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An Assessment of the Cox Proportional Hazards Regression Model for Epidemiologic Studies

机译：流行病学研究的Cox比例风险回归模型的评估

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摘要

The basic assumptions of the Cox proportional hazards regression model are rarely questioned. This study addresses whether hazard ratio, i.e., relative risk (RR), estimates using the Cox model are biased when these assumptions are violated. We investigated also the dependence of RR estimates on temporal exposure characteristics, and how inadequate control for a strong, time-dependent confounder affects RRs for a modest, correlated risk factor. In a realistic cohort of 500,000 adults constructed using the National Cancer Institute Smoking History Generator, we used the Cox model with increasing control of smoking to examine the impact on RRs for smoking and a correlated covariate X. The smoking-associated RR was strongly modified by age. Pack-years of smoking did not sufficiently control for its effects; simultaneous control for effect modification by age and time-dependent cumulative exposure, exposure duration, and time since cessation improved model fit. Even then, residual confounding was evident in RR estimates for covariate X, for which spurious RRs ranged from 0.980 to 1.017 per unit increase. Use of the Cox model to control for a time-dependent strong risk factor yields unreliable RR estimates unless detailed, time-varying information is incorporated in analyses. Notwithstanding, residual confounding may bias estimated RRs for a modest risk factor.
机译：Cox比例风险回归模型的基本假设很少受到质疑。这项研究解决了当违反这些假设时，使用Cox模型进行估计的危险比（即相对风险（RR））是否存在偏差。我们还调查了RR估计值对时间暴露特征的依赖性，以及对时间依赖性强的混杂因素的不充分控制如何影响适度相关风险因素的RRs。在使用美国国家癌症研究所吸烟史生成器构建的一个现实的队列中，有500,000名成年人，我们使用了Cox模型，通过增加吸烟控制来研究吸烟对RR的影响以及相关的协变量X。与吸烟相关的RR通过年龄。整年的吸烟不能充分控制吸烟的效果。同时根据年龄和时间而定的累积暴露量，暴露持续时间和终止后的时间进行效果修改，从而改善了模型拟合。即便如此，协变量X的RR估计中仍存在残留混淆，其虚假RR的增加幅度为0.980至1.017。除非将详细的随时间变化的信息纳入分析，否则使用Cox模型控制与时间有关的强风险因素会产生不可靠的RR估计。尽管如此，残留的混杂物可能会由于中等风险因素而使估计的RR产生偏差。

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