A disease is considered rare when it affects fewer than 2,000 people in the population. In Europe alone, approximately 30 million people in total suffer from a rare disease. Those worst affected are children, with childhood cancer being classified as a rare disease.

“When put together, this is a big problem for all of society. Many are affected, that's why there is a need,” says Frank Miller.

Those worst affected are children. Photo: Creative commons 0
Those worst affected are children. Photo: Creative commons 0

He is involved in two different projects, InSPiRe and IDEAL, which aim to design and analyse planned clinical trials to test new treatment methods for the patient group.

“The EU is financing the project to ultimately improve the chances for patients with a rare disease to receive treatment. It has been established that we need to develop new statistical methods. This difficult problem can be solver in a better way,” he says.

Performing clinical trials for rare diseases is more difficult than for common diseases – this is where the research comes in.

“The problem here is that there aren't as many patients as you would like to have participate in the trial. As a result, it isn't possible to carry out an experiment of the usual size,” he adds.

How are you working with this problem?

“There are a lot of perspectives on this issue, and I'm working with some ideas. One thing that I'm working with is the different ways to motivate and calculate the size of the random samples.

It is also possible to work by gathering information from various other sources, for example from similar treatments that have been examined previously,” explains Frank Miller. Using what is known as the Bayesian approach is suitable for this problem.

Frank Miller. Photo: Department of Statistics
Frank Miller. Photo: Department of Statistics

Put to the test for doctors

Generally, when you are going to compare a new treatment method for a disease with the standard one to see if the new one is better, you select a number of patients and then decide at random which treatment they will receive.

Then you examine how the patients have responded to the new treatment – whether it has had any effect or not. As the patients are chosen at randomly, it is possible to see if the new treatment is better than the standard one.
It's often the case that the doctors have thought a lot about the treatment in advance and are already convinced that it will work, explains Frank Miller.

"Then it is up to the evidence to show whether the treatment is of any value. A lot of the time they turn out to have been too optimistic." 

Concrete use of the statistics

Frank Miller explains that they are working in a mixed project group. In the group there are some who have great methodological strengths in mathematical statistics and others with long experience of clinical studies and diseases.

“One important aspect of the project that's close to my heart is just bringing statistical methodology together with concrete, practical needs. It's really important that the two forms of expert knowledge are introduced to – not isolated from – each other.”
What do you hope to achieve?

“Research usually moves in small steps. I'm not expecting a revolution, but hopefully we will arrive a few steps further ahead. If we can make an improvement to a part of statistical methods, then that's good. Hopefully the development will continue, even when the projects are over,” says Frank Miller.

Translation from Swedish by Språkservice Sverige AB