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评估研究随访访谈无应答导致偏倚的可能性:来自农业健康研究的一个例子。

Assessing the Potential for Bias From Nonresponse to a Study Follow-up Interview: An Example From the Agricultural Health Study.

作者信息

Rinsky Jessica L, Richardson David B, Wing Steve, Beard John D, Alavanja Michael, Beane Freeman Laura E, Chen Honglei, Henneberger Paul K, Kamel Freya, Sandler Dale P, Hoppin Jane A

出版信息

Am J Epidemiol. 2017 Aug 15;186(4):395-404. doi: 10.1093/aje/kwx098.

Abstract

Prospective cohort studies are important tools for identifying causes of disease. However, these studies are susceptible to attrition. When information collected after enrollment is through interview or exam, attrition leads to missing information for nonrespondents. The Agricultural Health Study enrolled 52,394 farmers in 1993-1997 and collected additional information during subsequent interviews. Forty-six percent of enrolled farmers responded to the 2005-2010 interview; 7% of farmers died prior to the interview. We examined whether response was related to attributes measured at enrollment. To characterize potential bias from attrition, we evaluated differences in associations between smoking and incidence of 3 cancer types between the enrolled cohort and the subcohort of 2005-2010 respondents, using cancer registry information. In the subcohort we evaluated the ability of inverse probability weighting (IPW) to reduce bias. Response was related to age, state, race/ethnicity, education, marital status, smoking, and alcohol consumption. When exposure and outcome were associated and case response was differential by exposure, some bias was observed; IPW conditional on exposure and covariates failed to correct estimates. When response was nondifferential, subcohort and full-cohort estimates were similar, making IPW unnecessary. This example provides a demonstration of investigating the influence of attrition in cohort studies using information that has been self-reported after enrollment.

摘要

前瞻性队列研究是确定疾病病因的重要工具。然而,这些研究容易出现失访情况。当入组后收集的信息通过访谈或检查获得时,失访会导致无应答者的信息缺失。农业健康研究在1993年至1997年招募了52394名农民,并在随后的访谈中收集了更多信息。46%的入组农民对2005年至2010年的访谈做出了回应;7%的农民在访谈前死亡。我们研究了应答是否与入组时测量的特征有关。为了描述失访可能导致的偏差,我们利用癌症登记信息,评估了入组队列与2005年至2010年应答者亚队列中吸烟与三种癌症类型发病率之间关联的差异。在亚队列中,我们评估了逆概率加权(IPW)减少偏差的能力。应答与年龄、州、种族/族裔、教育程度、婚姻状况、吸烟和饮酒有关。当暴露与结局相关且病例应答因暴露而异时,观察到了一些偏差;基于暴露和协变量的IPW未能校正估计值。当应答无差异时,亚队列和全队列的估计值相似,因此无需进行IPW。这个例子展示了如何利用入组后自我报告的信息来研究队列研究中失访的影响。

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