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International Clinical Trials Day helps to raise awareness of clinical trials and recognises everyone involved in and affected by trials – researchers, clinicians, statisticians, patient participants, funders and the wider public.

Here at NDORMS, the Centre for Statistics in Medicine celebrated how statistics underpin every element of a trial and how we all work together to make a difference in patients’ lives.

 Sallie Lamb – Director of CSM and trialist

After a 20-year career in clinical trials, International Clinical Trials Day gives me a chance to reflect on the importance of randomised controlled trials and on all of those exceptional people who give the gift of their time or career in the pursuit of high quality medical research. Randomisation remains the only true way to lay the foundation of bias-free experiments and to deliver robust proof that one or more types of healthcare are better (or worse) than another. That’s not to say other types of experiment don’t yield important new knowledge. 

As trialists, we face many challenges on a day to day basis. The stakes are high – allocation of scarce health resources, professional practice, industrial and personal wealth, and public, patient and government expectations for rapid cheap solutions to increasingly complex health problems. Regulation and accountability are rightly tight. The level of commitment needed from research professionals, our health sector partners, patients and their families is immense. Support from governments across the world is at an all-time high and the fruits of our labour are beginning to yield. There are real improvements and informed choices for patients and families. Let us take a moment to celebrate and be thankful for all the support and commitment, and then, onward and upward. Our journey is only just beginning.

Caption: NDORMS staff working on clinical trials were inspired by the NIHR’s #IAMRESEARCH campaign

Caption: NDORMS staff working on clinical trials were inspired by the NIHR’s #IAMRESEARCH campaign

Eleni Frangou – Medical statistician

Parallel or cluster trial? T-test or ANCOVA? Block randomisation or minimisation? Setting up a clinical trial so that the data we get at the end can actually answer our research question means thinking through a lot of different options. Statisticians are able to answer these and many more questions to help ensure a safe, ethical, successful clinical trial.

We’re involved in a trial’s journey right from its inception, when we advise on the most suitable trial type, work out how many participants the trial needs, and draw up an analysis plan for the final data. These elements are vital in making a grant application successful. Our involvement doesn’t end there. As the trial recruits and follows each participant, we prepare important recruitment and safety summaries to monitor the trial’s progress and keep our participants safe. Once the recruitment and follow-up are complete, we analyse the data and prepare the results to share with the world.

We strive for quality, efficiency and excellence in our clinical trials. That means keeping on top of the literature and attending courses and conferences so that we can use new and flexible methods, such as adaptive designs.

Designing and running trials is not effortless. It can take years to see the results published - but no one said making a difference is easy! I enjoy working on clinical trials as I get to learn lots of exciting things across medical disciplines, and I am proud to be able to contribute to evidence-based healthcare. 

Four people, three women and one man, smile at the camera as they hold signs onto which they have written how they are involved in clinical research. The first sign reads "I am dreaming about equal high qual. health for all across the globe!" The second dign reads "I am a trial statistician and proud of it!" The third sign reads "I am Melina and I help DRAFFT2, WHISH, RIDD, TRAFFIX, PARCS, MANTID, WHITE and NINJA to prove cost-effective." The fourth sign reads "I am a dedicated and passionate statistician."Caption: From left, Cynthia Srikesavan (postdoctoral research assistant in physiotherapy), Eleni Frangou (medical statistician), Melina Dritsaki (health economist) and Seid Mohammed (medical statistician)

Melina Dritsaki – Health economist

Although we’re not on the frontline with patients, the work of health economists benefits all patients by helping the wider community balance our limited healthcare resources. Restricted budgets unfortunately mean we can’t offer every healthcare intervention. Policy-makers need to make decisions that preserve equity and optimise resources. The findings of a well-designed and carefully delivered randomised controlled trial with a strong health economic component are invaluable for informing these decisions.

With a lot of clinicians asking good questions about the efficacy of new interventions, procedures and healthcare technologies, there comes questions about the economic viability of what they are testing. While clinical effectiveness should be and always is the primary aim of a randomised controlled trial, we can also answer other important and interesting questions while collecting individual patient information – like cost-effectiveness.

Health economists try to estimate how much it costs to deliver an intervention and what healthcare resources are used in the process. We look at things like how long it takes to deliver the intervention, medication costs, how the disease affects a participant’s ability to return to work, and what kind of expenses the participant or their family has to cover due to the disease. We are also interested in measuring the benefits of the intervention, both clinical progress and improvement in quality of life. We use self-reported information from participants to capture their ability to manage everyday life, both physically and mentally.

We combine all of these costs and benefits to work out the intervention’s cost per quality adjusted life years gained. This ratio can be used by groups like policy-makers and healthcare trusts to decide which interventions to recommend.

A thorough health economic evaluation – and indeed a strong trial – requires close collaboration between the whole trial team: clinicians, statisticians, health economists, trial managers, quality assurance managers, qualitative researchers and patient representatives. This exceptional mosaic of expertise helps us make decisions about the delivery of the intervention, patient recruitment, patient safety, ethical considerations, statistical power, economic evaluation, patient satisfaction and much more. Working as a health economist with clinical trials is rewarding and fulfilling, with a tangible perspective of social contribution!

Four people, three women and one man, smile at the camera as they hold signs onto which they have written how they are involved in clinical trials. The first sign reads "I am helping ‘OPAL’ to shine!" The second sign reads "I am helping to ‘BOOST’ recruitment." The third sign reads "I am doing my ‘BEST’ for research!” The fourth sign reads "I am helping ‘OPAL’ to bare fruit!" OPAL, BOOST and BEST are all trials run by the OCTRU trial unit.Caption: From left, Katie Chegwin (apprentice clinical trial support officer), Laura Nevay (clinical trials administrative coordinator), Oliver Conway (clinical trials administrator) and Angela Garrett (BOOST clinical trial manager)

Michael Maia Schlussel –Medical statistician

Although I am now a statistician for clinical trials, I first started working in research after getting a degree in nutrition. How did a nutritionist end up doing data analysis for clinical trials? The reasons for my career choices happen to be the same reasons why statisticians are important in the development of a clinical trial! 

I decided to join research because I had a burning curiosity about how medical science is built. I decided to learn how to do data analysis when I realised that most of the evidence available was unreliable, mainly because of improper use of statistical principles. I am not just talking about hypothesis testing. The role of a statistician in clinical trials is not restricted to analysing the data – or at least it shouldn’t be! We need clear statistical thinking from the trial’s very beginning when the research question is defined, through to how the trial is conducted and the data collected, and until the trial’s final reports are made available in as complete and transparent a manner as is possible. 

Only when we understand what can be done with clinical data and the best way of collecting and reporting it, can we be sure that we are using research resources to their fullest potential and achieve the main goal of medical investigation: provide the best evidence for improving patient care. This is why I decided to become a researcher. That is why I decided to train as a statistician. This is why statisticians are important for clinical trials.

A man and a woman smile at the camera as they hold signs onto which they have written their involvement in clinical trials. The man’s sign reads "I am passionate about a healthy future for all!" The woman’s sign reads "I am proud to help towards generating data about what is best for patients across medicine :)”Caption: From left, Asif Kamal (trials programmer) and Vicki Barber (OCTRU Hub manager)

Tim Cranston – Trial programmer

We create and maintain IT systems to enable and facilitate the running of clinical trials, such as recording training, randomising participants, collecting and storing data, and managing the trial. We use programming and IT to enable, not disable, research!

 We work closely with the whole trial team and in particular with the trial statisticians, throughout a trial’s life. For example, the trial team liaises with us and the statisticians to develop data maps for randomising participants and capturing participant information as they visit the trial. Once the data maps have been agreed on, we programme them into our systems, liaising with the statisticians all the time to make sure data will be collected in the best way for later analysis. We also configure the trial management system, allowing the trial team to log and manage clinical trial meta-data, such as follow-up dates with participants. Once data collection has started, we perform data-locks at allotted time points, which we pass on to the statisticians. At the end of the trial we take a final data-lock for the statistician and then archive the data and close down the systems.

 As I really enjoyed biology at school and am from a medical family, I like the exposure to the biological and medical world that working with clinical trials provides. It’s great to work on multiple projects with lots of people researching novel areas at the cutting edge of research, and it’s always nice to see a trial you’ve been involved with in the news, promoting new research and results found.