The duo from Cleveland Clinic stressed the reasons for conducting real-world data assessing migraine treatments and why it can lead to the ultimate goal of treatment optimization.
This is a 2-part interview. For part 1, click here.
At the 2021 American Headache Society (AHS) 63rd Annual Scientific Meeting, June 3-6, investigators Anam Baig, DO, Aarushi Suneja, MD, and Zubair Ahmed, MD, presented work conducted at the Cleveland Clinic Headache Department that evaluated real-world outcomes of eptinezumab (Vyepti; Lundbeck) in patients with migraine. The retrospective review included 45 patients who received the therapy for migraine and 4 patients who were being treated for new daily persistent headache.
Eptinezumab, a calcitonin gene-related peptide (CGRP) monoclonal antibody, reduced the average headache frequency from 27 days per month to 18 days per month at follow-up visit. Investigators concluded that it appears to be a safe and efficacious treatment option for patients, especially those who have very refractory migraine and have failed other preventives. This was indicated by an average of 14 preventives taken by each patient within the cohort.
Suneja, a headache fellow, and Ahmed, a neurologist, both of Cleveland Clinic, sat down for an interview to provide background on their findings. On a new iteration of NeuroVoices, the duo discussed why conducting real-world data helps uncover more about the use of specific drugs and who they should be prescribed to. They also touch upon the treatment optimization benefits from these studies, as well as future aspirations of research that may be of interest.
Zubair Ahmed, MD: For us, there are a couple of different benefits of real-world data. The first, is that when we have clinical trials, we’re looking at a subset group of patients with migraine that may not be representative of the patients that we see in our tertiary headache clinic. There may be a limit on how many medications they try before they try eptinezumab. There may be a limitation on their PHQ-9 score, meaning that patients who meet a certain level of depression severity aren’t included in the clinical trial. For us, we see patients who tend to have severe migraines. The results that we’ve seen from other eptinezumab trials at other centers may not be generalizable to the patient that we see.
We know the medicine works great for the population of patients that we’re studying in the clinical trials, but our population is a bit different. Does it work equally as well for our patients? That’s what we’re trying to identify. When we did this study, we weren’t sure what to expect. As I mentioned, our patients tend to have a higher degree of severity and a higher degree of frequency of migraine. What we found was that it was equally effective, if not more effective, in our patient population.
What’s more interesting is that patients treated with this treatment after failing maybe 10 different preventives. They had failed to see much benefit from those 10 different preventives and then were tried with eptinezumab. That tells us 2 things. Firstly, a lot of providers are using it as a last therapy after they found that a lot of other things don’t work. Secondly, despite that, patients are still improving. It’s very hopeful for our patient population that even if they tried and haven’t noticed a significant benefit with other therapies, that doesn’t mean that they’re not going to notice the benefit with eptinezumab. That’s one of the advantages. There are other confounding variables that we’re not able to account for as well, which is certainly one of the limitations of real-world studies. But overall, it can be helpful because sometimes insurers are less willing to pay for a new therapy that may be expensive. This type of data can help encourage them to cover these types of therapies.
Zubair Ahmed, MD: One of the biggest advantages we have at the Cleveland Clinic is that we there are a number of resources we can use. Many patients answer questions about their headache frequency and severity, and we’re able to use that data to evaluate the outcomes of patients who we’re seeing in our clinic. One of the questions that we’ve had for a long time is that a lot of patients are treated based on trial-and-error type of method. We don’t know if this is going to help you, so try it. If it helps, great. If it doesn’t help, let me know and we can try something else. That’s generally the paradigm.
The question we want to ask is, ‘can we identify which patients are more likely to respond to certain treatments without doing this trial-and-error method that can take weeks and months?’ The study we’ve recently received funding for is to identify clinical, demographic, and perhaps even genetic variables that may allow us to identify which patients would respond to certain therapies such as monoclonal antibodies, for example. This would be a predictive algorithm that could be used when a patient comes in. That way we can say, this patient has these characteristics, they would be a good candidate for this treatment, rather than the other way of trying a bunch of therapies. We don’t really have a good handle of what might be better and what benefits patients the most. That’s just in one study. I think we also want to expand upon our telemedicine study looking at disparities. Generally, we are looking at outcomes of patients that were on different types of therapies. The hope is that even if we can establish this predictive model or paradigm for one therapy, perhaps you can use the same model for other types of therapies as well.
Aarushi Suneja, MD: The prospective study regarding COVID-19 is at the top of our priority list. In terms of both urgency and timing, as well as because it’s a topic of interest of mine. Hopefully, we’ll work with our recover clinic and be able to take care of this patient population long-term. I’m also interested in traumatic brain injury and post concussive headaches. Again, hopefully our headache center will also have a large role in that long-term.
Transcript edited for clarity.