It is by no means straightforward to analyse the change in the rate of chronic obstructive pulmonary disease (COPD) exacerbations in clinical trials. Exacerbation rates do not follow a normal distribution, nor do they occur at random. High exacerbation rates in a few patients can make average rates difficult to calculate and interpret. So, surely, transforming exacerbation rates into numbers needed to treat (NNT) should help. Not necessarily so—this is the message from Professor Suissa's paper.1 He points out that the simplistic transformation from annual exacerbation rates to NNT in some published papers is misleading. He then goes on to present an alternative way of calculating NNT from survival curves showing time to first exacerbation, and a model to estimate such curves even if they are not presented.

I have used the exponential model suggested by Suissa, with the data from two of the arms of the Towards a Revolution in Chronic obstructive pulmonary disease Health (TORCH) trial2 to show how this works in practice. I chose the arms in TORCH, that compared combination fluticasone/salmeterol therapy with salmeterol alone, as this seems to me to be a fair way to estimate the impact of additional inhaled corticosteroids. Figure 1 shows pairs of modelled survival curves for pneumonia (in the upper part), and for COPD exacerbation (in the lower part). …