Tailoring Rheumatoid Arthritis Treatment
If you live with rheumatoid arthritis, you know that finding the right treatment involves a lot of trial and error. That could soon change thanks to a new study that aims to take the guesswork out of treating this serious, autoimmune disease.
“A lot of current treatment decisions are physician-guided and based on what we know on average,” said Dr. Glen Hazlewood, a rheumatologist and research scientist at Arthritis Research Canada. “We want this study to result in personalized medicine. We want physicians to be able to choose the right treatment for each patient – the one with the best chance of working when someone is first diagnosed.”
This research is part of a wider shift towards personalized, or precision medicine, and will involve analyzing data from big, randomized, rheumatoid arthritis trials to investigate whether certain patients respond differently to certain treatments.
We sat down with Dr. Hazlewood, who is leading this four-year study, to find out more about this groundbreaking research.
Why is personalizing treatment important for people with rheumatoid arthritis?
In short, rheumatoid arthritis is not the same for everyone, so treatment can’t be the same. This disease doesn’t just affect one part of the immune system. It impacts multiple parts and is different for everyone. For this reason, we currently develop treatments directed at different parts of the immune system. For one person, a specific part of the immune system might be driving the disease. So, targeting that specific part might be very effective. For another person, inflammation might be caused by a different part and they might get more benefit from a different drug. People also differ in their preferences around treatments and what matters most to them.
What will this research involve?
There are three components. The overall objective is to develop personalized predictions of benefits and potential harms to guide treatment choices for rheumatoid arthritis at three stages of disease: initial treatment, second line treatment (choice of first biologic) and third line treatment (choice of second biologic). We want to incorporate this into a decision aid that allows physicians to input information and identify the risks and benefits of treatment options for each patient, and communicates this to patients in a way that helps them make the best decision together with their rheumatologist.
To accomplish this, we will analyze multiple different data sources including doing what’s called an individual patient network meta-analysis, which is a fancy way of looking at all of the big randomized trials on rheumatoid arthritis treatments. We also have access to individual patient data for these studies. And we will look at data from three large Canadian studies, which have followed patients with rheumatoid arthritis for over 10 years.
What do you hope this research accomplishes for people with rheumatoid arthritis?
Ultimately, we want this research to result in personalized medicine. We want it to help physicians choose the right treatment for each patient and avoid the trial and error of switching between drugs.
The decision aid we create will include a risk calculator, which is a tool that allows a doctor to enter a patient’s characteristics. For example, how severe their rheumatoid arthritis is, how long they’ve had it, etc. and get estimates on which treatment might be better in terms of benefits and fewer side effects. Importantly, the decision aid will then present the information in a way to help patients make informed choices together with their rheumatologist.
Will this research help eliminate some uncertainty in treatment decision-making?
It’s really overwhelming to be diagnosed with rheumatoid arthritis. Negative emotions also come along with being diagnosed with a chronic disease. But there is also hope. Once there is a diagnosis, a treatment plan can be initiated. We have treatments that can help people get better. Early on, the physician makes most of the treatment decisions. It’s new to patients and they just want to get better. As time passes, patients get more and more familiar with their disease. They have tried different treatments and know side effects, so preferences around treatments and their interest in being more involved with decision-making evolves over time. This research is all about trying to help patients choose the right treatment at the right time.
It will be impossible to get to a point where we know with 100 per cent certainty that a treatment will work for one patient and not for another. But the goal is to use the best available data to tailor choices as best we can. The goal is to reduce uncertainty and frustration by trying treatments that have the best opportunity to work.