The term ‘clinical trials’ covers a wide range of different types of research (see also ‘Why do we have clinical trials in children and young people?’
). Trials are often used to test new medicines or vaccines but can also be used to look at new combinations of existing treatments. They can also be used to test whether giving a treatment in a different way will make it more effective or reduce any side effects.
In Phase 1 and Phase 2 trials everyone taking part will get the treatment being evaluated. At Phase 2 the researchers will know more about the treatment. The aim of a Phase 2 trial is to test the new treatment, such as a drug, in a larger group of people to better measure safety and side effects and see if there are signs of positive effects in patients. A Phase 2 trial may or may not involve comparison with another treatment. However, the numbers of people included are still too small to give reliable evidence about whether the treatment is effective or that any change is not just happening by chance. This is why Phase 3 trials are needed.
Phase 3 trials are usually large. They include hundreds or even thousands of patients. They often compare the effects of new treatments or drugs with treatments that are already being used, if there are any. They help to show whether newer treatments are better, or worse than existing treatments. They can give a clearer picture about how common and serious any short term side effects are.
Almost all Phase 3 trials are ‘randomised’ trials. This means that people are put into one of the groups in the trial at random, often by using a computer programme. When people are randomised they have an equal chance of being in either trial group. Random allocation helps ensure that two very similar groups of patients will be compared, so if one group does better, or worse than another, it is likely to be because the treatments being compared have different effects, and not because of differences between the people in the groups.
(Sometimes you may hear the group who are having the new treatment called the ‘experimental group’, ‘trial group’ or ‘intervention group’. This can be confusing, as all the groups, including the control group, are part of the trial, and people in the control group may also be given an intervention, in the form of the standard treatment or placebo.)
If no standard treatment is available, the control group may not be given any specific treatment, or may be given a placebo. A placebo is a treatment with no active ingredient, which is designed to appear very like the treatment being tested. By comparing people’s responses to the placebo and to the treatment being tested, researchers can tell whether the treatment is having any real benefit, rather than patients simply feeling better because ‘something is being done’.
There are several ways in which the results of trials can be made as reliable and accurate as possible. One of these is to make the trial a ‘blind trial’. In a blind trial the participants are not told which group they are in. This is because if they knew which treatment they were getting, it might influence how they felt or reported their symptoms. Some trials are double-blind, which means that neither participants nor the doctors and others treating them know which people are getting which treatments. This also avoids the doctors’ hopes and expectations influencing the results of the trial.
Some trials are designed to try out ways to prevent a particular disease in people who have never had the disease, or to prevent a disease from returning. The treatments being tested in these types of studies can include vaccines, but may also involve drugs or other treatments.
Sometimes vaccine trials require healthy children as volunteers. Parents that took part in vaccine trials explain how they felt that taking part has helped to protect their children and helped improve knowledge.
Drug trials are probably the most familiar type of trial for many people. Drug trials may be testing whether a new drug has any major side effects, or whether it works better than an existing treatment, but they may also test timing (when or how often to give a drug) or dosage (how much of the drug is needed to be effective).
In Alison’s case, her son took part in a growth hormone trial to help him grow at a normal rate. She says: ‘And in the first year there’s some uncertainty as to the best dosage, and models are different in America as they are from Europe. So we were part of a trial to see which dose is the best.’
Randomised trials are done when we don’t know which treatment is best, in other words when the relative merits and disadvantages of different treatments are uncertain. It is important to realise that, on average, new treatments are as likely to turn out worse as they are to turn out better than existing treatments. This means that, going into a trial, everyone, regardless of which of the treatment groups the computer allocates them to, must have similar chances of a good outcome. If, in spite of the treatment uncertainties that the trial has been designed to address, people would strongly prefer one of the treatments being compared, they should not volunteer for the trial.
Not all randomised trials are drug trials. They may also be testing other types of care, such as different levels of monitoring, the effect of different types of diet, or the effectiveness of different forms of screening.
Paul’s son, who is 8 years old, was diagnosed with Type 1 diabetes at the age of 6. Soon after his son’s diagnosis Paul was invited to enrol his son in a randomised trial to assess hospital versus home management in newly diagnosed childhood diabetes. Paul discussed the trial with his son and they agreed to take part.
There is also growing interest in testing different ways of giving people health information, to see which is most helpful to them in making decisions or understanding and managing their condition.
Parents were sometimes unsure how many other children were taking part in the trial, and some understood that there were lots taking part. The number needed, the ‘sample size’, will vary from trial to trial, depending on the condition, the treatment being tested and how big or small an effect the treatment is expected to have. The sample size is proposed by statisticians doing ‘power calculations’.