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基于限制平均生存时间的多组疗效比较

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目的 在临床随访研究中,基于时间尺度指标的限制平均生存时间(restricted mean survival time,RMST)越来越受到关注,然而目前基于RMST的统计推断主要用于两组比较,缺少进行两组以上比较的方法.方法 本文提出RMST多组间的假设检验法,包括经典法(naive)、对数转换法(log)、双对数转换法(cloglog)三种检验法,并通过Monte Carlo模拟评价其Ⅰ类错误和检验效能,最后进行实例分析.结果 综合Monte Carlo模拟的Ⅰ类错误及检验效能结果,显示所提出的RMST检验可以处理多组比较的问题,特别是cloglog转换法最为稳健.结论 针对生存数据的多组比较问题,若考虑从时间尺度指标分析,推荐使用cloglog转换法的RMST多组检验.
Multiple Groups Comparison Test based on Restricted Mean Survival Time
Objective In clinical follow-up studies,it is the most common method to quantify treatment differences between groups using a hazard ratio(HR).Moreover,restricted mean survival time(RMST)has attracted more and more attention.However,the current statistical inference method based on RMST is mainly used for the comparison between two groups.Methods In this paper,three RMST tests between multiple groups are proposed,including naive,logarithmic transformation and complementary logarithmic transformation.Monte Carlo simulations were performed to evaluate the type I error and power,and a case study was performed.Results Based on the type I errors obtained by Monte Carlo simulation and the test performance results,it is shown that the proposed RMST test can deal with the problem of multiple sets of comparisons,especially the complementary logarithmic transformation method is the most robust.Conclusions For the multi-group comparison of survival data,if the time scale index is considered,the RMST multi-group test by the complementary logarithmic transformation method is recommended.

Restricted mean survival timeProportional hazard assumptionComparison of multiple groupsComplementary logarithmic transformation

江珮瑜、周佳仪、徐筠天、张成凤、巫宏基、任嘉翘、黑子健、余磊、侯雅文、陈征

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南方医科大学公共卫生学院(广东省热带病研究重点实验室)生物统计学系(510515)

暨南大学经济学院统计与数学科学系

限制平均生存时间 比例风险假定 多组比较 双对数转换

广东省基础与应用基础研究基金广东省基础与应用基础研究基金国家自然科学基金广东省大学生创新创业训练计划项目广东省大学生创新创业训练计划项目

2022A15150115252024A151501140282173622S202212121142S202212121140

2024

10.11783/j.issn.1002-3674.2024.03.016

中国卫生统计
中国卫生信息学会 中国医科大学

中国卫生统计

CSTPCD北大核心
影响因子：1.172
ISSN：1002-3674
年,卷(期)：2024.41(3)
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