学和临床研究中竞争风险不可避免，但将竞争风险作为删失处理所估计的风险比与亚分布风险比之间的差异常常被忽视。
我们推导了亚分布风险比与特定病因风险比之间的定量关系，并得出一种将两者相互转换的近似计算方法。提供了对六种假设情景的数值检验以及一项降胆固醇治疗随机临床试验的已发表信息和一个急性髓细胞白血病登记处的数据。
给出了在罕见事件假设下两种风险比之间的一般和近似关系。该近似公式基于生存比，有两种可能的应用。第一，可以根据已发表的信息计算亚分布风险比。第二，该公式允许在考虑竞争风险存在的情况下进行样本量估计。
关注两个量可以解决两种风险比之间的差异问题。一个是感兴趣事件和竞争风险的罕见程度，另一个是生存比。
