{"title":"测试事件时间数据的统计方法综述","authors":"Tu Xu, Danting Zhu","doi":"10.15406/bbij.2018.07.00260","DOIUrl":null,"url":null,"abstract":"In oncology randomized clinical trials, the time-to-event(TTE) type of endpoints such as progression-free survival (PFS) and overall survival(OS), are commonly used as the primary or key secondary endpoints for comparing the experimental treatment and active control/ placebo. In practice, the proportional hazard (PH) is usually assumed to characterize the treatment benefit over time of TTE endpoints and calculate the required sample size. With the PH assumption, the hazard ratio (HR) between treatment arms is a constant over time, and the corresponding testing hypothesis is expressed as","PeriodicalId":90455,"journal":{"name":"Biometrics & biostatistics international journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A review of statistical methods on testing time-to-event data\",\"authors\":\"Tu Xu, Danting Zhu\",\"doi\":\"10.15406/bbij.2018.07.00260\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In oncology randomized clinical trials, the time-to-event(TTE) type of endpoints such as progression-free survival (PFS) and overall survival(OS), are commonly used as the primary or key secondary endpoints for comparing the experimental treatment and active control/ placebo. In practice, the proportional hazard (PH) is usually assumed to characterize the treatment benefit over time of TTE endpoints and calculate the required sample size. With the PH assumption, the hazard ratio (HR) between treatment arms is a constant over time, and the corresponding testing hypothesis is expressed as\",\"PeriodicalId\":90455,\"journal\":{\"name\":\"Biometrics & biostatistics international journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biometrics & biostatistics international journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15406/bbij.2018.07.00260\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biometrics & biostatistics international journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15406/bbij.2018.07.00260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A review of statistical methods on testing time-to-event data
In oncology randomized clinical trials, the time-to-event(TTE) type of endpoints such as progression-free survival (PFS) and overall survival(OS), are commonly used as the primary or key secondary endpoints for comparing the experimental treatment and active control/ placebo. In practice, the proportional hazard (PH) is usually assumed to characterize the treatment benefit over time of TTE endpoints and calculate the required sample size. With the PH assumption, the hazard ratio (HR) between treatment arms is a constant over time, and the corresponding testing hypothesis is expressed as