NIRG: Evaluation of interventions with rare events: methods for parallel cluster randomised trials and stepped-wedge cluster randomised trials

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This project will improve the statistical methods of trials when the outcome of the trial is rare. It will focus on trials that randomise groups of people rather than individual people. Trials are the gold standard for assessing whether an intervention has a positive impact across all areas of health research and beyond. However, it is sometimes difficult to randomise individual people. This could be because the intervention being tested affects a whole village or hospital ward, or the trial is testing the impact of large-scale rollout of an individual intervention. When this is the case, we can randomise groups of individuals such as whole villages or hospital wards that we call clusters. This randomisation of groups has implications for how we analyse data from the trial because individuals in the same cluster are likely to be more like one another than individuals from different clusters. This analysis is further complicated if the outcome we are trying to affect in the trial is a rare event, such as reducing levels of a disease from an already low starting point. For example, in infectious diseases, even a small increase in the number of disease cases can have a large impact on the disease trajectory. When we are interested in a rare event, there might be some clusters (the groups of people) where no one experience the event of interest (e.g. contracted the disease). In this project, I will explore how we deal with these rare events in the analysis of these trials, so that even when we have a rare outcome, we can trust the results. The project will focus on two types of trials. In the first type, the clusters are randomised to receive either the new intervention or a control condition for the duration of the trial. Current methods of analysing these trials are known to inaccurately estimate the effect of the intervention or underestimate our confidence in that estimate. I will develop a new method of analysis to over come this issue. New software will be created to help researchers implement our new analysis method.The second type of trial is called a stepped-wedge cluster randomised trial. Here, we randomise clusters to switch to the intervention at different times during the trial so that by the end of the trial all or most clusters have received the intervention. When events are rare, it is expected that standard methods of analysis will struggle to provide results or will give inaccurate estimates of our uncertainty in results. This project will determine how to conduct an existing analysis method for stepped-wedge cluster randomised trials; the method has not been used for these trials before. Like the first type of trial, I will also create software to help researchers implement the analysis methods I find work well.It is vital that we have validated and trustworthy analysis methods to use with these trials to be able to improve human health. By the end of this project, both types of trials will have improved, validated methods of analysis that can be used when the outcome of the trial is a rare event.