Covariate-adjusted Group Sequential Comparisons of Restricted Mean Survival Times
协变量调整的限制平均生存时间群序贯比较AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。
本页为预印本版本;arXiv 收录、作者填写的期刊信息以及作者既有发表经历,都不单独证明本篇已接收。作者发表记录按 OpenAlex 身份与完整姓名、本站覆盖期刊 ISSN 及正式卷期核对,只展示已核实例,档案仍可能误合并。
引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:摘要主要研究生存时间比较与序贯检验,未明确给出所列因果识别或其他计量细分的直接依据。
协变量调整的限制平均生存时间群序贯比较AI 解读 ↓
正在核对关联版本…
正在核对对应版本的资源…
The restricted mean survival time (RMST) is the mean survival time in the study population followed up to a specific time point, and is simply the area under the survival curve up to the specific time point. The difference between two RMSTs quantifies the group difference in a time scale by measuring the integrated difference between survival curves in the two treatment groups. This paper develops a group sequential (GS) test of comparing two RMSTs up to a restriction time point under a stratified proportional hazards model with stratum representing treatment status. This covariate-adjusted GS test does not require the assumption of a constant hazard ratio over time between the two treatment groups and is valid whether or not the proportional hazards assumption holds for the treatment effect. We establish the large-sample properties of the covariate-adjusted GS test and show that the proposed test statistics sequentially computed at different interim analysis times possess an independent increments covariance structure. Using currently available methodology, this joint independent increments structure allows us to calculate sequential stopping boundaries for preserving the desired type I error probability and maintaining the required statistical power. We evaluate the small-sample performance of the proposed GS test via a simulation study and illustrate its real-world application through analysis of a clinical trial dataset from the BMT CTN 1101 study.