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

This blog was created to inform you of statistical aspects of trials, what their impact might be in trial analysis and results, and how patients may get involved in defining them. The posts available here are aimed at patients and members of the public interested in trials. Each post covers a different statistical aspect of trials that is included in our INITIAL survey. They all use the toothpaste trial as an example to bring the aspects to life.  If these statistical aspects have been explained in lay terms elsewhere, we have included links to learn more. 

 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.  

What does it mean? When a participant outcome is unavailable, due to a missing questionnaire or non-attendance to a trial related clinical appointment, their results are unknown. We call this missing data. In the toothpaste trial, this would mean we don’t know a participant's pain score at the end. We have a number of options available to try to account for the missing values. For example, we can use statistical tools that aim to predict what happened to patients that did not provide results, taking into account these predictions are uncertain, ie we do not know for sure what happened to those participants. You can find out more about what missing data is and its impact on interpretation of treatment claims here . How could patients be involved? Patients can help us predict missing values so we can assess treatment effect with more certainty. Example  Some participants in the toothpaste trial will have their pain score missing. For those participants and to ensure we investigate di

 What does this mean? In trial analysis we are interested in understanding how well a treatment works. However, as the trial journey evolves and becomes more complex, this question can also be more complicated than what it looks. For example, we might be interested in understanding whether the treatment works for all patients regardless of whether they take it as instructed, or whether the treatment works in patients that tolerate the treatment. An example When Emma developed mouth ulcers after three months of using toothpaste A, she decided to stop using the toothpaste. In this case, Emma was no longer adhering to the treatment after three months because she was not using it at all. A decision needs to be made about whether Emma is included in the final analysis of the trial or not. This will depend on the question - are we interested in knowing how well toothpaste A works compared with toothpaste B irrespective of whether patients took the treatment? Or are we interested in knowing h

What does it mean? Most treatments come with a risk attached - they may lead to harms and side effects, even when they benefit patients. It is crucial to measure harms and side effects and show this information by treatment. This ensures patient's safety is always considered when running a trial and interpreting findings. An example As Emma starts using toothpaste A, she notices she has developed a strange side effect - she develops mouth ulcers and is concerned. She contacts her dentist who immediately reports this side effect to the trial team. The trial team keep note of this side effect, along with others that are reported from other patients. During the trial, and at the end, the trial team analyses and presents this information. How can patients be involved? Patients can help researchers when summarising and presenting data on safety, to ensure it is clear and can be discussed by the whole trial team. Patients can be involved in interpreting the safety analysis findings.

What does it mean? Adherence is a way to say whether a treatment was taken as intended, or what we consider in a trial as "treatment completed".  For example, if patients are allocated to get toothpaste A or B, how often would they need to use it for us to consider they "completed their treatment"? This is usually defined when writing the trial's plan (protocol), but may be defined later in the trial. You can find more information on adherence here:  Adherence - EUPATI Toolbox An example In the toothpaste trial, our participant Emma has been allocated to toothpaste A. Toothpaste A is stronger than toothpaste B, and tastes horribly. Emma uses toothpaste A for two months, twice a day, but ends up switching to toothpaste B, which is available in the supermarket. Has Emma completed her treatment?  How could patients be involved? Patients could help us decide what is a reasonable and acceptable definition of adherence to treatment. Patients could also be involved in

What does it mean? Protocols are plans that set out how a trial will be delivered. However, unexpected events may happen, or mistakes can be made which lead to what is called a "protocol deviation". In our toothbrush trial, imagine that by mistake a patient allocated to toothpaste A is given toothpaste B. Or that we should only include patients that have no history of toothache, but a patient fails to recall this until after entering the trial. Those can be considered protocol deviations. An example Emma joined the toothpaste trial and was randomised to receive toothpaste A. Emma takes her toothpaste prescription to the pharmacy and takes her toothpaste A home. However, Emma lives with Jess and they usually share their toothpaste. A few times Emma, by mistake, uses Jess toothpaste. When she realises this, she reports it to the trial team. The trial team decide this is a protocol deviation. How can patients get involved? Patients can be involved, along with the research team,

 What does it mean? Screening data is information collected before participants are recruited into a study. The information collected can help assess how representative patients in the trial are of the target population since we can compare those patients in the trial to those that declined to take part.  An example In the toothpaste trial, dentists recruit patients to the trial. Before patients are recruited they are asked about their age and gender, but some eligible patients decide they are not interested in being involved further. If they accept, their age and gender can still be used to compared with the age and gender of patients that accepted to take part. How can patients be involved? At the design and protocol stage of a trial, patients can be involved in deciding what is important and acceptable to measure at the screening stage. During the trial, patients can help decide how to summarise this information and present it to the trial team or in reports.

 What does it mean? Once patients enter a trial, they start a journey. After being randomised to receive a treatment, they will be followed up. This may involve answering questionnaires or attending clinical visits with their doctors. As the trial journey evolves, some participants may leave the trial actively (for example, they no longer wish to participate) or passively (they stop answering questionnaires or attending clinical visits). A participant's flow diagram aims to summarise this information so it is easier to understand the overall patient's journey in the trial in each treatment.   An example How can patients get involved? Trial participant's flow diagrams are usually prepared based on something called CONSORT . This is a set of recommendations to improve reporting of trials in academic publications. It is considered good practice to use these recommendations and they are often mandatory. However, there is room for discussion on what to report in the flow diagram

 What does it mean? Trial participants may leave the trial actively (for example, they contact the trial team to say they no longer wish to participate) or passively (they stop answering questionnaires or attending clinical visits, this is usually called "lost to follow-up"). Both options are called "withdrawal from the trial". From a trials analysis point of view, they usually mean we can't include these participants in the final analysis.  An example Emma was happy to join the toothpaste trial and attend clinical visits every year for three years. However, she started a new job in a different city and is no longer available to attend clinical visits. Emma contacts the trial team and says she no longer wishes to take part. Emma has withdrawn from the toothpaste trial. How can patients be involved? Patients can be involved in collecting and interpreting information related to trial participant's withdrawal. They can also help decide the best way to summarise

What does it mean? Baseline data is information collected  at the beginning of the trial, before any treatment starts. It is usually a patient symptom or characteristic (for example, age, gender, pain, blood pressure). An example Before the toothpaste trial starts, Emma has to fill out a form. That form asks her about her age, gender, and self-care dental habits. Emma's information, along with all the other patients in the trial, is then summarised and presented. This helps confirm patients in the toothpaste A group are similar to those in the toothpaste B. It also allows us to understand who are the participants in the trial, and how similar are they to the general population or the population needing a toothpaste treatment. How can patients get involved? Before a trial starts, and at the design and protocol stage, patients can be involved in deciding what is measured before the treatment starts. During the trial, patients can help statisticians and other researchers decide the be