Use of the landmark method to address immortal person-time bias in comparative effectiveness research: a simulation study

地标 计算机科学 观察研究 协变量 统计 危险系数 计量经济学 人工智能 数学 机器学习 置信区间
作者
Xiaojuan Mi,Bradley G. Hammill,Lesley H. Curtis,Edward Chia‐Cheng Lai,Soko Setoguchi
出处
期刊:Statistics in Medicine [Wiley]
卷期号:35 (26): 4824-4836 被引量:92
标识
DOI:10.1002/sim.7019
摘要

Observational comparative effectiveness and safety studies are often subject to immortal person-time, a period of follow-up during which outcomes cannot occur because of the treatment definition. Common approaches, like excluding immortal time from the analysis or naïvely including immortal time in the analysis, are known to result in biased estimates of treatment effect. Other approaches, such as the Mantel-Byar and landmark methods, have been proposed to handle immortal time. Little is known about the performance of the landmark method in different scenarios. We conducted extensive Monte Carlo simulations to assess the performance of the landmark method compared with other methods in settings that reflect realistic scenarios. We considered four landmark times for the landmark method. We found that the Mantel-Byar method provided unbiased estimates in all scenarios, whereas the exclusion and naïve methods resulted in substantial bias when the hazard of the event was constant or decreased over time. The landmark method performed well in correcting immortal person-time bias in all scenarios when the treatment effect was small, and provided unbiased estimates when there was no treatment effect. The bias associated with the landmark method tended to be small when the treatment rate was higher in the early follow-up period than it was later. These findings were confirmed in a case study of chronic obstructive pulmonary disease. Copyright © 2016 John Wiley & Sons, Ltd.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
自由夏旋应助是小孙啊采纳,获得10
刚刚
在水一方应助小王子采纳,获得10
1秒前
1秒前
1秒前
研友_VZG7GZ应助ydxhh采纳,获得10
2秒前
2秒前
柳香芦发布了新的文献求助10
2秒前
今天进步了吗完成签到,获得积分10
3秒前
nn完成签到 ,获得积分10
3秒前
思源应助chen采纳,获得10
3秒前
戳戳鱿鱼完成签到,获得积分10
4秒前
yaomuyang完成签到,获得积分10
4秒前
5秒前
5秒前
123完成签到,获得积分10
5秒前
科研通AI2S应助一颗栗子采纳,获得30
5秒前
mxd1991完成签到,获得积分10
5秒前
6秒前
ding应助木木木采纳,获得10
6秒前
我憋不住了完成签到,获得积分10
6秒前
科研通AI6.4应助YUKI采纳,获得10
6秒前
6秒前
个性的背包完成签到 ,获得积分10
7秒前
所所应助tian采纳,获得10
7秒前
7秒前
7秒前
阳光鹤轩完成签到 ,获得积分10
8秒前
8秒前
8秒前
szx发布了新的文献求助10
9秒前
9秒前
ydxhh完成签到,获得积分10
9秒前
刘嘉欣发布了新的文献求助10
9秒前
三水发布了新的文献求助10
9秒前
10秒前
无花果应助徐X采纳,获得30
10秒前
elgar612完成签到,获得积分10
10秒前
zhangjing发布了新的文献求助10
10秒前
英吉利25发布了新的文献求助10
11秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Direct and Iterative Linear System Solvers 500
Plato's Parmenides. A Constructive Reading 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7301003
求助须知:如何正确求助?哪些是违规求助? 8919355
关于积分的说明 18890898
捐赠科研通 6965728
什么是DOI,文献DOI怎么找? 3211290
关于科研通互助平台的介绍 2380363
邀请新用户注册赠送积分活动 2188075