Elizabeth Williamson, Christen Gray, Kirsty Hicks.
Elizabeth’s talk will explore different approaches to trial emulation using RWD using two examples both using data from the UK Clinical Practice Research Datalink (CPRD), a large database of UK primary care records. In the first example, data from the CPRD was used to emulate a trial of macrolide antibiotics on all-cause mortality prior to the relevant trial being conducted. In the second example, data from CPRD was used to generalise the results of the TORCH COPD trial to a patient group less represented among the original trial participants – those with mild COPD.
Christen will speak about augmentation of the control arm of a randomized controlled trial (RCT) with external data, which has been proposed in recent years where standard RCTs face enrolment restrictions. Using real-world data (RWD) for external controls is a natural next step. However, in order to do so, there need to exist accessible methods for researchers which can minimize the risk from unmeasured confounding in this setting. Bayesian borrowing methods, which discount the external data dependent upon the similarity of the outcomes to the internal controls, have been applied when the external data is prior control arms of clinical trials. The simplest of these approaches is the power prior. In using RWD, greater variation in the underlying population and measured variables is expected.
Finally Kirsty speaks on digital data and how it can be used to collect information on sleep patterns, respiration rate, step count and continuous monitoring of heart rate and energy expenditure. Collecting data through digital devices also increases patient engagement and can provide real time compliance monitoring. The regulations for use of digital technologies in clinical trials are still evolving, and current recommendations for the analysis of such data are limited. As a statistician initial questions that spring to mind include ‘How can this volume of data be analysed or represented visually?’ Statistical methods that can be applied to this data are under investigation and this presentation will introduce some of these. This session of the 2020 PSI Conference Webinar Series was kindly sponsored by Amgen.