A Conversation on Changing Trends in Advanced RCC Treatment: An Analysis of Real-World Data - Neil Shah
July 6, 2023
Neil Shah, MBBS, Medical Oncologist, Assistant Attending Physician, Memorial Sloan Kettering Cancer Center, New York City, NY
Pedro C. Barata, MD, MSc, Leader of the Clinical GU Medical Oncology Research Program, University Hospitals Seidman Cancer Center, Associate Professor of Medicine, Case Western University, Cleveland, OH
IKCS 2022: Real-world Clinical Outcomes of Patients with Metastatic Renal Cell Carcinoma Receiving Pembrolizumab + Axitinib vs Ipilimumab + Nivolumab
ASCO GU 2022: Real-World Assessment of Changing Treatment Patterns and Sequence for Patients With Metastatic RCC in the First-Line Setting
Pedro Barata: Hi there and welcome. My name is Pedro Barata. I'm a GU medical oncologist at Case Western University, Seidman Cancer Center in Cleveland, Ohio. And my true pleasure to be joined today by Dr. Neil Shah. Dr. Shah is a medical oncologist and assistant attending at the Memorial Sloan Kettering in New York. Welcome, Dr. Shah. Thank you for joining us today.
Neil Shah: Thank you, Dr. Barata. Thank you for your kind introduction, and happy to be here.
Pedro Barata: Absolutely. And by the way, I saw with interest, your presentations that you got at KCA, also at ASCO, very elegant work that you're doing. And today, we'll be talking specifically about your work regarding clinical outcomes for patients with advanced RCC.
As far as I know, you had two or many, but you had two studies addressing that topic. One is titled Real-World Clinical Outcomes of Patients with Metastatic Renal Cell Carcinoma receiving axi/pembro versus ipi/nivo. And the other one, titled, A Real-World Assessment of Changing Treatment Patterns and Sequence for Patients with Metastatic RCC in the first-line setting.
So I thought it would be a good idea for us just to chat a little bit about those two studies. I mean they are different, but they are kind of connected, in my opinion, and it's actually neat that we have you here to comment on that. So maybe I'll start here, because it's a big effort, over 1,500 patients on that dataset, and maybe is an opportunity for us to chat. I mean how are you able to access that database? Tell us a little bit about how the study was born, and how you felt it was important to report real-world data for the treating physicians and treating healthcare teams out there.
Neil Shah: So thank you so much. I think the big question for the field is that, we have a lot of new regimens approved in kidney cancer space, like five in last few years, and how to choose one versus another? Correct? And I think the study is not asking how to do here. This study is asking, okay, what people are doing? Correct? What is the real-world setting? So what we did is, we want to understand that what is happening in community setting? So we looked at the data from US Oncology, US Oncology McKesson database, where they have over 1400 providers across like 400 or 500 sites in US, and we access that EHR. They have really nice data system, where they are able to use the EHR to look at the data. So that's how it started.
Really, we want to understand what's happening out there in community setting, and people using these newer medications, if they're using it, what line they are using it?
The other questions what we have is that okay, we have this huge amount of push of this new medication in first-line setting. How does that influence what you do in second-line setting? What you do in third-line setting? Correct? What are the sequence and patterns, are they changing? Correct? If you start with TKI monotherapy, versus IO/IO, versus IO/TKI, what happens in second-line? A lot of these data is unknown. We don't have even good clinical trials in the second-line and more space. So that was another question, we wanted to just understand what's happening out there, what people are using, and what's their outcome? So that's how we decided to do this study. This study was sponsored by Merck, so Merck funded data access from a case and database, and data analysis, but we independently did the data analysis, and then wrote the manuscript.
Pedro Barata: That's great. Thank you for that. I mean fantastic effort, and I'm really happy that the data is out there. So actually, let me just go there. Because when I was going through the data that you presented, it's interesting to me and it's, by the way, I should say, correct me if I'm wrong, I think it's contemporary data from 2018, if I'm not mistaken. And it's interesting, because we do see a good deal of patients still being offered TKI monotherapy, and then of course, you got patients there treated with ipi/nivo, and also a lot of patients treated with axi/pembro. Can you walk us through what has been, what were your findings as far as treatment patterns in the front-line setting? And then, I'll ask you in a little bit what is going on upon progression.
Neil Shah: So I think that's exactly what we wanted to understand. Correct? Are people using TKI monotherapy? If so, how many percentage, and what's happening in other therapy? And this study is also a little bit old, because real-world data takes time to measure. Correct? Once it gets FDA approved, then it takes few months for people to understand, read the data, and start using it.
So goal was that, this study we planned in 2020, just before COVID pandemic, and at that time, ipi/nivo, and axi/pembro were approved, and lenva/pembro and cabo/nivo were in trials. In our data, they looked very positive. So that's why this study only focused on two regiments, ipi/nivo one, axi/pembro. We also evaluated axitinib and avelumab. But again, the numbers were very low. That's why we excluded from the analysis. When patients numbers are in single digit number, that's why we did not include it that.
So if you look at our abstract, it was really nice to see, we started from first quarter of 2018, until September of 2020. And then, so we had enough follow up so we can actually make some sense of clinical outcomes data. So when we look at first quarter of 2020, 60% or not of 50% were treated with TKI monotherapy. In second quarter, you start nicely seeing patients start using ipi/nivo, and that graph going up, TKI and monotherapy graph going down. And then in 2019 second quarter, you start seeing nicely IO/TKI, axi/pembro graph going up.
So at the end of our evaluation, we noted that at the end of 2020, majority of patients were actually getting IO/IO or IO/TKI. There was only subset of patients, I believe less than 20% of patients, were getting TKI monotherapy. And this was really very assuring. Correct? New people in community setting are using these newer agents, and we still know that there is some space for TKI monotherapy. Correct? If a lot of autoimmune disease or for various reasons. So I think, that was really reassuring, finding what we noted the nice trend of IO/IO or IO/TKI going up, and TKI monotherapy going down.
Pedro Barata: Great. That's a great summary, and that's exactly what my sense from talking to our colleagues in the community has been, and clearly, you're showing that. And I guess I'll take your words in a word in a way that, if we were to do the study again today, the picture that we would see today in 2022, will definitely be different from what we saw in '21. Definitely different from what you reported in 2020 and 2019. Which is, it speaks volumes about the pace of change that we're seeing. Right? And that's good problems for patients.
So let me switch gears here a little bit, because as we are offering different IO based combos more than ever in the front-line space, that's definitely impacted the way we treat patients upon progression, knowing that unfortunately, we are not able to achieve durable remissions in most of them. So with that said, can you tell us a little bit about what your data set showed you and taught us about what is going on upon progression? What are the treatment patterns out there that one should be aware of?
Neil Shah: So again, as you say that, unfortunately, it's still some subset of patient who do very well for long time, and majority patient does require second-line or more treatment. And then we just wanted to understand what is happening. So in our dataset, what we noted that if you start IO/IO or IO/TKI, the most common second-line regimen was cabozantinib. Over 50% of patients in both cohort received cabozantinib as second-line therapy. For IO/TKI cohort, ipi/nivo was common second-line therapy after cabozantinib. For IO/IO ipi/nivo cohort after cabozantinib ended up the common second-line therapy was pazopanib. And we also saw like IO/TKI axi/pembro in second-line setting also for some of these patients who are treated with IO/IO in first-line setting. And in TKI monotherapy cohort, the most common second-line treatment was nivolumab monotherapy, followed by ipi/nivo, and cabo was in a subset of patient. So this was a pattern we noted. And then in third-line setting, again, cabozantinib was the most common third-line drug, and we started seeing lenvatinib plus everolimus exiting of monotherapy in third-line setting.
Pedro Barata: Got it. So that's not quite surprising. I would say, probably the amount of the rate of patients getting a CTLA-4 not in front-line, is to some extent, not as high as I would predict. I don't know if you agree with that, but interesting findings indeed.
Let me ask you, because we're getting close to the end, and I know you're busy, but I want to pick your brain on something. So first of all, tell us if, when are we going to see this data published? Because I personally think this is very, very important data for us to be using in moving forward, to run trials, to design clinical trials, because we need to understand what the practices of treating physicians is in reality. And there's a couple of surprises. I mean, I'm highlighting the CTLA-4 with ipi in the post first-line, as something that caught my eye. So here's the opportunity for me to ask you. Do you have any other points that were perhaps surprising to you? And tell us a little bit of update on the publication of this work.
Neil Shah: So no, thank you so much. I think it was surprising. Correct? Ipi/nivo we are seeing in second-line settings. Axi/pembro you're seeing in second-line setting. And right now, we have currently ongoing trials. Correct? Like with IO/TKI in second-line setting. But it's really important to understand sequencing of this medication. We have a lot of data that CTLA-4 plus PD-1 combination in second-line and beyond setting is not as effective as in first-line setting. And to see people are using that in second and third-line setting, it's interesting to see. And again, there are many factors, influences, that what happened in first-line settings. Sometimes that depends on second-line setting. So I think that was interesting. And again, as you've mentioned, like cabozantinib, most common second-line setting, it's not surprising. We talk with many of our colleagues, so it was reassuring that that is a common standard practice.
I think your second question regarding the manuscript. So actually, our manuscript has been submitted to one of the European Urology journals, and it's under processing, it's under reviewer's comments and we already replied back. So we'll be seeing publications soon of this data.
Pedro Barata: Wow, that's a fantastic journal, and I think it's really fair, and I'm happy to hear the status of that. I'm happy to hear that. Listen, Dr. Shah, before I let you go, any final thoughts about your work you'd like to highlight?
Neil Shah: I think one of the key things for me and my message here is also, I think real-world data is important. Real-world data, it's not replacement clinical trial data. Clinical trial data is the gold standard data and we need clinical trials data. But I think, we can learn a lot from real-world data. There is no inclusion exclusion criteria. We have patients with poor performance data, we have elderly patients, we have patients with different comorbidity, which may not be eligible for a clinical trial. So I am true believer of understanding good real-world data. Now, real-world data is most of the time retrospective, and come with lot of confounding biases. So I think whenever anybody's doing analysis, or doing real-world study, really, they have to be very, I would say, strict about what to make sense, what not to make sense, and understand what are the factors influence this kind of data? But I do feel like, especially with the changing treatment landscape, this data becomes important. Yeah.
Pedro Barata: For sure. Listen, this was a pleasure. Big congratulations on your work. I'm looking forward to reading the paper. I'm happy to know this is going to come out soon. And I'm pretty sure we're going to be talking soon about kidney cancer. So thank you for taking the time and joining us today.
Neil Shah: Thank you so much, Dr. Barata, I really appreciate your time. Thank you. Bye-bye.
Pedro Barata: Thanks.