The "Lost NNT" can be used to represent uncertainty surrounding number needed to treat.
OBJECTIVE
The uncertainty around number needed to treat (NNT) is often represented through a confidence interval (CI). However, it is not clear how the CI can help inform treatment decisions. We developed decision-theoretic measures of uncertainty for the NNT.


METHODS
We build our argument on the basis that a risk-neutral decision maker should always choose the treatment with the highest expected benefit, regardless of uncertainty. From this perspective, uncertainty can be seen as a source of "opportunity loss" owing to its associated chance of choosing the suboptimal treatment. Motivated from the concept of the expected value of perfect information (EVPI) in decision analysis, we quantify such opportunity loss and propose novel measures of uncertainty around the NNT: the Lost NNT and the Lost Opportunity Index (LOI).


RESULTS
The Lost NNT is the quantification of the lost opportunity expressed on the same scale as the NNT. The LOI is a scale-free measure quantifying the loss in terms of the relative efficacy of treatment. We illustrate the method using a sample of published NNT values.


CONCLUSIONS
Decision-theoretic concepts have the potential to be applied in this context to provide measures of uncertainty that can have relevant implications.
Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, 2146 East Mall, Vancouver, BC, Canada. msafavi@mail.ubc.ca
Mohsen
M
Sadatsafavi
Saeedreza
S
Ganjizadeh
Rose
R
Hatala
Carlo
C
Marra
Mark
M
FitzGerald
D001499:Bayes Theorem; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D006801:Humans; D018401:Sample Size; D035501:Uncertainty