In this episode, hear from Dr Kate Scrivener, Dr Aidan Cashin and Clinical Associate Professor Mark Elkins about interpreting comparative effects in trials.

High-quality randomised controlled trials are a great source of evidence to support clinical decisions about which treatment may be best for the patients you work with. When interpreting the findings from trials, it is important to consider both how the outcomes are reported and what the treatment is being compared to.

Trial outcomes are often measured and reported as the ‘within-group’ change in outcomes or as the ‘between-group’ difference in outcomes. The distinction between within-group comparison and between-group comparison is critical when interpreting the results of trials. The between-group difference represents the treatment effect because it does not include natural history, regression to the mean, and nonspecific effects of receiving care which are included in the within-group change.

The treatment effect in trials is always comparative, meaning that the treatment benefit (or harm) is interpreted relative to the other treatment(s) in the trial. This is an important issue because the choice of comparison group will have a big influence on the interpretation of the size of the effect and whether the comparison was a fair test of the treatment.

Choosing the ideal comparison group is not straightforward and is heavily influenced by the research question (spanning the spectrum of efficacy to effectiveness research). For example, guideline-based care may be a suitable comparator if researchers were interested in investigating if the treatment was better than current practice.

The choice of comparison group is also important when trials are synthesised in systematic reviews. It is important that meta-analyses of systematic reviews combine trials with similar treatments, and trials that have similar comparison groups.