Patient and public Involvement in Numerical aspects of Trials (PoINT)

 What does it mean? When patients enter a trial, we collect their information. We usually collect their information at baseline (who is taking part in the trial?), and during follow-up (with questionnaires and/or clinical visits). This information is gathered in a database and analysed to answer the ultimate trial question - does the treatment work when compared with a control (usually another treatment)?  Trial analysis is complex and involves statistical models that estimate the treatment effect, ie how well the treatment works when compared with a control.  The statistical models we use to analyse trial data may be "adjusted for" patient's characteristics. This usually happens if we believe those characteristics are important to understand the treatment effect. Statistical models make assumptions about the information collected and it is important to know those assumptions in order to interpret the findings of the trial correctly. An example In the toothpaste trial, we...

What does it mean? Trial results are presented as numbers (for example, how well a treatment works) in long and detailed reports. An example When our toothpaste trial is over, we will have to discuss what the findings mean, how can they be applied in a wider context. We will want to show results to the trial team, and to the dental community, academics and patients. To do that, trial teams usually prepare presentations and reports. Whenever numerical information is presented, we will have to make calls on how to report it.  How could patients be involved? Patients could contribute to a better understanding of what the findings mean, as well as help co-design dissemination materials that include quantitative trial findings reported in a clear way.

What does it mean? Subgroup analyses try to find out whether the effect of a treatment is different for different types of people (e.g. men and women or different age groups).  Subgroup analyses are usually defined at the start of a trial, but may be discussed later on. Any subgroup analyses should be well justified as it can lead to wrong results or interpretation if not planned carefully. You can read more about subgroup analyses and how they can be tricky to interpret here .  An example In our toothpaste trial, we might be interested in finding out whether the effect of toothpaste A when compared with toothpaste B varies depending on the patient's age. For that reason, we will collect participant's age at the start of the trial and present the treatment results by age group. How can patients be involved? Patients could be involved in the discussions about what characteristics might be important to measure to explore differences in how well a treatment work.