Analysis of exacerbation rates in asthma and chronic obstructive pulmonary disease: example from the TRISTAN study

Recurrent events in clinical trials have typically been analysed using either a multiple time-to-event method or a direct approach based on the distribution of the number of events. An area of application for these methods is exacerbation data from respiratory clinical trials. The different approaches to the analysis and the issues involved are illustrated for a large trial (n = 1465) in chronic obstructive pulmonary disease (COPD). For exacerbation rates, clinical interest centres on a direct comparison of rates for each treatment which favours the distribution-based analysis, rather than a time-to-event approach. Poisson regression has often been employed and has recently been recommended as the appropriate method of analysis for COPD exacerbations but the key assumptions often appear unreasonable for this analysis. By contrast use of a negative binomial model which corresponds to assuming a separate Poisson parameter for each subject offers a more appealing approach. Non-parametric methods avoid some of the assumptions required by these models, but do not provide appropriate estimates of treatment effects because of the discrete and bounded nature of the data.     

The application of bespoke spending functions in group‐sequential designs and the effect of delayed treatment switching in survival trials

For a group‐sequential trial with two pre‐planned analyses, stopping boundaries can be calculated using a simple SAS? programme on the basis of the asymptotic bivariate normality of the interim and final test statistics. Given the simplicity and transparency of this approach, it is appropriate for researchers to apply their own bespoke spending function as long as the rate of alpha spend is pre‐specified. One such application could be an oncology trial where progression free survival (PFS) is the primary endpoint and overall survival (OS) is also assessed, both at the same time as the analysis of PFS and also later following further patient follow‐up. In many circumstances it is likely, if PFS is significantly extended, that the protocol will be amended to allow patients in the control arm to start receiving the experimental regimen. Such an eventuality is likely to result in the diminution of any effect on OS. It is shown that spending a greater proportion of alpha at the first analysis of OS, using either Pocock or bespoke boundaries, will maintain and in some cases result in greater power given a fixed number of events. Copyright © 2009 John Wiley & Sons, Ltd.