Competing risk of death: an important consideration in studies of older adults.
Competing risk of death: an important consideration in studies of older adults.
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DOI：
10.1111/j.1532-5415.2010.02767.x
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发表时间：
2010-04
影响因子：
6.3
通讯作者：
Kiel DP
中科院分区：
文献类型：
--
作者：
Berry SD;Ngo L;Samelson EJ;Kiel DP
临床研究经常面临的难题是如何解释那些没有经历过感兴趣的研究结果而死亡的参与者。在有相当多合并症的老年人群中，死亡的竞争风险特别高。描述疾病风险的传统方法包括Kaplan-Meier生存分析和考克斯比例风险回归;然而，这些方法可能会高估疾病风险，因为无法考虑死亡的竞争风险。在这份报告中，我们讨论了传统的生存分析和竞争风险分析，用于估计老年研究中的疾病风险。此外，我们提供了一个竞争风险的方法来估计骨折骨质疏松症研究中的第二次髋部骨折的风险的说明，我们将结果与传统的生存分析。在这个例子中，生存分析高估了第二次髋骨骨折的5年风险37%，10年风险75%。我们的结论是，在老年人的研究中，大量的参与者在长期随访期间死亡，累积发病率竞争风险（CICR）估计和竞争风险回归（CRR）应用于确定发病率和影响估计。使用竞争风险方法对于准确确定老年人的疾病风险至关重要，因此可以最好地为临床决策提供信息。
Clinical studies are often faced with the difficult problem of how to account for participants who die without experiencing the study outcome of interest. In a geriatric population with considerable co-morbidities, the competing risk of death is especially high. Traditional approaches to describe risk of disease include Kaplan-Meier survival analysis and Cox proportional hazards regression; however, these methods can overestimate risk of disease by failing to account for the competing risk of death. In this report, we discuss traditional survival analysis and competing risk analysis as used to estimate risk of disease in geriatric studies. Furthermore, we provide an illustration of a competing risk approach to estimate risk of second hip fracture in the Framingham Osteoporosis Study, and we compare the results with traditional survival analysis. In this example, survival analysis overestimated the five-year risk of second hip fracture by 37% and the ten-year risk by 75% compared with competing risk estimates. We conclude, that in studies of older individuals in which a substantial number of participants die during a long follow-up, the Cumulative Incidence Competing Risk (CICR) estimate and Competing Risk Regression (CRR) should be used to determine incidence and effect estimates. Use of a competing risk approach is critical to accurately determine disease risk for elderly individuals, and therefore best inform clinical decision-making.