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存在因果效应异质性时相加风险模型的偏差。

Bias of the additive hazard model in the presence of causal effect heterogeneity.

机构信息

Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands.

Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.

出版信息

Lifetime Data Anal. 2024 Apr;30(2):383-403. doi: 10.1007/s10985-024-09616-z. Epub 2024 Mar 11.

DOI:10.1007/s10985-024-09616-z
PMID:38466520
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10957647/
Abstract

Hazard ratios are prone to selection bias, compromising their use as causal estimands. On the other hand, if Aalen's additive hazard model applies, the hazard difference has been shown to remain unaffected by the selection of frailty factors over time. Then, in the absence of confounding, observed hazard differences are equal in expectation to the causal hazard differences. However, in the presence of effect (on the hazard) heterogeneity, the observed hazard difference is also affected by selection of survivors. In this work, we formalize how the observed hazard difference (from a randomized controlled trial) evolves by selecting favourable levels of effect modifiers in the exposed group and thus deviates from the causal effect of interest. Such selection may result in a non-linear integrated hazard difference curve even when the individual causal effects are time-invariant. Therefore, a homogeneous time-varying causal additive effect on the hazard cannot be distinguished from a time-invariant but heterogeneous causal effect. We illustrate this causal issue by studying the effect of chemotherapy on the survival time of patients suffering from carcinoma of the oropharynx using data from a clinical trial. The hazard difference can thus not be used as an appropriate measure of the causal effect without making untestable assumptions.

摘要

风险比容易受到选择偏倚的影响,从而影响其作为因果估计量的使用。另一方面,如果 Aalen 的加性风险模型适用,那么已经证明,随着时间的推移,风险差异不受脆弱性因素选择的影响。然后,在没有混杂的情况下,观察到的风险差异在预期上等于因果风险差异。然而,在存在效应(对风险的影响)异质性的情况下,观察到的风险差异也受到幸存者选择的影响。在这项工作中,我们形式化了观察到的风险差异(来自随机对照试验)如何通过在暴露组中选择有利的效应修饰因子来演变,从而偏离了感兴趣的因果效应。即使个体因果效应是时不变的,这种选择也可能导致非线性积分风险差异曲线。因此,不能将对风险的同质时变因果加性效应与时不变但异质的因果效应区分开来。我们通过使用临床试验中的数据来研究化疗对口咽癌患者生存时间的影响来说明这个因果问题。因此,如果不做出未经检验的假设,风险差异就不能作为因果效应的适当衡量标准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/7763edc398f8/10985_2024_9616_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/dafb7a182121/10985_2024_9616_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/2280005d6cb5/10985_2024_9616_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/1eb117d2e2c6/10985_2024_9616_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/2acd8e30567f/10985_2024_9616_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/95b5a67b618d/10985_2024_9616_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/59959c04ed64/10985_2024_9616_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/459e21ef2fa6/10985_2024_9616_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/7763edc398f8/10985_2024_9616_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/dafb7a182121/10985_2024_9616_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/2280005d6cb5/10985_2024_9616_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/1eb117d2e2c6/10985_2024_9616_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/2acd8e30567f/10985_2024_9616_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/95b5a67b618d/10985_2024_9616_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/59959c04ed64/10985_2024_9616_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/459e21ef2fa6/10985_2024_9616_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d120/10957647/7763edc398f8/10985_2024_9616_Fig8_HTML.jpg

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Stat Med. 2020 Apr 15;39(8):1199-1236. doi: 10.1002/sim.8471. Epub 2020 Jan 27.
4
Exploring Selection Bias by Causal Frailty Models: The Magnitude Matters.通过因果脆弱性模型探索选择偏倚:量级很重要。
Epidemiology. 2017 May;28(3):379-386. doi: 10.1097/EDE.0000000000000621.
5
Does Cox analysis of a randomized survival study yield a causal treatment effect?随机生存研究的Cox分析能否得出因果治疗效果?
Lifetime Data Anal. 2015 Oct;21(4):579-93. doi: 10.1007/s10985-015-9335-y. Epub 2015 Jun 24.
6
On collapsibility and confounding bias in Cox and Aalen regression models.关于Cox模型和Aalen回归模型中的可折叠性与混杂偏倚
Lifetime Data Anal. 2013 Jul;19(3):279-96. doi: 10.1007/s10985-013-9242-z. Epub 2013 Jan 18.
7
The hazards of hazard ratios.风险比的危害
Epidemiology. 2010 Jan;21(1):13-5. doi: 10.1097/EDE.0b013e3181c1ea43.
8
A linear regression model for the analysis of life times.用于分析寿命的线性回归模型。
Stat Med. 1989 Aug;8(8):907-25. doi: 10.1002/sim.4780080803.