Calculating the "number needed to be exposed" with adjustment for confounding variables in epidemiological studies

被引:109
作者
Bender, R [1 ]
Blettner, M [1 ]
机构
[1] Univ Bielefeld, Sch Publ Hlth, Dept Epidemiol & Med Stat, D-33501 Bielefeld, Germany
关键词
confounding; confidence intervals; epidemiology; logistic regression; number needed to treat; odds ratio; statistics;
D O I
10.1016/S0895-4356(01)00510-8
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The number needed to treat (NNT) is a popular summary statistic to describe the absolute effect of a new treatment compared with a standard treatment or control concerning the risk of an adverse event. The NNT concept can be applied whenever the risk of an adverse event is compared between two groups; for the comparison of exposed with unexposed subjects in epidemiological studies, we propose the term "number needed to be exposed" (NINE). Whereas in randomized clinical trials NNT can be calculated on the basis of a simple 2x2 table, in epidemiological studies methods to adjust for confounders are required in most applications. We derive a method based upon multiple logistic regression analysis to pet-form point and interval estimation of NNE with adjustment for confounding variables. The adjusted NNE can be calculated from the adjusted odds ratio (OR) and the unexposed event rate (UER) estimated by means of an appropriate multiple logistic regression model. As UER is dependent on the confounders, the adjusted NNEs also vary with the values of the confounding variables. Two methods are proposed to take the dependence of NNE on the values of the confounders into account. The adjusted number needed to be exposed can be a useful complement to the commonly presented results in epidemiological studies, such as ORs and attributable risks. (C) 2002 Elsevier Science Inc. All rights reserved.
引用
收藏
页码:525 / 530
页数:6
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