Pedro Barata: Hi, I'm Pedro Barata. I'm a GU medical oncologist at Tulane Medical School in New Orleans, Louisiana. It's a privilege to have here with me today Dr. David Cella. He's a PhD and Professor and Chair of the Department of Medical Social Sciences at Northwestern University and Feinberg School of Medicine in Chicago. Welcome, Dr. Cella.

David Cella: Thank you, Dr. Barata.

Pedro Barata: So thank you for taking the time to sit down with us and really go over what I think is really important data from CheckMate 214, which of course investigated the role of the combination of ipilimumab and nivolumab compared with sunitinib for patients with advanced renal cell carcinoma, and really what you presented at ASCO 2022 was the health-related quality of life and the association of the quality of life, actually, with clinical outcomes, including progression-free survival and overall survival. To me, this is so important data because this space is getting so crowded, right? That to get that information is really key. So with that said, could you summarize for us what you see being the key main points and highlights from the data you presented in Chicago?

David Cella: Sure. Well, this trial, CheckMate 214, that compared nivolumab/ipilimumab to sunitinib, we already know from previous publications that nivolumab/ipilimumab improved overall survival, as well as progression-free survival, in the later follow-up. So that information's already out there, but we also studied quality of life and had previously reported that the patient's quality of life was better on nivo/ipi as compared to sunitinib, which is actually kind of rare to see in oncology trials, where typically the newer or experimental treatment might tend to have more toxicity in the early going, and actually, if anything, maybe be equivalent quality of life or noninferior quality of life, but rarely better quality of life. And so that was nice to see in this particular trial, but what we presented here at ASCO was advancing this kind of information even further.

We looked at the relationship of this quality of life data collected by the FKSI-19 questionnaire, the relationship of quality of life at baseline and longitudinally to progression-free survival and overall survival. And we found that, in both cases, the baseline report of patients on their symptoms and function was predictive of progression-free survival and overall survival, and in an even more stronger fashion, looking at the hazard ratios, the longitudinal quality of life responses of patients over the first six months of therapy were strongly predictive of progression-free survival and overall survival. So this tells us that these clinical endpoints all work together in the case of nivo/ipi, progression-free survival, overall survival, which are very familiar in oncology, but also the patient's report of symptoms and function.

Pedro Barata: Yeah. Those are fantastic points. There's another way to say that, I guess. So it seems like, at least for patients treated with ipi/nivo, whoever's doing better on the regimen tends to do better overall. And I would I add to the value of your work, is I believe you guys did an analysis of five years of follow-up, correct? So the data is really mature.

David Cella: That's correct. It's a very mature dataset, and this is looking at the long view, and you're absolutely right. The patients that do well in the beginning of therapy, in those first six months, do tend to do better on the clinical measures of progression-free survival and overall survival.

Pedro Barata: Got it. So I guess the next question is how can we use this information? And kind of apply it to the prognostic models out there. Of course, we have many prognostic tools we can use. There's some popular ones, right? The Memorial score, the IMDC score, and so forth. Right now, we take some clinical and laboratory factors. I guess, what are your insights about bringing these kind of patient-reported outcomes, if you will? And can we strengthen those kinds of tools with the incorporation of this data? What are your thoughts about that?

David Cella: I think the prospect of doing that is very positive, very favorable. I would point out that around 20% of patients scored considerably poorly on this questionnaire, this FKSI-19, at baseline that is before starting therapy. So even though these were all performance status 0, 1 patients, about one in five were pretty symptomatic going into treatment. And those are the patients that tended to not do as well, so we may be able to enhance the concept of poor risk, for example, by identifying those patients who come into therapy with symptoms.

Pedro Barata: That's a very, very important point. And I have to say, every time and in this crowded place, as we have more and more efficacy data on different combination regimens, as ipi/nivo is part of and now is standard of care, data like quality of life might do the trick. Actually, my help is to define or decide which one of the combination regimens we want to go with, I guess, but to be transparent to you, I personally feel different every time I look at the efficacy data compared with the quality of life data, I feel far more comfortable discussing and analyzing, if you will, efficacy endpoints, like overall response rate, progression-free survival, overall survival, et cetera, compared with the quality of life/tolerability because they are different instruments, they're collected data at different time points. We're talking about sometimes different mechanisms of action of therapies.

I personally have that, and I believe, in the field, a lot of us have that, I guess, limitation or feel that way, right? They feel less comfortable. I mean, as an expert in the field, and you've done a lot of work and very, very solid work on quality of life, what are your insights and also tips and advice you can share with us to help us a little bit, or at least bring our attention to the things that really matter? If you were to give us some tips on that and thoughts, what would that be?

David Cella: Yeah. Well, first let me say you're not alone. There are many people in your position who are, just frankly, less comfortable with quality of life data as compared to response data or progression-free survival data or overall survival data. These are the familiar endpoints to oncologists. So you're in good company. And I think part of the problem if you will if you call it a problem, of people not understanding the quality of life data is on us, the people that do this research. We've created too many tools, too many different questions. We haven't emphasized the importance of standardizing measurement, at least in a clinical area, and so I think to offer one piece of advice, it would be to stay with something that you know and that you're familiar with. And in the case of kidney cancer, many of these trials that you mentioned at the beginning of your question, use the FKSI questionnaire as an outcome.

So I would encourage people to get familiar with those questions, get familiar with the scores, take some time to understand what's a meaningful difference, or what's a meaningful change in a score, and track your patients on it. It also works question by question. I mean, most of these questions in this 19-item questionnaire are asking about symptoms. The majority of them are asking about pain and fatigue and appetite, et cetera. So I would say look at the individual symptom responses in your patients, see where there may be flags to tune into, but also try to get more familiar with one questionnaire and stay with it.

Pedro Barata: Those are indeed valuable insights. Thank you so much. And that makes a lot of sense. So with that, again, a true pleasure to have you here. Again, congratulations on a great presentation at ASCO, and I'm looking forward to more work from you and your group. And so thank you, thank you once again, and we'll see you soon.

David Cella: Yeah. Thank you very much. A pleasure.