Journal of Clinical Oncology (JCO) Podcast

Host Dr. Davide Soldato and guests Dr. Suzanne George and Liz Salmi discuss their JCO article "Overcoming Systemic Barriers to Make Patient-Partnered Research a Reality" TRANSCRIPT TO COME Dr. Davide Soldato: Hello and welcome to JCO’s After Hours, the podcast where we sit down with authors from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato, Medical Oncologist at Ospedale San Martino in Genoa, Italy. Today, we are joined by JCO authors Liz Salmi, Researcher and Patient Advocate, and by Dr. Suzanne George, who works as a Medical Oncologist at the Dana-Farber Cancer Institute where she acts as the Chief of the Division of Sarcoma. She is also Associate Professor of Medicine at Harvard Medical School. Today, we are going to discuss with Suzanne and with Liz the article titled, “Overcoming Systemic Barriers to Make Patient-Partnered Research a Reality.” So thank you for speaking with us, Suzanne, Liz. Liz Salmi: Thanks for having us. Dr. Suzanne George: Yes, thanks. Dr. Davide Soldato: I just want to make a brief introduction because I think that the concept of patient partner research is very wide and I'm not sure that all of the readers of JCO really have a deep understanding because I imagine that there are a lot of ways we can involve patient and patient advocates in the research process. And so I was wondering if you could give us a little bit of an introduction about the concept. Dr. Suzanne George: Sure. I think the point that you raise is really important because there are many terms that are used, patient-partnered research, patient advocacy, but I don't think that there's a single definition as to what that actually means. In the context of our work, we’ve sort of summarized our experience through something called the PE-CGS or the Participant Engagement and Cancer Genome Sequencing network. And in that project, which is a Moonshot funded network, the intention is to have participants in research be true partners working with traditional academic research teams in order to develop networks specifically focused on cancer genomics. So what we've done, every center is a little bit different in the network, but we're really having research participants not just act, but really work on the research team from the beginning of the project inception all the way through the research project. Liz Salmi: What brings me to the PE-CGS network is my 17 years experience as a person living with a low grade glioma, brain tumor or brain cancer and involving patients in the co-design of research is super critical because patients bring unique lived experiences that can shape research questions, study designs and outcome measures in ways researchers might not anticipate. And we're finding this through our network. So through my work, including my patient experience and brain tumor focused study designs, I've seen firsthand that patient insights can drive more practical implementations that ultimately benefit both patients and the researchers. And so the particular project I work on in the network, we've got like five different arms and different groups of cancer types that are being represented, so I'm basically focusing on the OPTIMUM study around how brain tumor patients can help in this study design. So in this project I serve as not just a participant in the research, but also as a patient co-investigator. Dr. Davide Soldato: That is very interesting. And I think that we really captured the essence of patient-partnered research by having both of you here talking with us about the PE-CGS. And the second question that I wanted to ask is: I really think that the network focuses on something that is quite important right now and currently in medical oncology - so cancer genome sequencing, access to novel therapies - and I think that it's really challenging to imagine a way in which we can really get our patient and get patient advocates to help us designing new trials who are looking into this. And I just wanted to know, do you think that there is something that is particularly challenging when we are speaking specifically about cancer genomics and access to this type of drugs that are targeting specific molecular alteration? Because I think that in general it might be a little bit easier, maybe I'm biased on this, so you can also tell me if I'm wrong, but I think that it's a little bit easier when we are trying to design, for example, behavioral intervention or things that are more commonly found in oncology and a little bit more complicated when we are speaking about genomics. Dr. Suzanne George: So I think that's part of what this network is trying to address, which is really what are the barriers and the opportunities around cancer genomics from the patient perspective and how do we make sure that that perspective is included as we're thinking about study design and inclusion? As Liz mentioned, this network has five different networks within the network, five different centers, and each center is slightly different with the population that it engages with. And so there's diversity there in terms of reaching out to different patient communities and partner communities around potential barriers for genomics research. I think one of the things though that we're finding across the network is that people want to be part of this work. People that have a lived experience of cancer want to help move the field forward. And what we ended up writing about was some of the barriers that get in the way of that. It's awesome to have people like Liz that are like all in and then there's people who are on the other end of the spectrum that want to share their information to help move the field forward around genomics, but then there's all these barriers at the systems level that get in the way of that. So I think that that's one of the challenges we're trying to overcome and learn about across the network. Liz Salmi: Yeah, I think I bring this really interesting, I can't say I'm really interesting, but I think I bring this really niche perspective. Not only am I a person living with a brain tumor and I'm a co-investigator but also like a participant in this study. I also, in my day job, I'm an investigator as part of the director of communications and patient initiatives on the OpenNotes lab at Beth Israel Deaconess Medical Center. And our lab really focuses on how open, transparent communication between doctors and patients improves care. And that's been going on for longer than I've been around on our team. But what I bring to that lab is I focus on engaging both patients and clinicians in spreading the awareness about the power of how easy access and transparent communication, access to information across healthcare settings helps patients feel more involved and informed in their care.   And I work specifically, it's a really niche area. I work on projects that aim to expand access to notes and test results in diverse care settings, really helping tailoring initiatives so that various patient communities can understand how they can be involved in these types of research projects. Ultimately that's what brought me into this space. I might be one of the first generation of patients that actually starts helping co-design studies on things like this. And I think that across a lot of healthcare settings cancer is really what we're focused on. But patients are now increasingly being involved as research collaborators. And there's many different funding institutions such as the NCI but also PCORI they now mandate that funders reflect a shift towards more patient centered research frameworks. So it's like the PE-CGS network isn't the only group that's being funded to do research in this way. And I think other investigators, even outside of the cancer space, but specifically in cancer, need to learn how to do research in this way. Dr. Suzanne George: Yeah, I agree. And I think the other thing that we need to do is if people want to participate and that participation in many of these networks has to do with record sharing and data sharing, the system needs to accommodate that. If people want to share their information in order to allow research to be performed, then we need to make sure that that can happen, and that it's not that the institution systems don't connect with someone else's systems or that you to pay X, Y and Z dollars for the data to go A, B and C, or that some places are on this EHR and some places are on that EHR and so, sure, you can share it, but you have to go through all of these hurdles in order to make it happen. When a patient signs a consent form that says, “I want my data to be used,” we as an investigator community, we owe it to that patient to make sure that their information is being part of the data set that will be used for learnings. And that's part of what we wrote about, is the lots of behind the scenes things that just get in the way and that we need to work towards improving. Liz Salmi: Both Suzanne and I are really passionate about this stuff. And as a person living with a brain tumor for the last 17 years, I'm a chronic research participant. I always, always, am really curious. I'm like, “Yes, let me contribute my data. Whether that's electronic health record data or maybe I'm being interviewed about certain aspects of the cancer care experience.” And the one thing that bummed me out for like the first 10 years of being this chronic research participant is I would enroll in things, I'd be interviewed for things, I'd fill out these surveys and then I never heard anything about what happened with that information and that time I spent. And people would send me like a $10 gift card to Amazon, like, “Thanks for participating,” but really what I wanted to know is like, did you do anything with that? How did that inform things? So that really annoyed me to the point where I was like, I'm just going to be part of the research process and really figure out how we share that information back to everybody who had spent so much time. And so my participation in this space is like, “Let's change it. Let's give people information back.” And now I know it takes a really long time to have a finding that could be published somewhere that we then get it back. But closing the loop on the communications gap is something I'm really passionate about. Dr. Davide Soldato: Do you think that we are changing a little bit this perspective? I feel like we are getting a little bit better in creating patient communities of patients who are included in specific clinical trials. And then we do the effort of creating a community, of keeping people really involved with the research that they are participating in. I think that we are not quite there yet, but I think that we are making some kind of steps in that direction. For example, trying also to inform patients to participate in the study when the publication that is related to that specific study comes out. What is the benefit? What have we discovered? I think that we are not quite there yet. There is a lot of room for improvement, particularly in the way I think we communicate these to patients who participated in research. But I have the impression that we are making some steps forward. So I don't know. Do you share the same thoughts? Liz Salmi: So Dr. George talked about the PE-CGS network and then there's five different cancer types being studied. So the thing I can reflect on is what we've done in the, this is a really long acronym but, Optimizing Molecular Characterization of Low Grade Glioma. Say that 10 times fast. So our particular group is people who donate tissues about their brain tumors. We're really collecting data from people with multiple brain surgeries over time, which is really complicated and to make that process easier. And then once those tissue samples are stored somewhere, studying that information about what changes in the brain tumors over time and then also giving those results back to people so they can take that research level data and bring it back to their neuro oncology team and say, “Hey. Here's what I found out, “and having a conversation. So, this is a long multi touch point study and in order to do that, to even make that possible is the individual patients need to understand what's in it for them. They're donating precious tissue in order to make the research process work. And so in order to do that, it's not just the investigators saying, “Hey. Give us your brain tissue, peace out.” It is we have a whole research advisory council of people living with these particular tumor types who help us co-design how do we do that outreach, how do we explain why this is important, or how do we message the importance of this work so they understand,“Oh, this is what's in it for me and this is what's in it for other people like me.” And from there then with that process, which again I mentioned, all of these multi-step processes, once we're able to understand how patients want to hear that information, what's in it for them, then we bring it back to like those bench scientists, investigators going, “Okay. And here's how this workflow should work for the patients,” and design everything around the patient experience before we even care about what's happening from the scientist researcher perspective. Dr. Suzanne George: I agree. I think to your point, I think the fact that we're all here today talking about this is just like you said, is that we are making progress, right? Like we're even here having this conversation. Just like you said, I think there's opportunities to improve and further refine the communication and the involvement back in the patient community. When I think- if I put on my clinical investigator hat, I'm very involved in PE-CGS, but my primary research interest historically has been clinical trials and drug development. And I think that our approach in communicating results back has just not been consistent. But I do think that there's opportunities, just like you said, to provide summaries of information to loop back. I don't think that we've completely solved: What do we do? How do we provide information back to loved ones of patients that may no longer be alive that participated? How do we provide information to people who maybe we don't have their contact information? What if we lose track of them? How do we also make sure that we give people the choice to know? Do you want to know about this or would you rather just participate and then give space to that research? Because maybe that's how people's best for them. So I think that you're right, we're making progress, but I think that there's also a lot more that we can do. So I'm glad we're talking about it. Dr. Davide Soldato: How much do you think that directly involving patients in this process, like asking them directly and co-designing the trial from the very beginning and understanding the level of information? This might also be another question inside of the question. So first, how much co-designing this type of research helps, and then do we also need to further refine at that level of communication, different communication depending on the level of information that different people want to have? Because I think that that's another level of complexity that we need to work towards at a certain point. We need to work on that first level of giving back the information. But then I think that there is also the other point of providing the information and information that should also be probably adapted to the cultural belief of different patients, to the ethnicity or to whatever cultural background or social background or whatever they may place their most interest in. Dr. Suzanne George: So I think that you're 100% right on all of those points. I think those are all topics that need to be considered. We may be able to get to a certain degree of granularity around those communication points, but on the other hand, we also want to be able to communicate broadly and accessibly as possible. One of the interesting things about PE-CGS, as Liz was mentioning, is each of the five centers has a slightly different focus. For example, one of the centers is focused on American Indians and Tribal Nations, and the communication practices coming out of that center are really unique and really very special and something that's been really, I think for me, very fascinating to hear about. Because to your point, like, just the strategy and what's considered appropriate is just different. I think if we hope to build a research world where our research participants and research data come from a broad swath of the population that really represents the population, the only way that we're going to be able to do that is find ways that bring meaning across the population as well. And that may be different based on where people are coming from and where people are at in their own journeys and in their own lives. But it's on us to be open to that and like to hear that, so we can do the right thing. Dr. Davide Soldato: And I think that this is one of the objectives of the PE-CGS, really trying to bring this type of research participation to really diverse and underrepresented populations, not only in terms of cultural background, but I also think about different types of tumors. Like Liz was referring about brain cancer or low grade glioma, which is a very niche population. And I also think about sarcomas, for example, the degree of variability that we have in that specific type of disease is such that we really need to probably find different ways to communicate also inside of this diversity in terms of single patient and experiences, but also in terms of single diseases. You were speaking a little bit before about the fact that the manuscript is really on the barriers that we would need to identify and then to change to make this system a reality. We were talking a little bit about consenting information and consenting the sharing of information, and I think that you make a very interesting point about the consent process when we are designing research. Could you give a little bit of your impressions about giving informed consent? What we need to change, how can we improve? Dr. Suzanne George: The bottom line is the consent process needs to be simple, clear, and transparent. And sometimes I feel, because the traditional way that we've always gone about consent is frequently consent is as it should be in many ways. These consent forms are developed from a regulatory framework. What are we required to do to consent and how do we meet those requirements? Sometimes that becomes directly at odds with how do we do this simply, clearly and transparently? And I think as a research community, we have to be able to find a common ground there. That has to include regulatory requirements, that has to include IRBs. When we think about consents and work with our patient communities on this, everybody agrees the consents need to be more simple, except the IRB or maybe the IRB agrees, but it's this tension between how do we make it simple, clear and transparent and not get so bogged down in the regulatory that we lose that intent. Liz Salmi: It's complicated. As a person, I mentioned, I'm a chronic research participant living with a brain tumor for 17 years. I remember enrolling in studies and seeing things that are just so complicated. I'm like, “Well, I'm just going to sign off.” I imagine somewhere somebody who knew more than me said, “I should just fill out this thing.” And then as I switched to the research world, I spent more time digging into, “Wow, this is a really complicated consent,” versus, “This is a really streamlined consent and I love this.” And throughout my work with Dr. George and others on the PE-CGS network, an example of a good consent that's easy for people to understand is what the NIH All Of Us research project did, where they're trying to get a million people, more than that, signed up to be in this longitudinal study. And their consent is to go to their website and they have a whole bunch of short YouTube videos. There's a kind of like a quiz involved and they're animated, they have multiple languages involved. And I signed up for that study and I was like, “This is a beautiful consent.” And it's a very plain language. And more consents like that. If you're looking for a good example, go there. I have not been paid by them in any way. I'm a participant in their study. I'm not sure if you guys and your listeners are aware, but there was I think, October 19th of this year or 2024, there was a special communication published in JAMA on an update on the Helsinki Principles for Medical Research involving human participants. And what they're saying is an ethical update is patient engagement in research, which emphasizes the need for continuous, meaningful engagement with research participants and their communities throughout the research life cycle, before, during and after studies. And so this is what we're talking about here. And it's now been embedded in these updated principles. Dr. Suzanne George: That's really great and I agree with you. I think the All Of Us consent process is very accessible. It feels like you can understand it. But the other thing is that, again, I also am not directly involved with All Of Us, but the other thing about it is that they also have a high-touch way to consent where they have navigators and people that will go into communities in a very resource intensive way. So there's all different ways to go about it. We need to find a way that we can balance the complexity around regulatory and the simplicity and transparency that we need in cancer research. Dr. Davide Soldato: Do you think that in terms of patient engagement we are doing better in academic sponsored research compared to sponsored research? A little bit of a provocative question maybe. Dr. Suzanne George: I think that's a really interesting question. I think this idea of participant engagement and involvement is being infused across the research community. And in part, the FDA has prioritized it as well. I think the industry sees the FDA prioritizing this as well. And I think that there are many companies that are involving participant and advocacy communities in different ways in the study design, in the study process early on. So I think it's happening. Liz Salmi: I'll be spicy. I've been a participant, I've been an investigator, co-investigator on studies and I have been reached out to often by pharma of, “Hey Liz, brain tumor patient advocate, would you be kind of like the poster child of our study or be involved in that way?” And I personally want to have no work in that space. I have no interest. However, I am approached, and other people living with cancer have been approached, by industry about lending their likeness or being commercials. And I don't think there's enough education to patient advocates of what that necessarily means, pros and cons. But I also can't speak on behalf of all of the patient advocates who might want to see that's a way that they could lend their voice and advance research. I personally think that there needs to be more involvement from the academic side of creating spaces where patients can be involved in the co-design of research and they also get compensated for their time fairly at the same level or some version of it in a way so they don't just jump to the pharma side of things. But that's an opinion that I have. Opinions. Dr. Suzanne George: I think it's really interesting the point that you make about providing more awareness or information about what it even means to do these things from a patient side. I certainly don't know that side as well, but I do see, often, the term patient advocate used very frequently in many different contexts that mean many different things. And I think that there's an opportunity there for understanding more about what that really means and what it can mean. Liz Salmi: Yeah. We want to involve patients, we want to do patient engagement. The BMJ or the British Medical Journal, have this new policy in place for patients as reviewers of research. And what I find interesting with the BMJ is they also ask patients to declare their conflicts of interest. So this is kind of a new space. If you're involved in patient research or perhaps working with pharma, patients, if you're involved at that level, should also be declaring their conflicts of interest if they're getting paid by a pharma. Or do I have a conflict now that I'm doing this cool ASCO podcast? Maybe. But do we want to overburden patients with tracking all this information? So it's a new world. The more we have access to information, the more we share information, the more we can read studies and we co-design, there's a new space I think over the next 5 to 10 years where how do we define this in a transparent way. Dr. Suzanne George: Yeah, I think you're right. I know that we're getting long, but I just want to say one other thing about that, which is that you're right. If we're bringing patients in to be partners, then we have to treat each other that way. We have to acknowledge- I think this issue that you raise about compensation and about paying people for their time or acknowledging people for their time, I think that's really important and very under-discussed. Liz and I were at the annual meeting for the PE-CGS and someone was there giving a talk about- this was a guest speaker that was giving a talk about a very large high impact grant and that included a patient advocacy kind of module, let's say. And they put in a specific funding and budget for that component that included compensation for the people- from the people in the advocacy community that were spending their time. And the PI of this project, again, not to get into the details of it, but they were sharing that they got a fair bit of pushback on that. But the PI pushed back and said, “Listen, we're compensating other people for their time. These guys, we want them to be partners, we need to treat them as such.” And I think that also again, kind of we're in a new space, but if we're going to do it right, then we have to acknowledge that we're partners. Dr. Davide Soldato: But I think that maybe an experience like the PE-CGS probably can be also a network for expanding awareness for patient advocates and also for creating sort of a new culture about what does that mean and how can we also improve on that part. Because in the end, if we want to engage, we also need to provide patients with the instruments to engage in a way that we think it's both useful for them, that can make research better, but can also make them at the exact same level as everyone who is participating in that research, which I think it's the bottom line of all the concepts that we are discussing right now. Liz Salmi: Yep. Dr. Suzanne George: Yes, I agree. Dr. Davide Soldato: So I think we have covered a lot of things. Just wanted to make one last reference to a point that Suzanne mentioned earlier, which is the interoperability of systems. And I think that when we come to the cancer genome, that is very important, being able to share information, especially for those diverse and less common cancer types that we were discussing earlier. There is a lot of work in gaining all that information and we need to be able to gather all of that information in the same place to advance research. You were mentioning before that the process is actually very complicated and I was wondering if in the network you are already working on some potential ways to address this type of issue. Dr. Suzanne George: I think our first step is really just calling it out, acknowledging how hard this is and what the barriers are. Oftentimes I think in research, we don't talk enough about what our methodologic barriers are. We talk more about what our results are, but not like how hard it is. But like in our projects, the Count Me In project, my network that I'm involved with, we're doing rare tumors. We can only do the United States and Canada because of privacy issues. And we're doing a completely web based platform. So we have the technology. But the privacy laws are impeding our ability to involve other parts of the world. And even within the United States, it's not as easy as we would like to get records. For example, despite the fact that people are saying, “Yes, use my records.” But then it's like, “Okay. Well, that's not that easy. How are we going to get them?” We had to hire a third party vendor in order to get the records, in order to manage all the different consents and releases that were needed across all these different hospital systems. So I think the first question is just calling it out and then from there working together as a community to try to see what the solutions can be, because we need to come up with those solutions. Liz Salmi: Yeah, we're in the same camp as Dr. George and the fact that of the five partners, we're not associated with one particular institution. So we can reach out around the country and get access to those records. And we need them at multiple points in time, over time and it takes a lot of effort and work. And it's not like you could just, say, call hospital A and they have all the information. It's like all of the calls to all of the other sites. And it's not just from one surgery, it's from two or more surgeries. But also the way that people stay involved, and, by people, I mean patients and family members, there's this promise that at some point you're going to get some sort of information in response. Like, it's the “what's in it for me?” aspect of it. We do interviews with those who've been enrolled in the study, those who could be potential enrollees in the future because they've only had one surgery. And what we're learning overall is there's this altruistic nature that people have of- they want to participate in the research because they're like, “Here's my horrible cancer experience. I know other people are going to go through this as well.” There's this guiding light of “I want to do something, and I'm not going to be the person that creates the cure, discovers the genome or whatever for this particular cancer type. But my little bit of participation in this multiplied by 20, 30, 100, 1000 people, is what is going to lead us to the next phase in development and is going to move the needle for this particular tumor type or other cancer types.” And so what I think the impact in this space and participant engagement isn't just something we figure out, like a little research method and a little finding for one small tumor type, it's like the methods to do that is the big impact. The method around participant engagement can impact even beyond the cancer community. Dr. Davide Soldato: Yeah. As Suzanne was saying, we need to be in a system that really helps us and allows us to do that. So I think that you really have a lot of things to work on inside of the network. Dr. Suzanne George: I think one thing that I would say is I think that this issue of interoperability is acknowledged as a challenge. We refer to several different initiatives across the US where this is supposed to ideally change over time. I think people want it to change over time. I think investigators at the ERTC want it to change over time. I think different countries are working on this. And I think, again, the first step is getting us at the table talking about it, and then figuring out ways to move it forward. And I think it's there. I think that there is the will. We just have to figure out the how and continue to work on that together, because there's just a tremendous opportunity. I live in the rare tumor space, and between the FDA and the EMA and the regulatory, the national and the international research groups, the patient communities, people want this to be solved and I do hope that we will be able to get there. Dr. Davide Soldato: So I would like to thank Liz and Suzanne for joining us today. Dr. Suzanne George: Thanks for having us. Liz Salmi: Thank you. Dr. Davide Soldato: Suzanne, Liz, we appreciate you sharing more on your JCO article titled, “Overcoming Systemic Barriers to Make Patient-Partnered Research a Reality.” If you enjoy our show, please leave us a rating and a review and be sure to come back for another episode. You can find all ASCO shows at asco.org/podcasts.   The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.     DISCLOSURES Liz Salmi Speaking Honoria: Medscape. Research Funding (Inst): Abridge AI, Inc., Yosemite. Dr. Suzanne George Honoraria CStone Pharmaceuticals Consulting or Advisory Role Blueprint Medicines, deciphera, Bayer,  Lilly, UpToDate, Research to Practice, MORE Health, Daiichi, Kayothera, Immunicum, BioAtla   Research Funding Blueprint Medicines, Deciphera, Daiichi Sankyo RD Novare, Merck, Eisai, SpringWorks Therapeutics, TRACON Pharma, Theseus Pharmaceuticals, BioAtla, IDRx, NewBay Pharma, Acrivon Therapeutics   Patents, Royalties, Other Intellectual Property Company name: UptoDate Stock and Other Ownership Interests Abbott Laboratories and Pfizer Recipient: An Immediate Family Member

In this JCO Article Insights episode, Rohit Singh provides a summary on "First-Line Nivolumab Plus Relatlimab Versus Nivolumab Plus Ipilimumab in Advanced Melanoma: An Indirect Treatment Comparison Using RELATIVITY-047 and CheckMate 067 Trial Data", by Long et al, published in the November issue of the Journal of Clinical Oncology. The article provides insights into the use of the two dual immune checkpoint inhibitor regimens in patients with untreated advanced melanoma. TRANSCRIPT Rohit Singh: Hello and welcome to JCO Article Insights. I'm your host Rohit Singh, Assistant Professor at the University of Vermont Cancer Center and today we'll be discussing the article “First-Line Nivolumab Plus Relatlimab Versus Nivolumab Plus Ipilimumab in Advanced Melanoma: An Indirect Treatment Comparison Using RELATIVITY-047 and CheckMate 067 Trials,” authored by Dr. Georgina Long from the Melanoma Institute of Australia and her colleagues.  So as we know, nivolumab plus relatlimab and nivo plus ipi, I'm going to refer to as ipi-nivo moving forward, are dual immune checkpoint inhibitors regimens that are approved for treating patients with advanced melanoma based on the phase 2 and 3 RELATIVITY-047 and phase 3 CheckMate 067 trials respectively. Nivo plus relatlimab is the only dual PD-1 and LAG-3 inhibitor regimen approved for treating patients with advanced melanoma and relatlimab is the first in class human IgG4 LAG-3 blocking antibody. Ipi plus nivo is a dual PD-1 and CTLA-4 inhibitor regimen.  So this paper basically is an indirect treatment comparison using a patient level database from these trials and this pretty much was conducted because of the absence of head to head trials looking at different regimens in advanced melanoma in first line setting. In this trial, the authors tried to compare these two trials. However, it's always hard to compare two different trials and we usually don't do cross trial comparisons. The problem is that the groups might be different to begin with. For example, one group might have younger patients, healthier patients, while the other might have older or sicker. These differences can make it hard to tell if the treatment caused improvement or if the groups were different to begin with. In this trial, researchers use inverse probability of treatment weighting to adjust the baseline differences between the two patient groups or between these two trials. Inverse probability of treatment weighting is a method used in research to help make a fair comparison between two groups when studying how a treatment intervention works. Basically, IPTW helps level the playing field between the two groups or like two trials for this paper. So, it calculates the likelihood of receiving a treatment. For each person, for each patient, researchers estimate the chance they would have gotten the treatment based on their characteristics like age, health, condition, their baseline staging, and based on that they create weights. People who are less likely to get the treatment but did are given more weight, and those who are very likely to get the treatment are given less weight. The same is done for the group that didn't get the treatment, and then they rebalance the groups. By applying these weights the group becomes more similar in their characteristics as if everyone had an equal chance of getting the treatment. This way, IPTW helps researchers focus on the effect of treatment itself and other differences between the groups. It's like adjusting the scales to make sure you are comparing apples to apples.  The key outcomes the authors are looking at in this one was progression free survivals, overall survival, confirmed objective response rate, melanoma specific survival, and treatment related adverse events. Looking at the results of this cross comparison trial, first looking at the PFS or progression free survival, both regimens ipi plus nivo and nivo plus relatlimab, showed similar PFS. At 36 months, PFS was 36% in nivo-relatlimab versus 39% in the ipi-nivo regimen with a hazard ratio of 1.08 indicating no significant differences. Looking at the overall survival at 36 months, overall survival was 57% in both the treatment regimens with a hazard ratio of 0.14, again, indicating no significant differences. Now looking at another confirmed objective response rate, confirmed objective rates were similar between both treatment regimens after weighting, 48% versus 50% with an odds ratio of 0.91 suggesting comparable response rates between the two regimens. Looking at melanoma specific survival at 36 months it was 65% versus 62%. Both treatments had similar melanoma specific survival with a hazard ratio 0.86.  An interesting thing in these results was subgroup analysis. Subgroups showed larger numerical differences in efficacy which favored ipi-nivo over nivo-relatlimab that included acral melanoma with a hazard ratio of 1.42 and OS with a hazard ratio of 1.72 in favor of ipi-nivo. Similarly for BRAF mutant melanoma, it showed a confirmed objective response rate with odds ratio 1.54 and same applied to mucosal melanoma with odds ratio of 1.59 and patients who have high LDH more than two times upper level limit. Looking at the safety and adverse side effects, nivolumab plus relatlimab had fewer grade 3 or 4 treatment related adverse effect which is 23% versus 61% and fewer any grade treatment related adverse events leading to discontinuation which was 17% versus 41%, which means 41% of the patients in the ipi-nivo arm lead to discontinuation. However, I would like to add to that that ipi-nivo was conducted much earlier and at that time we were still kind of assessing and trying to understand the immunity adverse effects, how to manage them, which probably could have made discontinuation more common compared to a nivo-relatlimab trial. By that time we definitely had much more experience dealing with immunity adverse effects.A couple of things mentionable in this, notable rates of hepatic and GI grade 3 or 4 treatment adverse events were lower in nivo plus relatlimab than with ipi-nivo, although the onset of any grade endocrine GI hepatic or skin related treatment related adverse events occurred most frequently in both treatment arms and in less than three months from randomization.  So looking at all this data and looking at all this, it definitely seems like both the trials are very comparable in terms of efficacy, though nivo plus relatlimab seems to have a better safety profile. This trial does have some strengths. It does use the patient level data from two large well conducted trials allowing for a robust comparison and inverse weighting which would definitely better help balance baseline characteristics, enhancing the reliability of the results, and it does lead to comprehensive assessment of both efficacy and safety outcomes, and provides a holistic view of the treatments. Given all this, definitely the fact that it's a cross comparison trial which leads to a big limitation, as I already mentioned, like definitely two trials, it's hard to compare two trials which can have its own inherited biases. So it has some differences in trial design, conduct and follow up times. Small size subgroup analysis definitely limits the ability to draw definite conclusions from those groups. There's definitely some inherent uncertainty with direct head to head cross comparison trials.  Looking at the future direction I would take from this trial, if we can have a direct head to head trial because both of the treatments are proven first line setting, it will be comparing these two regimen that can definitely provide more definite evidence and further research is needed to explore the efficacy of these regimens in specific subgroups. As I mentioned in this, some subgroups showed increased benefit in the ipi-nivo regimen, however, they were very small sample size so we need more research exploring those subgroups. One other part in both these trials, patients with active brain mets were excluded. However, there's a phase 2 trial looking at ipi-nivo in active brain mets patients. So I think assessing patients with active brain mets moving forward is also a crucial part looking at, because often, patients with advanced melanoma develop brain mets. It does lead to some unanswered questions like long term survival and quality of life. How do these regimens compare in terms of long term survival and quality of life? While the study provides data on PFS and OS, long term survival and quality of life metrics are essential for understanding the full impact of these treatments. Optimal sequencing strategies: what are the optimal sequence strategies for these patients who progress on one regimen? There is data suggesting that patients may respond to alternative regimens after progression, but more research is needed to establish the best treatment sequence. And real world performance: how do these treatments perform in real world settings outside of clinical trials? Real world data can provide insight into the effectiveness and safety of these regimens in a broader patient population.  So, in summary, nivo plus relatlimab offers similar efficacy to nivolumab plus ipilimumab but a significantly improved safety profile, making it the potentially preferable option for patients with untreated advanced melanoma. However, results should be interpreted with caution due to limitations of cross trial analysis for certain subgroups like acral melanoma, mucosal melanoma, BRAF mutant melanoma, and patients with high LDH more than two times off upper normal limit. The trial showed that there's a trend definitely with ipi-nivo may be more beneficial. Also, today data on the use of nivolumab plus relatlimab in active brain mets has not been reported. Based on these existing data, ipi-nivo remains a standard immunotherapy for patients with active brain mets. Further research, including direct head to head trials is needed to confirm these findings and explore optimal treatment strategies.  Thank you for tuning into today's episode. We hope this detailed summary of the study comparing Nivolumab Plus Relatlimab and Nivolumab Plus Ipilimumab in advanced melanoma has been informative. This is Rohit Singh. Thank you again for listening to JCO Article Insights. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.  

Host Dr. Davide Soldato and Dr. Aaron Mitchell discuss the JCO article "Quality of Treatment Selection for Medicare Beneficiaries With Cancer" TRANSCRIPT Dr. Davide Soldato: Hello and welcome to JCO After Hours, the podcast where we sit down with authors from some of the latest articles published in the Journal of Clinical Oncology. I am your host, Dr. Davide Soldato, medical oncologist at Hospital San Martino in Genoa, Italy. Today, we are joined by JCO author Dr. Aaron Mitchell. Dr. Mitchell is a medical oncologist working at Memorial Sloan Kettering Cancer Center where he is also part of the Department of Epidemiology and Biostatistics. Dr. Mitchell specializes in treating genitourinary malignancy and has a research focus on improving how the healthcare system helps people with these and other cancers. So today, Dr. Mitchell will be discussing the article titled, “Quality of Treatment Selection for Medicare Beneficiaries with Cancer.” Thank you for speaking with us, Dr. Mitchell. Dr. Aaron Mitchell: Well, thank you for inviting me. I'm very glad to be here. Dr. Davide Soldato: So I just wanted to introduce the topic by asking a couple of questions, very general, about the background of the article. So basically you reported the data using the SEER-Medicare to assist to assess the determinants of optimal systemic therapies delivery and selection. So, in particular, you focused on individuals that were diagnosed with cancer who were Medicare beneficiaries and in particular were part of the low income subsidy, which is also known as LIS. So I just wanted to ask you if you could briefly explain to our listeners how this program works, and what was the rationale of the study, and if there is any element of novelty in your study compared to what was done before the study was published. Dr. Aaron Mitchell: Yeah. So that's a lot to cover, but yeah, a lot of opportunity to introduce the low income subsidy program which is a very important part of the Medicare program for prescription drugs, but often one that flies under the radar a little bit in the policy discussion. So this subsidy was created synchronously back with the Medicare Part D Program, which was created in 2006. There was some anticipation that for some high cost drugs, not all patients would be able to afford them even with the Part D program insurance as it was being created. And so they created a pathway to give an additional subsidy to some patients who had low income, who were anticipated to being at need and needing that assistance to afford high cost drugs. As the number of high cost drugs has really risen since 2006, this program has played an important role in helping patients afford drugs, especially those who need very expensive cancer drugs.  And what this program does is, once you meet the eligibility requirements, which require patients to have both quite a low income. So if you're single, that is at 135% of the federal poverty limit or below, and it also places some restrictions on assets. You also have to have low assets, so low income and low assets in order to qualify for the subsidy. But then once you do, the subsidy is really quite large. Patients who qualify for the LIS at the full subsidy level will pay about $10 per month per drug, even for specialty cancer drugs. So if you think about drugs such as those that we use to treat prostate cancer, my specialty, drugs like enzalutamide or XTANDI that run $15,000 to $20,000 per month, the out of pocket cost for a low income subsidy beneficiary is $10. So that is a huge discount. $10 isn't nothing, but even for someone with a low income, if they've got one or two cancer drugs that are at this rate, it's something that they can often afford.  This program applies to Part D cancer drugs that are prescription drugs basically. By and large, these are oral pills that patients are taking on a daily basis at home. These are the drugs that the low income subsidy program applies to. So if a patient needs a drug like that to treat their cancer, then they are able to receive it at very low cost. And what you'll see is a patient- in the studies that have been done, when a patient has low income, low enough for them to be able to qualify for this program, they then have better access to these drugs. You see increased adherence rates, you see increased prescription fill rates. And then when someone, when their income is just high enough to no longer qualify for this program, and they go back to regular Medicare Part D coverage, that's when the problems arise. So it's like as your income moves up the scale, you actually get more problems affording your cancer drugs. So that's the state of the literature so far.  And what we realize though, is that all these studies that have looked at the low income subsidy have really focused on just the Part D drugs themselves, the oral drugs. And that's certainly not all of cancer care. There is a growing number of oral drugs, but for many cancers, especially when you're talking about immunotherapy drugs or new systemic radioligand therapies, these are not Part D drugs, these are Part B drugs. And so even if you are low income and you're qualifying for this subsidy, it's not going to help you if you need a Part B drug. Yes, there are certainly a whole host of other programs and different avenues that we can get patients assistance, but some percentage of them, even though they're low income and high need, would not have assistance with a Part B drug.  So now, in coming back, the long answer to your question, our rationale was, let's look at these Part D low income subsidy patients and let's see what their access looks like, not just to the oral drugs, but to cancer care writ large. And can we study where they're fitting into the system, not only when they need oral drugs, but when they need any kind of cancer care across the board? Dr. Davide Soldato: So basically, just to summarize, it was an extension of previous literature, but specifically evaluating whether novel regimens that use, for example intravenous drugs, they were covered at the same level and whether there were any inequities in access to cancer treatment under this specific program, which is the LIS. Dr. Aaron Mitchell: Yes, I'd say that's a fair summary. Dr. Davide Soldato: Okay. So more or less, you included 9,000 patients inside of the study and 25% of them were beneficiaries of the LIS program. And you specifically looked at factors that could be associated with not receiving therapies at all, and also whether the quality of care that these patients were receiving were any different compared to those who were not part of the LIS program. So I just wanted to see if you could guide us a little bit in the results, whether you see any kind of differences when we look at access to any type of systemic therapies and whether being a part of the LIS program modified access to the drugs. Dr. Aaron Mitchell: Let me take this opportunity also to highlight a feature of our study that differentiates us a little bit from previous work that's been done. And this is around the specific definition of quality that we use. I know quality is in the title of the manuscript, but I think it's important to emphasize exactly what we mean in this study when we say quality, and it's something very specific. So our measure of quality references back to the NCCN guidelines, which I don't think our audience needs much of an introduction to that. It's the most worldwide recognized standard of care guidelines for oncology practice. And we specifically looked not only at the NCCN guidelines, but at their evidence block scoring system. So what we did was we looked not only at one set of guidelines, but we looked at guidelines across time. We looked at guidelines across our full study period, which was, give or take, 2015-2018, depending on the cancer. And we looked at each point in time to see what was the treatment regimen that was recommended by the NCCN guidelines as being preferred. Some of them make that designation, some of them don't. If there was not a designation of preferred, then we turned to the evidence blocks. And the evidence blocks, we then apply several different measures to kind of rank treatments from those that get high scores for efficacy and safety to those that get low scores for efficacy, safety and the quality of evidence. So we basically come up with a kind of a rank list of the recommended treatments at each point in time. And then we look at the ones that are the highest, we say which are the most highly recommended treatments at any given point in time. That then becomes our definition of quality treatment. And I'm saying this with air quotes, we use the term “optimal treatment” in the study. Did they get that treatment? If there were ties, you could have gotten either of the two treatments that got the equally good score, did you get that treatment versus did you get anything else?  So then getting back to our analysis, what we really did was kind of a two-stage study. First, we put all of our patients into our pool, into one big analytic model. And we looked to see what are the factors that predict or are associated with a patient either getting no systemic therapy or any systemic therapy. And then as a second question, we look at the patients who got some form of systemic therapy, and then we ask, again, what percentage of those got the optimal treatment or high quality treatment as opposed to one of the more lowly recommended treatment regimens? So that's how we asked it. We found that patients who were low income subsidy recipients, the low income ones, they were both less likely to receive any systemic therapy. And then even the ones that receive systemic therapy, the ones who made it in the door to see their doctor or their part of the system, they still were less likely to get the optimal treatment that was recommended for their cancer type at the time that they were diagnosed. Dr. Davide Soldato: So basically, even when you are a part of this subsidiary program, you still have a lower access to any type of treatment. And even if you get treatment, you kind of get the ones that were not the preferred according to the NCCN guidelines, or at least they were not scoring as well as those specific regimens. But I think that what our audience might be wondering about is that frequently there are also some other types of characteristics, for example, age or number of comorbidities, which can be associated with having a low socioeconomic status. So I was wondering whether in the analysis you kind of looked specifically also at patient factors, for example, income rather than age or comorbidities, and whether you found any significant association with those and whether it was something that you planned to do in your study. Dr. Aaron Mitchell: Yes. So we looked at many patient factors and those included age and they included the degree of comorbidity. And what we saw with respect to those characteristics was not too surprising. We saw that patients who were older were less likely to receive systemic therapy. We saw that patients who had more comorbidities were also less likely to get systemic therapy. And then across our different designations of treatments, we saw that those patients were also less likely to get the optimal treatment for their cancer. This result though, we would say it certainly needs more study in the future, but it's not immediately concerning. And that is because for patients who have more age, more comorbidity, those often correlate with frailty. And so it could be that these patients aren't getting optimally treated or it could be that their oncologists are just making clinically appropriate decisions about patient selection.  We saw as we were doing this work that the treatment regimens that are often getting the highest recommendations from the NCCN, hence, it would become our definition of high quality optimal treatment, are often ones that are aggressive. They're often ones that are multi-drug combinations. They're often ones that it's not just your old antineoplastics, it's the antineoplastics plus an additional immunotherapy or plus a targeted drug. So it's the ones that are more aggressive by and large, and that might be in some cases more than a patient who is older, more frail, could be able to tolerate. And so the oncologist might be making inappropriate judgment to say I'm going to do something a little bit less aggressive here and make an appropriate trade off between anti cancer efficacy and safety.  I think we've got kind of a bookmark there and we can look at those trends in the future. So we saw that kind of as expected, and then we turned and looked towards the low income subsidy. And our premise there is, well, your income shouldn't predict what you're getting clinically. In an ideal world, you'd be able to get the appropriate treatment for a patient, and not depend on whether their income is above or below 135% of the poverty limit. So that one seems more like on its face an immediate concern. Dr. Davide Soldato: Thank you very much for the explanation. I was just wondering, did you make some kind of selection when you were analyzing specific diseases or settings where you included just metastatic patients or you also included patients with early stage neoadjuvant treatments? Because I think that it is also very interesting from the perspective of the objectives that we have as oncologists when we are administering systemic treatments. Dr. Aaron Mitchell: Yeah, thank you for bringing that up. That was also one of the goals of our study was to be broad. And we wanted to look for factors, whether it be low income subsidy, whether it be age, socioeconomic background, etc., things that would be broad predictors of outcomes, and by which I mean care delivery outcomes across the board. So not just for, let's say, metastatic breast cancer, but also across any cancer that a patient might walk in the door with, what are the systemic predictors. And so when you mentioned before that our overall cohort is approximately 9,000 patients, that's 9,000 patients split over a variety of what we call clinical scenarios or clinical indications. And that includes multiple solid tumor as well as liquid tumor malignancies. It includes both patients who are initiating systemic therapy with palliative intent for metastatic disease. It also includes several groups of patients who are getting adjuvant therapy. So we want it to be as broad as possible. Our selection of those scenarios was really done with the goal of being as broad as possible and really bringing in everything that we could within the constraints of our data source. And that was really the only limitation that we applied in concept was tumor types that are common enough to have a meaningful sample of patients to analyze. So, one, are there enough patients? And then two, are you able to identify this specific group of patients within SEER-Medicare data? Because when the NCCN divides groups of patients by biomarkers that are not available in SEER-Medicare, we can't really say, “Oh, we're going to study this group of patients.” That would then be one that we have to leave on the side and not include. But everything else where one of those things didn't apply, we tried to include it as best we could. Dr. Davide Soldato: Thank you very much for the explanation. And among the scenarios that you included in the study, were there any striking differences in terms of access to treatment and access to quality treatment the way you define the study? Dr. Aaron Mitchell: Yes, there were differences between these different cancer types, these different cancer indications, but they're not differences that I want to over interpret or read too much into. Certainly, every cancer indication is going to be different, but when we start getting into the individual cancer types, the sample size does get smaller. And we've not done formal tests of comparison or heterogeneity among cancer types. So I don't want to say that the differences which we certainly do see, like numerically, there are differences in the proportion of patients who are getting optimal treatment versus no treatment. I don't want to say that it's because the low income subsidy status or patient age has a bigger impact, let's say for lung cancer than breast cancer. I want to say that is heterogeneity for potential future study when we are able to do a similar follow up analysis with say a larger sample size. I don't want to over interpret those differences at the moment. Dr. Davide Soldato: I was just wondering in case there was anything in particular that you wanted to highlight. But in the end, I think that we also have to acknowledge that the data are based on claims data, observational data. So maybe you're right when you say we should not over interpret this type of difference.  And this is just to speculate a little bit, do you think that if you would look at this same specific question in a more contemporary diagnosis frame, like for example, you refer to the fact that most of the diagnoses were between 2016 and 2018. Now that we have more and more of these drugs that would qualify as Part B in the adjuvant or new adjuvant setting, do you think that you would see more differences compared to what you observed in the current study or do you think that it would be more or less the same? Of course this was not part of the analysis that you did, but it's just to have your opinion on the topic in general. Dr. Aaron Mitchell: My expectation would be that since not much has changed with respect to the low income subsidy program from the time period of our study until now, my baseline expectation would be that those results would hold. On the other hand, it is the case that there have been improvements to the standard Medicare Part D benefit since the time of our study. So the low income subsidy patients would be paying the same low out of pocket costs that I mentioned before, about $10 a month give or take, for a specialty cancer drug. But what has started to happen is that for everyone else, their coverage has improved. Because in the US we're in the process of closing, or I think now we finally finished, but you know, a few years lag in claims data, we've closed what used to be called the donut hole, where there was this big coverage gap where patients had to pay a large amount out of pocket for drugs. So there might therefore be a narrowing of the difference, let's say between our low income subsidy participants, the lowest income patients, and then everyone else. But not so much because the low income subsidy status improved or changed, but just because the baseline level of coverage for everyone else may have improved, narrowing that gap. So I'd say that would be very possible.  And if your question is more geared towards not so much policy changes, but treatment landscape changes, I would say the big thing that I would maybe guess, and again, this is very much speculation, but you introduce the speculation in TBD on follow up. I think the big change in the landscape has been the broadening indication and uptake of immunotherapy drugs, our PD-1, PD-L1 inhibitors, for a variety of cancer types. And I think the way that that would manifest in our data, were we to repeat it in a more contemporary data set, would be, I think that the access for, let's say, that any systemic therapy among older patients might change. And that is because rather than just having your cytotoxics in hand, the clinical oncologists now know that for many cases there's if not first line therapy, then second line therapy for patients who don't qualify, you can go straight to it, to someone who's not a chemo candidate, you've got a much more tolerable treatment in your back pocket. And so I think that for patients who are more old or more comorbid, we might start to see that a greater proportion of them receive some systemic therapy, it just might not be the cytotoxic agent that is still most highly recommended. It might be, say a single agent, PD-L1 inhibitor, because their oncologist wants to be able to give them something. So I wouldn't be surprised if that gap starts to narrow as well if you're measuring no systemic therapy versus any systemic therapy. Dr. Davide Soldato: And going back to the policy part of the study that you did, do you think that the results of the study that you published in the JCO can better inform policy makers on how to make these treatments more available and be sure that the largest possible proportion of patients gets a systemic treatment and gets the optimal systemic treatment? Dr. Aaron Mitchell: Yes, I do think that this study has some direct and indirect policy implications. I think that our finding is one to highlight the low income subsidy program and maybe help it not to fly under the radar so much anymore. I think all the work that has been done on how much it has helped patients who need oral cancer medications is great, and it shows how beneficial this program can be. We're now shining the light kind of everywhere else and saying, “Okay. That's great. Here's how well it can work when it covers an oral drug, but we've got this group of low income patients who are still at need and they're still very clearly not able to access everything else. When it's not axitinib that they need, it's a pembrolizumab, they're still very much behind the curve and they need some help.” So I think that's one thing just to call attention to this as an ongoing problem. Low income patients, it's not a solved problem yet. It's something that needs further attention.  And then for direct policy implications that are on the table, I think we're about to see the Medicare program be able to start negotiating not just Part D drugs, but also in future years, Part B covered drugs and try to lower the price for everyone, both for insurance, both for Medicare itself. And then to the extent that that boils over to the patient's out of pocket responsibility, it'll start to reduce the patient out of pocket costs as well. So I think we can look forward to hopefully an aggressive negotiation program by Medicare to start to directly lower the prices of Part B cancer drugs that these patients are unable to afford. Dr. Davide Soldato: Thank you very much. You did the research you published in the JCO, but you really seem very passionate about the topic of care delivery and quality of care and policy. So I just wanted to ask on a personal note, how did you come to this area of research which is frequently not one that is very cared for by oncologists? It's more frequently something that biostatisticians or public health scientists put their attention to. I just had this curiosity and I wanted to ask you if you could explain a little bit how you came to this area of research. Dr. Aaron Mitchell: Thank you for asking. That's a great question. I'll tell my favorite story about my journey there. I entered medical school planning to be a clinical investigator or maybe even a basic science researcher, and I had some background in that. I went to medical school at NYU where the teaching hospital is Bellevue, which is a large, well known public hospital within New York City. And my eyes started to open regarding the inequities in the system. You always hear about it, you read about the problems in the US healthcare system, but then when you see it on a day to day basis and you can walk four blocks from a private, very well resourced hospital to see a patient with a similar condition four blocks down the road at a under resourced public hospital getting very different treatments and receiving very different outcomes, the injustice in the system really hits you on a visceral level. And it was really, I would say, as soon as I started my clinical rotations in medical school that I realized maybe that's where I can make the most impact with my career and just really fell into it. By the time I was done with medical school, I then knew that I wanted to do something that was in the health policy space. And then by the time I was done with residency, I was like, “Oh, someone had mentioned the words health services research” and the light went on. It's like, “Oh, that's me. That's what I want to do.” Dr. Davide Soldato: Thank you very much. That was a nice story. And I really think that we should all work towards trying to make sure that the inequities inside of the system are eliminated as much as possible.  So I think that this concludes our interview for today. So thank you again, Dr. Mitchell, for joining us. Dr. Aaron Mitchell: You're very welcome and thank you so much for your interest. Dr. Davide Soldato: We appreciate you sharing more on your JCO article titled, “Quality of Treatment Selection for Medicare Beneficiaries with Cancer.”  If you enjoy our show, please leave us a rating and review and be sure to come back for another episode. You can find all ASCO shows at asco.org/podcasts.   The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  Guests on this podcast express their own opinion, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.

In this JCO Article Insights episode, Alexandra Rojek provides a summary on "Post-Transplant Cyclophosphamide–Based Graft-Versus-Host Disease Prophylaxis Attenuates Disparity in Outcomes Between Use of Matched or Mismatched Unrelated Donors" by Schaffer et al published in the Journal of Clinical Oncology July 17th, 2024. TRANSCRIPT Alexandra Rojek: Hello and welcome to JCO Article Insights. I'm your host, Alexandra Rojek, and today we will be discussing an original report published in the October 1st issue of JCO titled, “Post-Transplant Cyclophosphamide–Based Graft-Versus-Host Disease Prophylaxis Attenuates Disparity in Outcomes Between Use of Matched or Mismatched Unrelated Donors,” by Shaffer et al. The CIBMTR registry study set out to compare outcomes of patients undergoing allogeneic stem cell transplantation hematologic malignancies by HLA antigen matching status as well as by the type of GVHD prophylaxis regimen received either calcineurin inhibitor-based prophylaxis or post-transplant cyclophosphamide or PTCy. This study included patients reported to CIBMTR from January 2017 to June 2021 with AML, ALL or MDS, and required that they have undergone allotransplant with either a calcineurin inhibitor based so tacro or cyclosporine, GVHD prophylaxis, or PTCy, which included a calcineurin inhibitor or sirolimus with or without MMF and ATG. Matched unrelated donors were defined as an 8 out of 8 HLA match. And mismatched unrelated donors were defined as HLA mismatched at any single locus or 7 out of 8. The primary objective of the study aimed to compare overall survival or OS and GVHD and relapse-free survival (GRFS) within and between matched unrelated donors versus mismatched unrelated donors separated by calcineurin inhibitor versus PTCy based GVHD prophylaxis. GRFS was defined as survival without grade 3 to 4 acute GVHD, moderate to severe chronic GVHD requiring systemic therapy or relapse. 10,025 patients were included from 153 centers, with a median follow up of over 36 months. Mismatched unrelated donor recipients were made up of 22% minority ancestry patients as compared to just 8% of patients receiving a matched unrelated donor allo transplant, showing an enrichment for patients of minority ancestry in the mismatched unrelated donor group. Just under 10% of patients were of minority ancestry in the study overall, reflective of challenges in transplant care for these patients, which may include inferior access to care, fewer available and suitably matched donors, among other factors. 54% of all patients were transplanted for AML and 29% for MDS. 45% of patients received myeloablative conditioning, 25% received regimens containing ATG, and 23% overall received PTCy with either a calcineurin inhibitor or sirolimus as well as MMF. Among patients receiving PTCy, the authors did not find differences in overall survival by degree of HLA matching, whereas among patients receiving calcineurin inhibitor-based prophylaxis, there remained survival differences by HLA matching status. When comparing matched unrelated donor calcineurin inhibitor patients with PTCy matched unrelated donor patients, the PTCy arm had better OS, and the mismatched unrelated donor group who received PTCy had similar OS as well. For GRFS, matched unrelated donor and mismatched unrelated donor PTCy patients had no difference in GRFS, similar to the trend the authors see with overall survival. But these patients also had better GRFS than matched unrelated donor patients receiving calcineurin inhibitor-based prophylaxis. Within each prophylaxis arm, there was no difference in GRFS by HLA matching status. HLA mismatched patients receiving PTCy were less likely to experience GRFS than HLA mismatched patients receiving calcineurin inhibitor-based prophylaxis. The authors saw similar differences in comparative trends when subgrouping patients based on conditioning intensity and additionally did not find differences in GRFS and OS by ATG exposure. When looking at patients with minority ancestry, those patients who received a match unrelated donor or mismatched unrelated donor with PTCy had comparable outcomes to non-Hispanic white patients. Additionally, among minority ancestry patients, there was a significant benefit in both GRFS and OS in the PTCy groups as compared to calcineurin inhibitor-based prophylaxis. When examining other specific toxicities included in the composite GRFS endpoint, such as GVHD rates among PTCy patients, the authors note that patients receiving a matched unrelated donor had similar rates of grade 3 to 4 acute GVHD but lower rates of moderate to severe chronic GVHD requiring systemic therapy. There appears to be signal that among PTCy patients, HLA matching reduced rates of moderate to severe chronic GVHD compared to mismatched unrelated donor patients receiving PTCy. These same trends also held when the authors looked at non relapse mortality with no significant differences within the PTCy groups by HLA matching status but reduced non relapse mortality compared to both calcineur and inhibitor-based groups. However, notably, there was a greater risk of relapse among matched unrelated donor PTCy patients than matched unrelated donor calcineurin inhibitor patients, although this risk was comparable between mismatched unrelated donor patients by type of prophylaxis. The authors note that this has also been observed in other retrospective cohorts and may be confounded by differences in conditioning intensity between these cohorts of matched unrelated donor patients, affecting the risk of relapse. Finally, the authors also evaluate whether expansion of donor search criteria to mismatch donors from full HLA matching would increase availability of young donors from minority ancestry patients, and the study noted striking increases for all subgroups examined. This study fits nicely with the BMT CTN 1703 trial published in the recent past, which has showed the superiority of PTCy with the calcineurin inhibitor and MMF when compared with conventional calcineurin inhibitor based immune prophylaxis for reduced intensity matched related donor and matched unrelated donor allotransplant. Of note, very few patients with one HLA antigen mismatch were enrolled on that study. However, others have shown the feasibility of PTCy in the mismatched unrelated donor setting, which has led to its adoption in practice. Although less than a quarter of patients included in this current study received PTCy overall, the findings clearly are aligned with the BMT CTN 1703 study, which is likely to change clinical practice in the longer term in this field. As the accompanying editorial in JCO, written by Dr. Chakravarty nicely lays out, the differences between this study and the EBMT registry study, also published in this issue of JCO are subtle but worthy of note. While both studies show that mismatched unrelated donor patients had worse OS and GRFS than those receiving matched unrelated donor transplants, and then among matched unrelated donor patients the addition of PTCy improved GRFS and OS, there is discordance between the studies whether the addition of PTCy abrogates the effect of HLA mismatching on GRFS and OS. As this editorial points out, there are strikingly different rates of T cell depletion with ATG between the US and Europe, which may account for differences in comparator arms that lead to this discordance. There are several very exciting clinical trials ongoing that will aim to answer some of these outstanding questions regarding comparisons of PTCy and T cell depletion, which the field eagerly looks forward to reviewing. In summary, this registry study of patients receiving allo transplant with matched unrelated donor or mismatched unrelated donor and calcineurin inhibitor or PTCy based GVHD prophylaxis, most notably shows that for patients who may not have a matched unrelated donor available, the addition of PTCy to a mismatched unrelated donor allo transplant allows for improved outcomes after transplant in toxicities and survival. This is most significant for patients of minority ancestries who usually have fewer matched unrelated donors available in registry searches. Improving the transplant options available to these groups of patients is of critical importance in improving equitable access to care for all of our patients. And this study, although retrospective in nature, provides an important understanding of our progress to date and suggests directions for future investigation may indeed be very feasible to continue to close these gaps in care for patients in need of an allo transplant for hematologic malignancies. This is Alexandra Rojek. Thank you for listening to JCO Article Insights. Don't forget to give us a rating or review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts.   The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.