Challenges in Optimally Treating Multiple Sclerosis
EP: 1.2017 Changes to the McDonald Criteria: Diagnosing Multiple Sclerosis
EP: 2.Use of MRI in Diagnosing Multiple Sclerosis
EP: 3.Misdiagnosis of Multiple Sclerosis
EP: 4.Cerebrospinal Fluid in Diagnosing Multiple Sclerosis
EP: 5.Challenges in Optimally Treating Multiple Sclerosis
EP: 6. QoL Issues in the Management of Multiple Sclerosis
EP: 7.Multiple Sclerosis Fatigue
EP: 8.TRIUMPHANT-MS Trial: Fatigue in MS
EP: 9.OPTIMUM Phase 3 Trial: Secondary End Point Effect on Fatigue
EP: 10.Strategies for Choosing Initial Therapy in MS
EP: 11.Anti-CD20 Monoclonal Antibodies for Treatment of RMS
EP: 12.Cladribine for Treatment of RMS
EP: 13.S1P Receptor Modulators for Treatment of RMS
EP: 14.Fumarates for Treatment of RMS
EP: 15.The Future of Managing Multiple Sclerosis
Mark Freedman, MD, MSc, outlines the challenges in optimally treating multiple sclerosis, including prognosis, picking the right first agent, and monitoring and assessing treatment response.
Fred Lublin, MD: Let’s move into a broader question. This is for you, Mark. What are the current challenges to optimally treating patients with MS [multiple sclerosis]?
Mark Freedman, MD, MSc: That’s quite the question, Fred. I could probably take up the next hour working on that, but I’ll try to summarize. My thinking on this concerns 3 areas, and each of these is developing in evolving fields. One of the first things you do as soon as you’ve made the diagnosis is get an idea of what sort of disease this patient is bringing to the table. Use all the features of the clinical exam, the patient’s history, and all the paraclinical test results to give you an impression of their prognosis. Are you catching the disease early, or is this a person who is bringing a lot of silent disease to the table? If this someone who’s acquired a lot of deficits and if they have another attack, it could be the straw that breaks the camel’s back.
Prognosticating and getting an impression of where this patient is in the spectrum of presentation helps you make the next decision, which is picking the right first agent for that patient. I wish we had better ways of evaluating our different therapies. We can group them into moderate efficacy and higher efficacy, but beyond that, trying to select a best agent for the patient requires a bit more science that we simply don’t have.
We need to be able to ballpark that. People have often talked about moving through an escalation strategy. Start low and then only escalate if the disease declares itself. Alternatively, you can use induction therapy, starting with a higher-efficacy therapy. That’s based on your sense of prognosis. When you say optimal treatments, ideally, we would stop the disease in its tracks. But we all know that none of the medications is able to do that, unless you go to the very extreme, which is to replace their immune system. That is not appropriate for most patients.
The first thing is prognosis. The second is choosing an agent appropriate to the prognosis. Now we get into the hardest part, which is monitoring and assessing the treatment response. We’ve all come up with various means to do that. We just published our Canadian treatment optimization recommendations based on a lot of information we’ve gained over the past several years. All this indicates that there may be some degree of disease activity through our measures that is acceptable for the appropriate therapy, or which perhaps does not pose a big risk for that individual. This is keeping in mind that there’s nothing that achieves 100% NEDA—no evidence of disease activity. But you want to try to get as close as you can to that for optimal treatment. This also implies that the patient is tolerating and taking the medication, and that’s a given.
Monitoring treatment response is key in deciding which threshold this patient has exceeded and what we would have expected with optimal treatment vs without it. That would dictate a change in therapy. This a challenge in the progressive forms of MS, where we now have some therapies. It behooves us to try to figure out whether we are winning or losing the battle, knowing full well in the trials with these drugs that the progression is expected. Even on the appropriate therapy, how do we know we’re winning the battle? We need some other measure that tells us that we’re doing something to disease. This is where the value of the evolving biomarker lies. Measuring neurofilament light chain or the GFAP [glial fibrillary acidic protein] marker in the serum might help us know if we are getting at the progressive nature of the disease with our therapies. Otherwise, it’s futile to continue.
