Journal of Biometrics & Biostatistics

Number Needed to Treat for Recurrent Events

Abstract

Richard J Cook

Many clinical investigators find the Number Needed to Treat (NNT) an appealing measure of treatment effect and use it routinely in reporting the results of randomized trials. It is most easily computed and interpreted for trials with binary responses, but attempts have been made to compute NNT-like measures for recurrent event outcomes. We discuss methodological issues concerning the construction of NNT-like measures of treatment effect based on recurrent event outcomes. Rate and mean functions are used to develop nonparametric estimates of NNT-like measures of treatment effect for recurrent events in terms of the number of individuals to be treated to expect to prevent a k and simply to prevent any event. Parametric analyses facilitate the derivation of alternative measures and associated estimates. Applications to a trial of patients with cystic fibrosis are given for illustration. In settings where mortality rates are non-negligible, joint NNT-like measures for the recurrent event and survival processes are required and these are discussed.