Competing Risk Regression Models for Epidemiologic Data
Competing Risk Regression Models for Epidemiologic Data
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DOI：
10.1093/aje/kwp107
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发表时间：
2009-07-15
影响因子：
5
通讯作者：
Gange, Stephen J.
中科院分区：
文献类型：
--
作者：
Lau, Bryan;Cole, Stephen R.;Gange, Stephen J.
竞争事件可以排除流行病学数据中发生的感兴趣事件，并可以通过使用生存分析方法的扩展进行分析。在本文中，作者概述了3种回归方法，用于估计竞争风险分析中的2个关键量：特定原因相对危险度（csRH）和子分布相对危险度（sdRH）。他们比较和对比的风险集的结构和这些方法获得的参数的解释。他们还证明了这些方法的使用与1993年建立的妇女机构间艾滋病毒研究的数据，治疗时间开始高活性抗逆转录病毒治疗或临床疾病进展的竞争事件。在我们的例子中，有注射吸毒史的女性比没有注射吸毒史的女性在进展为获得性免疫缺陷综合征或死亡之前开始治疗的可能性更小（csRH = 0.67，95%置信区间：0.57，0.80和sdRH = 0.60，95%置信区间：0.50，0.71）。此外，治疗前疾病进展的相对风险升高（csRH = 1.71，95%置信区间：1.37，2.13和sdRH = 2.01，95%置信区间：1.62，2.51）。流行病学家应使用竞争风险的方法，方法的选择以科学问题为指导。
Competing events can preclude the event of interest from occurring in epidemiologic data and can be analyzed by using extensions of survival analysis methods. In this paper, the authors outline 3 regression approaches for estimating 2 key quantities in competing risks analysis: the cause-specific relative hazard (csRH) and the subdistribution relative hazard (sdRH). They compare and contrast the structure of the risk sets and the interpretation of parameters obtained with these methods. They also demonstrate the use of these methods with data from the Women's Interagency HIV Study established in 1993, treating time to initiation of highly active antiretroviral therapy or to clinical disease progression as competing events. In our example, women with an injection drug use history were less likely than those without a history of injection drug use to initiate therapy prior to progression to acquired immunodeficiency syndrome or death by both measures of association (csRH = 0.67, 95% confidence interval: 0.57, 0.80 and sdRH = 0.60, 95% confidence interval: 0.50, 0.71). Moreover, the relative hazards for disease progression prior to treatment were elevated (csRH = 1.71, 95% confidence interval: 1.37, 2.13 and sdRH = 2.01, 95% confidence interval: 1.62, 2.51). Methods for competing risks should be used by epidemiologists, with the choice of method guided by the scientific question.