In this interview, Renée Saliby, MD, Dana-Farber Cancer Institute, Boston, Massachusetts, provides an overview of her study on whether intermediate endpoints such as time to treatment failure (TTF) and time to next therapy (TTNT) are associated with overall survival in patients with renal cell carcinoma receiving immune checkpoint inhibitor-based treatments. The study results were presented at the 2024 ASCO Genitourinary Cancers Symposium.

Transcript:

Dr Renée Saliby, MD: My name is Renée Saliby and I'm a postdoctoral research fellow here at Dana -Farber Cancer Institute and at the State Cancer Center under Dr Choueiri and Dr Braun's mentorship.

Can you give some background about your study and what prompted you to undertake it?

Dr Saliby: As you may know, the last couple of years have been really instrumental in improving the treatment landscape of metastatic renal cell carcinoma (or RCC) and overall survival has tremendously improved.

However, we know that a subset of patients still doesn't benefit from the contemporary drugs. And so, we still need to do clinical trials and find new drugs that will provide deep and durable response to all patients, hopefully. And with this increasing overall survival (OS) and OS being the primary endpoint at most phase 3 trials, evaluating these new drugs that we would like to come up with have become increasingly difficult. It's now a lengthy process and has enormous costs. So this will delay the approval of new drugs and of course the access of these new drugs.

So, we were interested in looking and evaluating shorter clinical endpoints that we called intermediate endpoints and see how they associate with overall survival or OS.

Can you briefly describe how the study was conducted?

Dr Saliby: So we performed a multicenter, real-world analysis using data from IMDC, which is an international metastatic RCC database consortium, and we included patients who were receiving contemporary approved first-line immune checkpoint inhibitor-based therapies from 2013 to 2023.

And the endpoints we wanted to study, the shorter endpoints, were time to treatment failure (or TTF), time to next therapy (or TTNT), and objective response (or OR). And we defined them as follows: So TTF was defined from the start of the first-line immune checkpoint inhibitor-based therapy until the stop of this therapy or death.

Time to next therapy (or TTNT) was defined from the start of ICI until the initiation of the second line of systemic therapy or death. And objective response was evaluated according to RECIST 1.1 criteria. And we used three approaches to evaluate these endpoints with respect to OS.

So first, we used the Kendall’s Tau Correlation by Clayton Coppula to evaluate the correlation at all time points. Second, we divided the whole population into 10 equal size subcohorts based on the desired group of disease risk score. And that's a bit of a prognosis factor that we studied in order to define these 10 subcohorts.

And for each subcohort, we performed linear regression in order to obtain an R². And that R² is kind of how much the intermediate endpoint can explain the variance of OS. And the third method was to assess hazard ratio using the Cox regression.

What were the main findings of your study?

Dr Saliby: Overall, our study included 1684 patients who received first-line immune checkpoint inhibitor-based therapy, with most patients having clear histology and receiving nivolumab plus ipilimumab, followed by pembrolizumab plus axitinib. And now the interesting results.

So Kendall’s Tau correlation was over 0.49 for our endpoints and this threshold means that this is a strong correlation. So it was exactly 0.49 between TTF and OS and it was 0.67 for TTNT and OS.

So this shows really a strong correlation between the endpoints. And concerning R², we were able to show that 76% of the variation of OS can be explained by TTF. Ninety-one percent of the variation of OS can be explained by TTNT.

So that's really impressive I think for TTNT, honestly. And for 6 months landmark analysis we showed hazard ratios of 2.77 for objective response, 2.74 for time to treatment failure, and 2.82 for time to next therapy, and these results were all consistent across subgroups. And just to visualize that better, so patients who had an objective response had 91% 18-month OS rate vs 74% for patients who did not have an objective response.

And on the other hand, patients who had treatment failure at 6 months, they had an OS rate of 68% versus 92% for those who did not have a treatment failure at 6 months. And finally, for time to next therapy, specific patient transitions to the next therapy. So the OS rate here was 63% at 18 months vs 87% for patients who did not transition to the next line of therapy.

Looking ahead, what potential impact do you hope your findings will have on the standard of care and or treatment for patients with renal cell carcinoma?

Dr Saliby: So our study is hypothesis generating, I think, and it identifies TTNTs for time to next therapy as a potentially meaningful clinical endpoint. However, I think we need much larger cohorts and ideally from clinical trials because these are very standardized and very well evaluated endpoints in order to really have impact for results that will hopefully change the way we do trials.

I think we would be very happy to collaborate with anyone who is interested in order to expand the study and maybe learn from other groups who have been looking at these kinds of analyses. Thank you.