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

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" (NNE). Whereas in randomized clinical trials NNT can be calculated on the basis of a simple 2 x 2 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 perform 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.