Charles (Chas) Peyton: Well, thanks so much for having me, and thanks to UroToday for sponsoring this, and Dr. Chang and everyone. All right, thanks so much for the invitation to present on this topic. This is patient reported outcomes following UGN-102 in the treatment of low-grade intermediate-risk non-muscle-invasive bladder cancer. Looking at three different clinical trials, here's your citation. Just a word of disclosure. I did previously serve as a consultant for UroGen, the producer of UGN-102. However, all this work was done separately, I was an independent reviewer and not compensated for any of this work.
We'll go over some introduction objectives, some methods, results, discussion, and conclusion. As way of introduction here, recurrent low-grade intermediate-risk non-muscle-invasive invasive bladder cancer is frequently managed with either repeat trans urethral resections, office cautery, and surveillance for some patients. But for patients who have the frequent recurrent high volume disease or refused surveillance or can't tolerate office cautery, there is some morbidity related to TURBTs that are reported.
I've got the citation down there below. Max Kates and some colleagues from Hopkins actually did a nice job of reviewing this recently and showing that we probably under-report a little bit of the morbidity associated with repeat TURBTs. I don't think that's something we should ignore. Office cauteries with small low-volume disease is certainly reasonable in a lot of these patients, so is surveillance in some of these patients. But occasionally you do get patients that have repeat high-volume, high frequency disease that is all low-grade, but needs maybe an alternative treatment.
UGN-102 is an intravesical solution. It's a reverse thermal hydrogel formation of mitomycin. It was recently FDA approved, specifically for this, for their chemoablative effects of low-grade intramurous non-muscle-invasive bladder cancer. The objective here is to take all the patient reported outcomes data from the three trials describing the use of this medication, and review specifically the patient reported outcomes, not necessarily efficacy. We've seen all that data come out. This is specific to patient reported outcomes. How much do patients have worse, better, improved symptoms related to this medicine and treatment?
Here's the design and outcomes. We collected patient reported outcomes data for UGN-102 patients instilled once weekly for the six weeks that it is instilled. And did this over the course of three trials, the OPTIMA II, ATLAS, and ENVISION trial. Validated patient reported outcome questionnaires were included, including the QLQ and NMIBC24, which is non-muscle-invasive. It's bladder cancer-specific. And we also did the QLQ-C30, which is specific to the ENVISION trial. And that's a overall cancer-specific symptoms and global functioning quality of life type of questionnaire.
And work done previous to this, we did something really important called calculating the minimally clinically important differences. Whenever you have a patient reported outcome or a questionnaire, it's pretty easy to take two different questionnaires or different dime points and possibly prove that they're statistically different in terms of the numbers of the questionnaire at this time point versus this time. But that's really not as meaningful as actually proving that the questionnaire answers are different in terms of what range of changes of the questionnaire answers actually reflect the clinical change. Not just the numbers, meaning the global numbers.
We're familiar with [Inaudible] scores and those sorts of things. And we know that it's not just a one point difference that actually signifies a clinical change, it's a higher than that. We did prior work to calculate the MCIDs, which is the minimally clinically important difference of this score that actually is meaningful between those two. And we looked at those. These were collected again each time we did a treatment at the baseline, of course, and then during each weeks that they got the treatments. And then at each month in follow-up at three months, six, nine, 12, and so forth.
You'll notice that the OPTIMA scores were not collected as frequently. That study was a little bit challenged by being in the midst of COVID, and various other things going on, so the data is a little bit more sparse with some of that data. Anyway, the baseline characteristics are listed here. Demographics are generally similar. There's a high proportion of patients in the ATLAS study with greater than three centimeter tumors. And the proportion of patients with recurrent low-grade intermediaries, non-muscle-invasive bladder cancer that undergone prior TURBT differed a little bit between folks, between studies. And then the completion rates were over 90% for ATLAS and ENVISION. Like I said, OPTIMA was less high. And you can see the numbers of the completion rates up top. 240 for ENVISION, 138 for ATLAS, and 63 for OPTIMA in terms of the completion of the patient reported outcomes.
And here's the results. Baseline NMIBC24 scores. The way these scores work are important, meaning that lower scores is perceived in lower symptom burden, whereas higher score represent worse symptom burden on all scales for the NMIBC24. For the ATLAS study, the clinical and meaningful improvements in urinary symptoms, other than urinary symptoms, including malaise, future worries, bloating, flatulence, that sort of stuff, were initiated and mostly maintained throughout follow-up. And there was really no clinically worsening of those scores at any point. In terms of OPTIMA and ENVISION, there was no clinically meaningful change from baseline. CFB means change for baseline for urinary symptom scores at any point.
You can see here in the graphs below the OPTIMA score, if you look within the dotted lines, that is the minimally clinically important different range. If you stay within that range, we pretty much think that the change in any score that we see doesn't necessarily equate to a difference in clinical meaningfulness. That's pretty stable here with OPTIMA. And the ATLAS, you see lower scores are better. That goes up a little bit during treatment, and then this is changed from baseline. Overall, it got better, but only -1.4 at the end of the treatment period. And then, actually improves in follow-up. And same with the EVISION study, which is highest volume.
During treatment, a little bit of worsening and then improves our baseline in follow-up. And really, what you can say about this graph here is there's no clinical meaningful change because everything's within the two dotted blue lines. With the ATLAS study, you see some improvement actually. And then, if you look at the QLQ-C30, which again, which is global symptoms functioning, this is the opposite. The higher the score represents better functioning. It's the opposite of what I was just telling you. You can see here that they maintain throughout, there's no real big changes. In fact, in the follow-up, it's maybe a little bit better, but again, the dotted lines are what's the MCID threshold, so no real changes.
And then, if you bust this up by patients that had what we call a adverse event, a treatment-related adverse event, and you look at treatment around that adverse event, there's no adverse event. And you look at the differences, there wasn't too many changes. But what's bold would be outside of that clinically meaningful change. You're seeing what you would expect. People who had adverse events didn't have significant improvement. Remember, a minus is improvement here. People with no TA did have improvement. And then afterwards, it really was improvement across the board. Whereas, in ENVISION they maintained stable in both groups, whether or not you had a treatment-related AE. And again, that'd be worsening urinary frequency, urgency, and urinary symptoms.
In the discussion part, they had pretty much a meaningful, favorable outcome in comparison to baseline scores. We had improvement in select domains, urinary symptoms, and future worries. Particularly in the ATLAS study, like I showed you. The transient worsening, a patient received urinary symptoms associated with urinary T adverse events resolved by about three months, which supports that there's some tolerability to this. And the other thing you have to know that there's cross-trial heterogeneity here, and there's a limited comparator. All these studies were single arm. The ATLAS study did have a comparator arm, but that data was not included, the TURBT only arm. We didn't have enough to actually appropriately compare between the two of them. But that's obviously a major criticism here, which we'd like to see in the future.
And again, there's some incomplete pro data on some of the studies, particularly with the OPTIMA study there's some COVID disruptions. And this is basically observational data. But I think you can conclude from this that across all three late phase trials, UGN-102 didn't necessarily worsen quality of life functioning or symptom burden. People were similar. The pro data would suggest that there's maintained or improved compared with baseline, with notable improvements in urinary symptoms for some folks. There was some transient worsening of symptoms, particularly with those who had worsening symptoms during treatment that all resolved by three months. And I think overall, this data would support that the UGN-102 is reasonably well-tolerated and may be a non-surgical option for some of these patients.
Sam Chang: Chas, that was great. I think a couple questions to ask you during the treatment phase. Clearly, overall, it doesn't seem at the end of the treatment that there's a big deviation or change from baseline to CFB. During the treatments, I noticed that each of the curves did rise in terms of symptomatology. But if it's within that dotted range, then you would say it's not clinically significant, is that correct?
Charles (Chas) Peyton: Right. Anytime you do a patient-reported outcome study, like I said, it's easy to take two time points and compare the numbers and make, oh, yeah, statistically difference, but that doesn't really matter. What matters more is, what is the magnitude of change reflecting an actual clinical difference? And what I didn't show you in this data is prior work where we actually were able to calculate that in MCID based on... And there's two different ways to do it. There's an anchor-based approach where you have something else that already exists and you anchor that to, and then there's a statistical method to do it. And that's more of the way it was done in here because all those quality of life questionnaires are not specific for non-muscle-invasive. We've got further another analysis coming out showing that data that I just described on how we came up with that number.
Sam Chang: And so, even more telling HR, but even more telling then perhaps then is the... I can't remember if it was the ENVISION or the ATLAS that actually showed then after the treatment cycle the symptoms improved. Implying, at least, that the successful treatment... And I know you don't know that the success data within that, the cohort of patients that improved or didn't improve and their symptomatology. But overall, the symptoms improved after treatment. At least, implying that there were some issues, some whatever bleed and whatever maybe tumor associated actually improved over time. Is that-
Charles (Chas) Peyton: That's right.-
Sam Chang: ... that study? That was a smaller study, I know.
Charles (Chas) Peyton: Right. The ATLAS did show improvement after completing treatment, whereas the ENVISION study just showed maintenance, no difference. The ENVISION study has more patients, a little bit more data. The ATLAS study has a little bit fewer data. The ATLAS study was cut short, like we all remember for various reasons. But it would've been nice if we'd had been able to finish the ATLAS study and then had the comparator arm that was worthwhile with TURBT only, but we weren't able to do that.
Sam Chang: Chas, how do you use this data when you counsel patients with, at least, considering not taking them to the operating room? Some patients you really need to in terms of bulk, et cetera. Or some you really don't want to do anything at all because it's a tiny recurrence and you do surveillance, et cetera. But in those that you're considering a chemoablation, not going in the operating room, but treating, how do you use this data to help counsel patients?
Charles (Chas) Peyton: Right. I think you can simply tell them that the quality of life data would be suggested that they would be perhaps better, no worse, obviously, with this medicine in terms of their symptoms. I think patients worry about that. I wish we had the same sort of thing in the BCG world, but we don't. But I think patients worry about that. Particularly, you're talking about someone who doesn't want to go to the operating room necessarily, so they may be more fixated on that quality of life symptomatology component more than someone who wasn't. That's the group that you're talking to. I think this data supports that you can tell folks that, "Hey, I think the quality of life data would be supportive that you'll be no worse with this comparatively."
Sam Chang: Chas, thanks so much for your wisdom and your research. Where are we going to go next? You mentioned that you had already published, obviously, rationale behind the clinical impact and the impact. Where do you go next?
Charles (Chas) Peyton: Yeah, we just put out another paper looking at the psychometric validation of this and how we came up with those numbers. Now, it's really a tricky statistic. We need a lot of support and help to do that, because it's something that you and I don't think about every day on how to calculate these numbers, but there's actually a real science to it. That was recently published online, and it's the psychometric validation of low-grade intermediate-risk non-muscle-invasive bladder cancer for these questionnaires. And that would be the first time that's published in low-grade intermediate-risk non-muscle-invasive bladder cancer, because also-
Sam Chang: I think they'll be increasingly important as we consider other treatment options that may become available, either as ablative or adjuvant, those types of things to help determine. And now with a validated questionnaire and setup that you've confirmed here, this is actually what's impactful versus not.
Charles (Chas) Peyton: Yeah, for the long run.
Sam Chang: Yeah, will be increasingly important. Thank you. Thank you again, and looking forward to your future presentations and your work. And really appreciate your time, Chas. You're the best.
Charles (Chas) Peyton: Thanks so much. Thanks, Sam. Thanks, UroToday for having me. I appreciate it.