Video
Molecular Signature Response Classifier (MSRC) Test to Guide Treatment Selection in RA
Author(s):
Experts in rheumatology review the molecular signature response classifier (MSRC) test for use in guiding RA treatment selection.
Nehad Soloman, MD: Given that TNF [tumor necrosis factor] therapies are the most commonly prescribed biologic post-methotrexate or leflunomide synthetic DMARD [disease-modifying antirheumatic drug] therapy and knowing that although they respond better than methotrexate, some patients don’t respond or have an inadequate response; are there any tools that you’re aware of that may help predict if you will have a response or nonresponse? I know we’ve often wished for the Holy Grail rather than the guessing game of “Your insurance will cover this, this is a pretty good drug, let’s try that,” but really to get to the heart of that precision or individualized medicine for our patients.
Joy Schechtman, DO: We’re using a test called the Molecular Signature Response Classifier, or MSRC, and that comes from a lot of the science that came out in 2020 and 2021. Then an article that Bob was an author on in 2022, and then there’s some new data here at the ACR [American College of Rheumatology]. In looking at that testing, it’s giving us this light that we have a test that’s going to point to some of these patients who are not going to be responders and say to us that the TNF drug probably shouldn’t be started first. We want to get these patients in low disease activity very quickly; we want to get that trust between the patient and the physician. And by using some of this precise precision medicine, we’re going to get that patient started on the right drug quicker, get their disease under control, and prevent their comorbidities. We’re going to start a whole new age of how we treat our patients with a very devastating disease process.
Nehad Soloman, MD: Thanks, Joy. You mentioned Bob was an author on the first AIMS [Accelerate Information of Molecular Signatures] paper. Can you tell us a little bit about the AIMS study and your work in that?
Robert Levine, MD: I was an investigator in the AIMS trial, which was a real-world study. Basically, they had almost no inclusions or exclusions except that the patient had to have rheumatoid arthritis. We were supposed to say that if they were not responding to their current treatment, which at the beginning was a traditional DMARD, but later on in the study it was added that they could be on a biologic at entry. They had to be a candidate to go on to advanced therapy. It’s not like they should be contraindicated, so there wasn’t any joint count that was required; there weren’t disease activity measures that were required. They were collected at screening, but they weren’t collective. The study time 0 was when the decision was made to start an advanced therapy, and we had already collected the molecular signature. What happened is, we had the choice. We didn’t have to follow the test and in fact more than 61% of the time that advanced therapy was added, it did not follow the results of the molecular signature test. The results of the molecular signature test say, is the patient likely to not respond to a TNF inhibitor or is that signature of response not there, double negative, or in other words there’s no reason not to use a TNF inhibitor in that patient. We could do whatever we felt was appropriate or what the insurance dictated as the treatment that was initiated. Basically, the primary endpoint was ACR 50 at 12 and 24 weeks. The primary end point was 24 weeks, and the secondary end point was at 12 weeks. We also collected other composites such as CDAI [Clinical Disease Activity Index] and some of the AIMS publications have focused on CDAI rather than ACR 50. This is the design of the trial.
Nehad Soloman, MD: It’s interesting, you mentioned 61% didn’t follow the test recommendation, and that was mainly due to insurance reasons and coverage more than anything else. It is also interesting that these patients were tested, if you will, in the wild. It was, let’s see how this performs and as the data was aggregated and then looked at, it was very fascinating to see what the ACR 50s were or how we met the end points, also the P values being statistically significant sort of giving more credence. I know as rheumatologists, I’m guilty of this as well, we tend to be cynics. We all want the Holy Grail, and then when somebody offers an insight or shines a light on some of the potential therapeutic benefits or nonbenefits, we become skeptics.
Robert Levine, MD: If I can add to what you just said; among rheumatologists, it’s been my impression that some of us will adopt new technologies and new treatments early, and others want to wait for more. Many are skeptical, and appropriately skeptical as we’ve seen things not pan out in the past. There’s across the board a wide spectrum of us and just our willingness to accept new stuff, and this is new technology. I think the study was nice because it didn’t dictate to us what we needed to do. If we were solidly in the camp that TNF inhibitors are our first-line therapy no matter what, this study was there to shed some light on whether the study that we did, the blood study, performed. Did it predict nonresponse to TNF inhibitors? Or was that not a finding, and it turned out that the study was a success?
Nehad Soloman, MD: The fact that it corresponded to 43.2% relative improvement in achieving a lower CDAI disease activity level makes it very exciting to see this type of data arise. Joy, what’s your impression of the data and the test?
Joy Schechtman, DO: I think it lends us to have more objective criteria on what we’re doing with our patients. Some people do say we live in the gray zone as rheumatologists; we’re very conservative, we want to look at the science, we want to take our time in evaluating everything. But when you’re looking at this test and you see the numbers and the percentages of patients doing well, it tells us that using our gestalt kind of ideology is probably not that good. As oncologists have shown us that this is precision medicine, we need to go forward into the 21st century, and using some of these scientific measures helps us in wading through which drug to start with first. Bob mentioned something early on; he talked about the fact years ago when we didn’t have biologics, what we would do is sit there and say, let’s do this anti-inflammatory, let’s do that anti-inflammatory. Should we be using methotrexate in patients who do not have cancer? That was even part of our decision-making. Now we’ve moved way past that, and now…we have the tools. We have biologics, we’ve got targeted synthetic treatments, and we need to look at the science and be more precise about which drugs we start early on to bring those patients from high disease activity down to low disease activity and do that targeted therapy. We’re treating the target and getting that disease under control, and I think more precision testing like this has been shown to give us that option and to be more precise in what we’re doing as clinicians.
Transcript edited for clarity
