Meet Professor Richard Hooper, Professor of Medical Statistics and Deputy Centre Lead at the Wolfson Institute of Population Health, who talks about his fascinating research into clinical trials.
1. Could you tell us about your work as Professor of Medical Statistics?
I’m based at the Wolfson Institute of Population Health, in the Centre for Evaluation and Methods, where I’m the Deputy Centre Lead. A lot of my work revolves around clinical trials. A clinical trial is any study that evaluates the effects of treatments on human health outcomes. A lot of people assume that a clinical trial must involve a pharmaceutical treatment, but actually you can have a trial of just about anything: an educational programme, a change to the way your GP’s computer system works, or even an activity like gardening or playing football. The trials that particularly interest me are randomised controlled trials, meaning that different people are allocated to different treatments at random, and their health outcomes compared.
One of my roles is to lead the statistics team at the Pragmatic Clinical Trials Unit. Clinical Trials Units are centres of expertise in designing, conducting, analysing and publishing clinical trials, and “Pragmatic” means that ours is focused particularly on trials of treatments as they might be rolled out in practice by health services. I help Chief Investigators to develop new ideas for trials, and if we can successfully find funding then I help them with the statistical aspects of running those trials. I also help and support other statisticians in the Unit who are performing similar roles.
Helping people find funding is another important part of my work. I belong to an initiative called Research Design Service London, which is funded by the UK National Institute for Health Research (the research arm of the NHS) to provide free advice to researchers looking for public funding for their research in health and social care. I co-lead the team of RDS London advisors at QMUL. It’s a good feeling to be able to help people in this way, particularly when they can obtain personal awards like Fellowships, which fund their own training and development as well as research.
As well as all this I have my own programme of research on the design of randomised trials. One topic I’ve written a lot about is a variety of trial called a “stepped wedge” trial: these are increasingly popular with health researchers and are not always done well or in an appropriate way, though this just makes me want to understand them better. In 2020 I set up a website called www.steppedwedgehog.org to give researchers access to more information about this design.
Finally, being a comparative expert on trials means I am also regularly invited to take on roles on funding panels, journal editorial boards, and Trial Steering Committees.
2. Tell us more about your own research: what fascinates you so much about randomised controlled trials?
The randomised controlled trial has been with us in its modern form for over 70 years, and as a technology (in this case one that helps health services to understand which treatments work) has proved as revolutionary as the jet engine. Though many people are highly critical of trials they continue to deliver: the first persuasive evidence for a treatment against COVID-19 (dexamethasone) came from a large-scale randomised trial called RECOVERY. Still, it might be argued that a technology as old as the randomised trial needs to evolve in order to survive.
One way in which the design and conduct of randomised trials evolves is through a philosophy of “marginal gains”, a term popularised by the controversial Team GB and Team Sky cycling coach, Dave Brailsford, and applied more recently to trials by the Trial Forge initiative led from the University of Aberdeen. It refers to breaking down an objective (such as winning a cycle race, or doing a trial) into many parts, making a small change to each, and thus achieving a significant overall improvement.
Marginal gains are all very well – you might improve 50 different aspects of your cycle ride by 1% – but what if I could just design you a bicycle that went 50% faster? (Incidentally, in 2016 I discovered a fascinating article in the science journal, Nature, describing how the received wisdom on the physics of bicycle design was being rewritten, leading to fundamentally new bicycle forms.) The history of trial design is one of constant innovation and discovery, and my own research attempts in its own small way to turn received wisdom on its head. I find it tremendously exciting that there are still new things to be discovered about the design of randomised trials, however simple they might appear at first sight.
3. Tell us a bit about your educational and training background and what advice you would give to a student wanting to follow in similar footsteps
One of the wonderful things about medical statistics as a career is that there’s no single pathway. I studied maths at university, and one area that particularly fascinated me was statistics, so after my undergraduate degree I did a Postgraduate Diploma in Mathematical Statistics. My first job on graduating from the Diploma was with a small group of researchers who were studying postnatal depression and the way this affected mothers’ interactions with their babies. This was the start of a new learning chapter for me: my background was mathematical and theoretical, but now I was learning how to use statistics to tackle real problems with real data. Most medical statisticians, whatever training route they follow, find there is no substitute for working at the applied research coalface in order to truly understand their discipline. To be honest, I’m still learning.
Having a less well-defined career structure can sometimes make it harder to see how to progress further. My own path was decidedly rambling, and at one point I was seriously toying with the idea of an alternative occupation as a jewellery designer. But I was lucky enough ten years ago to find a role at QMUL that introduced me to the world of clinical trials, kick-started my professional development and progression as a statistician, and allowed me to develop my own research programme for the first time. These moments are transformative. Part of my role now is to help statisticians to identify and take advantage of career opportunities such as Fellowships that can benefit them in a similar way.