Number Needed to Treat for Recurrent Events
Richard J Cook*
Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON, Canada
- *Corresponding Author:
- Richard J Cook
Department of Statistics and Actuarial Science
University of Waterloo
200 University Avenue West
Waterloo, Ontario, Canada
E-mail: [email protected]
Received Date: April 10, 2013; Accepted Date: May 07, 2013; Published Date: May 11, 2013
Citation: Cook RJ (2013) Number Needed to Treat for Recurrent Events. J Biomet Biostat 4:167. doi:10.4172/2155-6180.1000167
Copyright: © 2013 Cook BJ. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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.