Hernán M A, Brumback B, Robins J M
Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA.
Epidemiology. 2000 Sep;11(5):561-70. doi: 10.1097/00001648-200009000-00012.
Standard methods for survival analysis, such as the time-dependent Cox model, may produce biased effect estimates when there exist time-dependent confounders that are themselves affected by previous treatment or exposure. Marginal structural models are a new class of causal models the parameters of which are estimated through inverse-probability-of-treatment weighting; these models allow for appropriate adjustment for confounding. We describe the marginal structural Cox proportional hazards model and use it to estimate the causal effect of zidovudine on the survival of human immunodeficiency virus-positive men participating in the Multicenter AIDS Cohort Study. In this study, CD4 lymphocyte count is both a time-dependent confounder of the causal effect of zidovudine on survival and is affected by past zidovudine treatment. The crude mortality rate ratio (95% confidence interval) for zidovudine was 3.6 (3.0-4.3), which reflects the presence of confounding. After controlling for baseline CD4 count and other baseline covariates using standard methods, the mortality rate ratio decreased to 2.3 (1.9-2.8). Using a marginal structural Cox model to control further for time-dependent confounding due to CD4 count and other time-dependent covariates, the mortality rate ratio was 0.7 (95% conservative confidence interval = 0.6-1.0). We compare marginal structural models with previously proposed causal methods.
生存分析的标准方法，如时间相依Cox模型，当存在受既往治疗或暴露影响的时间相依混杂因素时，可能会产生有偏倚的效应估计值。边际结构模型是一类新的因果模型，其参数通过治疗逆概率加权来估计；这些模型允许对混杂因素进行适当调整。我们描述了边际结构Cox比例风险模型，并使用它来估计齐多夫定对参与多中心艾滋病队列研究的人类免疫缺陷病毒阳性男性生存的因果效应。在这项研究中，CD4淋巴细胞计数既是齐多夫定对生存因果效应的时间相依混杂因素，又受到过去齐多夫定治疗的影响。齐多夫定的粗死亡率比（95%置信区间）为3.6（3.0 - 4.3），这反映了混杂因素的存在。使用标准方法控制基线CD4计数和其他基线协变量后，死亡率比降至2.3（1.9 - 2.8）。使用边际结构Cox模型进一步控制因CD4计数和其他时间相依协变量导致的时间相依混杂因素后，死亡率比为0.7（95%保守置信区间 = 0.6 - 1.0）。我们将边际结构模型与先前提出的因果方法进行了比较。
