{"title":"在有竞争风险的生存分析中,子分布危险比和特定原因危险比之间的罕见事件近似。","authors":"Shiro Tanaka","doi":"10.2188/jea.JE20240063","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":15799,"journal":{"name":"Journal of Epidemiology","volume":" ","pages":"595-599"},"PeriodicalIF":3.7000,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11564069/pdf/","citationCount":"0","resultStr":"{\"title\":\"Rare Event Approximation Between Subdistribution Hazard Ratio and Cause-specific Hazard Ratio in Survival Analysis With Competing Risks.\",\"authors\":\"Shiro Tanaka\",\"doi\":\"10.2188/jea.JE20240063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":15799,\"journal\":{\"name\":\"Journal of Epidemiology\",\"volume\":\" \",\"pages\":\"595-599\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11564069/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Epidemiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2188/jea.JE20240063\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2188/jea.JE20240063","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/31 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Rare Event Approximation Between Subdistribution Hazard Ratio and Cause-specific Hazard Ratio in Survival Analysis With Competing Risks.
Background: 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.
Methods: 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.
Results: 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.
Conclusion: 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.
期刊介绍:
The Journal of Epidemiology is the official open access scientific journal of the Japan Epidemiological Association. The Journal publishes a broad range of original research on epidemiology as it relates to human health, and aims to promote communication among those engaged in the field of epidemiological research and those who use epidemiological findings.