Sensitivity analysis for unmeasured confounding in estimating the difference in restricted mean survival time.

IF 1.6 3区 医学 Q3 HEALTH CARE SCIENCES & SERVICES
Statistical Methods in Medical Research Pub Date : 2024-11-01 Epub Date: 2024-10-07 DOI:10.1177/09622802241280782
Seungjae Lee, Ji Hoon Park, Woojoo Lee
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引用次数: 0

Abstract

The difference in restricted mean survival time has been increasingly used as an alternative measure to the hazard ratio in survival analysis. Although some statistical methods have been developed for estimating the difference in restricted mean survival time adjusted for measured confounders in observational studies, the impact of unmeasured confounding on the estimate has rarely been assessed. We develop a novel sensitivity analysis for the estimate of the difference in restricted mean survival time with respect to unmeasured confounding. After formulating the sensitivity analysis problem as an optimization problem, we explain how to obtain the sensitivity range of the difference in restricted mean survival time efficiently and assess its uncertainty using the percentile bootstrap confidence interval. Analytic results are provided for some important survival settings. Simulation studies show that the proposed methods perform well in various settings. We illustrate the proposed sensitivity analysis method by analyzing data from the German Breast Cancer Study Group study.

在估算受限平均存活时间差异时对未测量混杂因素的敏感性分析。
在生存分析中,限制性平均生存时间差已越来越多地被用作危险比的替代指标。虽然已经开发了一些统计方法来估算观察性研究中经测量混杂因素调整后的受限平均生存时间差,但很少有人评估未测量混杂因素对估算结果的影响。我们开发了一种新的敏感性分析方法,用于估算未测量混杂因素对受限平均生存时间的影响。在将敏感性分析问题表述为一个优化问题后,我们解释了如何有效地获得受限平均生存时间差的敏感性范围,并使用百分位数引导置信区间评估其不确定性。我们提供了一些重要生存设置的分析结果。模拟研究表明,所提出的方法在各种情况下都表现良好。我们通过分析德国乳腺癌研究小组的研究数据来说明所提出的敏感性分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Statistical Methods in Medical Research
Statistical Methods in Medical Research 医学-数学与计算生物学
CiteScore
4.10
自引率
4.30%
发文量
127
审稿时长
>12 weeks
期刊介绍: Statistical Methods in Medical Research is a peer reviewed scholarly journal and is the leading vehicle for articles in all the main areas of medical statistics and an essential reference for all medical statisticians. This unique journal is devoted solely to statistics and medicine and aims to keep professionals abreast of the many powerful statistical techniques now available to the medical profession. This journal is a member of the Committee on Publication Ethics (COPE)
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