ACR 2025 Daily Podcasts Day4b Save

This is an ACR twenty twenty five podcast coming to you from Chicago. Hope you enjoy it.

Hi. I'm Sheila Reyes from The Philippines, and I'm here in Windy, Chicago reporting live for RheumNow for ACR Convergence twenty twenty five. In this video, I will be talking about one of the late breaking abstracts that were presented in the poster sessions this afternoon. It's abstract number l b zero nine entitled rotation or change of biologic after TNF blocker treatment failure for axial spondyloarthritis or the RaxPAS study from the group of doctor Daleks. So this study is a prospective randomized open label superiority trial.

It's a phase four study, which was conducted in France and in Monaco between 2018 and 2023 that enrolled patients with spondyloarthritis who developed inadequate response or treatment failure with their first TNF inhibitors for at least three months. And so the group wanted to identify whether what would be the most effective treatment after these patients get an adequate response from their first TNF inhibitors by either getting an or or switching to an IL-17A inhibitor or a second TNF alpha inhibitor. And so the primary outcome was achievement of ASAS 40 at week twenty four, and secondary outcomes were achievement of ASAS 40 at different time points. Now as I mentioned earlier, also, were randomized to either switching to an IL seventeen a inhibitor or rotating to a second TNF inhibitor. And for those given or being switched or being changed to an IL seventeen inhibitor during this study, only secukinumab and execizumab were the available IL-17A inhibitors at the time of the study.

So what are the results? Well, the primary outcome was not achieved because there was really no significant, statistically significant difference between the ASAS 40 rates of the IL-seventeen A inhibitor group and the second TNF inhibitor groups. And this means that well, this means that the IL seven or changing to an IL-seventeen inhibitor was not superior compared with shifting or rotating to a second TNF inhibitor. Now how can these results help in clinical practice? I think it informs us of the options that we can give our patients and that, it also aligns with what the, current recommendations say about either switching or rotating to biologic DMARDs in our patients who fail an initial an initial treatment for axSpA.

But it's also interesting to watch out for newer data as the trial may progress or probably addition of addition of other newer IL seventeens. Follow me on x at RheumNow for more updates of the ACR twenty twenty five.

Hello. I'm Anthony Chan reporting for RheumNow here at ACR twenty twenty five in Chicago. One of the questions that we meet in a in psoriatic arthritis is head to head studies where we can compare the efficacy of biologics with each other. And this is particularly so in the area after a patient has failed TNF inhibitor. And today, there was a late breaking abstract, which is LB06, which is a study that comes from Germany which addresses this question.

In this study, they studied patients who had failed TNF, and then they were either randomized to either having secukinumab or istakinumab. So the comparison was to see whether at the end of this study whether they had improvement in their health assessment questionnaire. The HACDI score was used as their primary outcome. And also, look at other scores including joint counts. There were hundred and nineteen patients randomized equally one to one into either the sacrokinumab group or the istakinumab group.

All these patients met Casper criteria for PSA. And the mean age was around 53 years. There were some patients who were had a higher body weight of greater than hundred kilogram, roughly about a third in both groups. And the features were were then analyzed in the results section. These patients had the efficacy outcome, which is the primary outcome, which is the HAC DI.

And at the end of twenty eight weeks, the patients who were randomised to sacukinumab, fifty seven percent achieved the HACGI compared to twenty seven percent in the istakinumab group. The patients who were also in the sacrokinumab group also had better results in terms of their secondary outcomes, which were the joint counts, the pain scores, skin outcomes, and also the patient reported outcomes. These improvements were seen very early by week two and were sustained up to week twenty eight. There were no new safety signals for the secukinumab and histokinide groups other than what is known in previous studies, and these were well tolerated. What I took away from this study is three things.

Firstly, that there are differences in terms of choice of treatment in our patients, after TNF inhibitor. Secondly, these, these changes can be very beneficial and meaningful, for the patients, in both in all, the factors that, affect these patients with psoriatic arthritis. And I think this study called, again, is one of the many studies now that we will see where we can look at more head to head comparisons between biologic drugs, especially in this group of patients who may have failed some of the other earlier treatments, either conventional synthetic or biologic DMARDs. I'm Anthony Chan reporting here for RheumNow, ACR twenty twenty five.

Hi, everyone. This is Oily Naj reporting for RheumNow. I'm from Glasgow, Scotland, but I'm currently in Chicago. Day three of the conference, ACR twenty twenty five. Absolute joy.

I went to this session this morning, and it was an RA ILD session, which obviously, for me, is is is the most amazing thing because that's most of my research. So I was quite excited about that, and it was so interesting. So the same way we've been seeing so many abstracts about how do we predict who's gonna develop RA in the people at risk. There was a lot of prediction studies looking at what is what is the biomarker of ILD? How can we identify people with RA that will go into developing ILD?

And so that was quite interesting actually. And there's one in particular that caught my attention because I found the ID quite exciting. So it was a new a urine study, basically. So they did urine proteomics. They linked it with blood proteomics, but the result of the blood proteomics wasn't presented.

So it was abstract seventeen fifty. There's a few caveats here that we're gonna discuss at the end, generally a small cohort, 14 patients with RA, LLD, so that's not huge. 64 controls, RA, no ILD. It wasn't clear whether the people with that ILD had had a chest CT to verify they didn't have any form of ILD, and also the cohort was too small to get granularity in the pulmonary fibrosis patterns between UIP and NSIP and so and so on. But but what they found overall is a couple of proteins.

I could give you the name, but you will forget them the same way I did. So it's SPOCK one and PGRMC one. But these seem to be associated with fibrosis response in terms of the biology as well as cell stress response. So interestingly, these two proteins, they were elevated in people with ILD in their urine. And there was a correlation as well between the levels of the proteins, in particular one of them, and the severity of the lung disease but also when they did their multivariate analysis, they showed that it was independently associated with the risk of predicting of of developing ILD.

It was another ratio of about six, which is quite high. And so they developed a prediction model with these two proteins and then with and without clinical parameters as well, such as age, sex, duration of the disease or a seropositivity. And they were able to predict development with a round of the curve of 0.94 with a whole model, but with proteins only it was 0.9. So it was actually pretty good. It's obviously not validated in the second cohort.

So that's something we're gonna have to be looking out for because there are so many studies that show one market elevated, and then, you know, you never hear about it again. But certainly, small numbers not yet validated. The other caveats there could be the issue with urine, you know, when the it didn't seem to be particularly standardized the way they collected it. You know, depending on time of the day, there might be variations and stuff, and that was brought up during the questions. And also the function of these proteins in the ILD development pathogenesis are not really clear yet.

But certainly, if we're able to predict who's gonna develop ILD in our patients using a dipstick, that would be quite cool. So that's what I wanted to share with you today. Go online and check RheumNow for more content and follow me on Twitter orillirimo.

Hi. This is doctor Jiehao Li from Michigan reporting for RheumNow at ACO twenty twenty five in Chicago. I have the pleasure of having here with me doctor Thomas Grader Beck to talk about Shrogan and his abstract number two three zero two titled Clustering by ESPRIT and PROMISE Domain Measures to Define Distinct Subtypes and Facilitate Longitudinal Assessment of Patients with Sjogun Disease. So, Doctor. Thomas, at ECR twenty twenty five, Sjogun is finally getting the attention that is long overdue, with Sjogun being renamed from Shogun Syndrome to Shogun Diagnosis.

And I think with that comes this movement to make sure that we're actually treating our patients well, have measurable outcomes. And along with that, with towards the precision of medicine, you've done this really interesting study where you're trying to use patient reported outcome measures to understand how there are specific phenotypes or clustering. So can you tell us a little bit and walk us through what motivated you to do this study and how you came about it?

Yeah, thank you so much for inviting me. So we do have patient reported outcome measures in Sjogren's. The most important one we call ESPRIT. And the ESPRIT basically is a simple measure for dryness, fatigue, and pain on a scale from zero to 10. And kind of that represents the cardinal symptoms that Sjogren's patients experience.

But it's not the whole story. And so, we know that symptoms can have different effects on function. For some people, they may function very well. When they have high symptoms, other people cannot function. And so our idea was to incorporate measures that also measure function in the study.

And so what we did, we used the ESPIRE along with PROMISE measures, and that's another whole set of measures that can physical function, it can measure social ability to participate. So there are a number of them and then you can start to ask, you can put all these measures together and you can ask, Well, are there different subsets of patients? And do represent clinically meaningful subtypes of the patients we see normally in clinic? So that's basically what we did in this study as one objective.

I see. So for Sjogren traditionally with a very heterogeneous and an experience based symptomology and cluster, you're taking both an objective measure as well as patient experience to come at a phenotype together. And I understand with this that how you derive at the data and how you actually incorporate into methodology is very important. Can you walk us through that?

Yeah, so traditionally, often this kind of research is done separate from the clinic care that you give to patients. The method that we have developed, we actually incorporated those measures directly in the clinic when we see the patients. We give everyone questionnaires that are representing the disease and the kind of symptoms that they have, and then they get a tablet and they answer the questions just before they see us, and that, immediately flows on the back end into our whole registry database. And so we're very closely related between where we collect the data and seeing the patient and it's not separately. And that is very valuable because it gives you this connection to the moment and you can verify that you're really measuring what you think you measure.

Absolutely, and I can also imagine it also allows you to see how treatment may have changed in the future potentially and associate that. But coming back to the clustering, were there certain subsets of patients that were quite distinct and different from each other?

Yeah, absolutely. So what we found in a nutshell is we have two extremes, which is what we see clinically. There are patients that are, when you look at their blood work, you look at some of the numbers that say how active they are, they're really high, but they function very well. They come to the visit and they say, I'm feeling fine, and you look at their numbers and you're worried about them, but there's nothing really that needs necessarily to be treated. On the other end, there are patients that cannot function at all, they have very high symptoms, and so those are the extremes.

But in the middle we find, interestingly, one cluster, people can have quite severe symptoms, but they're still functioning quite well, and another cluster where they actually don't have as severe symptoms, but they cannot function. And that really also highlights that the esprit that I talked about earlier cannot really necessarily capture the effect that Sjogren's has on how people live their everyday life. So there are other factors, and we're hoping that this kind of method will help us to identify better what other factors may be so we can overall improve measuring what the patient feels like and how they function in their life.

And were there any distinct patient characteristics, for example, age, gender, race, allowed you to predict between the different classes? And if somebody was on one extreme, are they likely to stay in that extreme class throughout their disease course?

Yeah. So to your second question first, I think that was the other objective in our study was to really figure out if patients are in a cluster, do they stay in that cluster over time or does it randomly go back and forth? Our hypothesis was from the clinical observation that patients usually stay in their cluster. In fact, that's what we show over time. Now, this doesn't measure potentially effects of treatments and how they could maybe change clusters according to that, but the clusters themselves are very stable.

So we started to look into what other markers may be associated with those different clusters and that work is still early on in development, but I would say the early results confirm that patients that seem to be more immunologically active don't necessarily suffer as much from functional consequence or symptoms than the other extreme. Age wise and the typical distribution that we look for, gender and so forth, There doesn't seem to be much of a difference.

I see. In terms of that stability though, going back to your earlier point about the infrastructure and the robustness of the data, I think you actually showed it was over a three to four year period with a quite impressive number of sample size and the degree of granularity of data that you have that really attests to the fact that this is a good baseline to be used in clinical future, is that right?

Yes, I would think so. I mean, we have been collecting this kind of data with the help of our patients also for over ten years. So I think that gives it strength for us to really think that this is something valuable and real. But again, it is something preliminary that we want to work on further and refine further.

Absolutely. Since you said this is preliminary and there's more road to be achieved here towards that precision goal, what do you think is the potential or hopeful clinical application, the next steps for your project?

Yeah, so if we assume that patients stay in the same cluster they are, the question of course occurs like what happens if they have a flare? Do they still stay in that same cluster or are these patient reported outcomes valuable in indicating when someone leaves that cluster? And if that is the case, then we have some more quantitative measurement if we should probe a patient's state at the point where they have a flare. So for example, asking the patient to fill out these PROs, but collecting blood samples, doing other tests and see if we can find reasons for their flare. Because about fifty percent of patients with Sjogren's, they will flare but not in a way that we can measure, like their lung function doesn't change or their joints don't change.

It's like they have this fatigue, dryness and some other symptoms. And we have a very hard time really assessing and measuring that. So if we can use those PROs to help identify the state, then we have a chance of better identifying the mechanisms behind that.

I see. So you're really taking the whole patient experience, symptomology, to take into account what their disease state is to see how you can make an improvement forward.

Exactly, that's our goal.

Okay, well thank you for that. And again, this was Jihye Lee for RheumNow, talking about using patient reported outcome measures towards precision medicine for Sjogren's disease. Thank you. Hello,

this is Atul Devdar from Portland, Oregon. Has it ever occurred to you that why do patients stay in long term clinical trials like three years, four years, five years, even when they have not received the minimal outcome? Case in point, in axial spondyloarthritis, as DAS inactive disease or as DAS low disease activity is a good endpoint for the patients to be. Why would patients stay in a clinical trial after three years if they have not even received as DAS low disease activity and they're still at the end of three years in high disease activity? And we generally don't think about it.

Case in point here is there is an abstract here two, three, four, seven, where bimekizumab patients stayed in clinical trial of axial spondyloarthritis. There were two phase three studies done. These are pooled results. And eighty percent of the patients in that clinical trial at the end of three years were in ASDAS, low disease activity, which means twenty percent of the patients were in high disease activity. And you think why were these patients even they stayed?

And there was this abstract number two, three, four, seven poster which actually had heat maps. Heat maps is a great way of showing what happens to individual patient over time. In the heat map, if it is a green line, that means the patient is in low disease activity or inactive disease. If it is orange, it is high disease activity and red would be very high disease activity. If you look at the figure, you will find out that patients who at the end of three years were in high disease activity.

But if you look back, they were in low disease activity before. And that brings an important point that just cutting the data at one particular time point, say three years, doesn't really give you the full picture. You need to see what happened to the patient over entire three year period. And the heat map is the only heat map is the only way you can get that those data. A couple of other points I want to make here is if we really follow treat to target.

Treat to target means that you see the patient and the patient is not doing so well, you have to change the therapy. Here, these patients did intermittently very well and then intermittently had flares. If trick to target was applied on every time they did badly, they would have changed the therapy, which really was not essential. Another point that comes out of this is that maybe the outcome measures that we have for axial spondyloarthritis are not really measuring why the patient stays into clinical trial. There is something that is making them happy.

One of those things could be that compared to what they were at baseline, they are so much better now. Even though they were high disease activity, were in very high disease activity, and their Asthma has dropped. So it made me think that if somebody is not doing so well at one particular time point, it doesn't necessarily tell you that the therapy has failed. That could be a blip in their long journey. All our diseases are chronic, and there is something else that we are not really measuring in our measurements, that is missing, which actually, in fact, makes the patient stay into the clinical trials.

Hi. Welcome. I'm doctor Janet Pope reporting AtRoomNow. This is ACR twenty twenty five coming live from Chicago. I wanted to talk about IgG four, rare but treatable and now even more treatable.

I'm gonna talk about several abstracts, late breaking o two poster, abstract zero two three nine, abstract one one six three, and one one seven two. So first of all, there were some criteria that have come out, before for IgG four, and there are also onco measurements that have been developed and, ongoing presentations in those areas have been done. However, there's some neat stuff. So first of all, new kids on the block, not approved yet, not ready for prime time, are BTK inhibitors. So there were two studies, rizabrutinib and zanubrutinib, both BTK inhibitors, looking at some success, early on in I g g four.

We need some more RCT data to really help enhance that. We already know about the, ianabilizumab, which is a c d 19 monoclonal antibody, positive RCT, recent publication and, obviously, the journal on how exciting it was. And there was a subset analysis presented by John Stone and others saying that, basically, this c d 19, deep monoclonal antibody, basically decreased FLAIR. So already positive data and some secondary looks. The new kid on the block, though, is a JAK inhibitor.

So this was a single site study. This was the late breaking abstract two poster, and it was an RCT of a decent size in this rare disease, 58 people. And they randomized patients to tofacitinib plus glucocorticoids or glucocorticoids alone. They found several things of interest. So they found a better response on JAK inhibition.

They found everybody on JAK inhibitor plus glucocorticoids reduced the IgG four, not as consistent if you were on glucocorticoids alone. And importantly, for me as a treating physician, there were less relapses. So what are we gonna do with all these data? We're soon gonna have, more drugs than we have treatment, patients in our practice with IgG four, but I think that's a good, dilemma to be in. More will come.

Follow me, please, at Janet Burdope. Thank you.