A cautionary note on the use of attributable fractions in cohort studies

The attributable fraction is a widely used measure to quantify the public health impact of an exposure on an outcome. It was originally proposed for binary outcomes, but attributable fraction estimators have also been proposed for time-to-event outcomes. In this note, we consider an estimator which was proposed by Benichou (Stats Methods Med Res, 2001) and is supposed to estimate the cohort attributable fraction, i.e. the number of events that would have been prevented in the cohort during follow-up, if the exposure would hypothetically have been eliminated. We show that this estimator is only valid under certain assumptions, which are often likely to be violated in practice. We further argue that the cohort attributable fraction may not be of substantial scientific interest in the first place. We propose a potentially more relevant measure of attributable fraction in cohort studies; the baseline attributable fraction. We show how the baseline attributable fraction can be conveniently estimated in Cox proportional hazards models.