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Good Trials need Good Maths!

Clinical trials are described as the gold standard way to test treatments with patients or healthy volunteers. We look at key aspects such as the safety of treatments, their effectiveness to treat a certain condition or disease or a clinical approach to improve a patient’s quality of life.

But what are the stages of a clinical trial? Well to start off, we have the design, conduct, monitoring, analysis and reporting aspects of a trial. In that order, to be specific! Each of these stages of a trial are as important as each other. The latter stages of a trial are dependent on the successful running of previous stages.

So how much thought goes in to the planning of a clinical trial? Well first off, we need qualified and experienced people – experts in trial planning to help us choose the right study design. Then, we recruit our study participants, ask for their consent to participate, collect their data and analyse it. But what do we mean by ‘data’? And what do we mean by ‘analyse’? Do we analyse our study participants as a whole and as individuals?

If you were anything like me in school, maths wasn’t exactly my favourite subject. I struggled with understanding its relevance to everyday life! But if we start to look at maths as ‘the science of numbers’, we now see its place in our type of science, clinical science and therefore, clinical trials.

When we say ‘data’, we mean any piece of information that can be measured from study participants, combined together, analysed and interpreted in a meaningful way to help future patients. But there’s that word again! Analysis.

A trial analysis involves a detailed examination of the data collected, to form results. But how does this help patients? If we gather enough information from trial participants, we can be more confident in the results we get. However, we need to think about this maths, or statistics as it is called in clinical trials, from the beginning too. We need to think about what type of data we will collect, how much data we can collect from each person, how we will organise the data, what kind of outcomes we hope to achieve and most importantly, the correct tests to run, to analyse this data. Maths also plays other roles in trial design, such as: ‘randomisation’ – where we can use maths to randomly assign treatments to trial participants for a fair study. We use maths to calculate ‘sample sizes’ that tell us how many trial participants we need. Therefore, good maths (statistics) and good analysis, is not possible without good planning and good conduct of a trial – mainly, through good people!

Statistics, a more wholesome term, is the branch of maths that involves everything from the collection, analysis, interpretation and presentation of numbers. It combines both the data collection element, the maths of it (the analysis) but also interprets the results – by putting numbers, into words and actions that can be applied to clinical practice and help patients. This can be through running tests on the numbers to see trends or patterns – meaning, the numbers need to tell us a story. And it’s up to experienced researchers to correctly interpret these numbers. The numbers may not be significant. They may show that an intervention didn’t work or wasn’t beneficial to a group of patients. But that’s still useful information. It tells us to move on with our research and find something else! Statistics can also tell us whether one treatment is better than another and which group of patients a treatment is more suited for. Statistics can also tell us why different people respond differently to certain treatments. It helps doctors, nurses and other healthcare professionals make informed decisions, in what we call ‘evidence-based medicine’, when deciding treatment plans for their patients.

However, because of its importance in clinical research, we need to be honest with our maths. And by this, I mean we need to accurately and ethically collect data the same way for every patient so that the results will be reliable. Clinical trial professionals (or, ‘trialists’) need to plan their maths before they have the numbers. A good scientist will think about the statistics before the trial recruits participants, to prevent mistakes in the long run.

When telling the story of a clinical trial, we need to report all the statistics. There have been several cases of trials where results are “cherry-picked”, to only include the positive ones. This means that these trials only report, for example, statistics showing the benefits of the drug and leaving out the numbers about the drug’s side-effects. This is known as ‘selective reporting’ and unfortunately, happens all too often. This is why we use the word ‘transparency’ when it comes to reporting. Trials should be transparent. Both the good and the bad numbers need to be published so that it is a fair reflection of the study. Presenting half a clinical trial story is not only misleading to healthcare professionals but can be harmful to patient’s lives.

Taking part in a clinical trial can be a big ask for patients – asking them to give up a portion of their day, travel to clinics, offer their data (and their bloods in some cases)! We therefore owe it to them to be truthful and accurate in our reporting – and this starts with having a good design which leads to good conduct and most importantly: good maths!

Thanks for reading my first blog 😊


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