Maximising the impact of our work

Appropriate analysis of trial data is vital, but often far from straightforward. It must respect the chosen design, provide a meaningful and unbiased summary of the treatment effect, whilst having sufficient robustness to unforeseen issues. As a practical CTU we are able to maximize the impact of our work by developing, testing and applying our proposed solutions within our own trials.

 

Missing outcome data

There is a rising awareness of the need to take account of missing outcome data in trials, but the range and novelty of methods is a barrier to many trialists. We focus on practical, accessible methods for exploring the assumptions underlying missing-data methodology, and on frameworks for analysis and reporting.

 

Treatment switching

Treatment switching (which does not reflect routine clinical practice) complicates the interpretation of a trial. For example, control arm patients may receive an unlicensed and/or unfunded experimental treatment on disease progression. Again, our focus is on developing practical methods and frameworks for analysis and interpretation of trials in the presence of treatment changes.

 

Meta-analysis

The MRC CTU at UCL is leading the way in developing and implementing best practice for meta-analysis (MA). For example, we show that treatment-covariate interactions, on which stratified medicine relies, can and should be corrected for so-called “aggregation bias” whether with Individual Participant Data (IPD) or with published data. We also clarify when so-called “one-stage” and “two-stage” models are likely to give similar results and when not; and how complex novel trial designs should best be included in both standard and Network MA.