Treatment-Free Survival Can Be a Meaningful Endpoint in Clinical Trials
Researchers and clinicians should consider treatment-free survival when analyzing the results of clinical trials, according to one expert.
Treatment-free survival (TFS) could be a meaningful endpoint for researchers and clinicians alike to consider when analyzing clinical trial data, according to Meredith M. Regan, ScD.
Regan, a researcher at the Dana-Farber Cancer Institute in Boston recently used TFS in her analysis of multiple CheckMate trials, which investigate the efficacy of the immunotherapy agents nivolumab (Opdivo) and ipilimumab (Yervoy) alone, in combination, and compared with standard of care. She sat down with OncLive®, a sister publication of Oncology Nursing News® to discuss TFS.
OncLive®: Can you explain the background on the idea behind using TFS as an endpoint in clinical research?
Regan: Back in the earlier days of immuno-oncology, back to high-dose IL-2 in kidney cancer and melanoma, the treatment period was very brief, and then there was a small proportion of patients who benefited with long, durable complete responses. Then with the newer immuno-oncology agents, immune checkpoint inhibitors, in particular, used in combination, the same thing has been observed.
So this unique pattern is coming back with immuno-oncology and brings up the idea that if patients are able to be treated and therapy stopped, then the treatment-free duration that they have would be a really appropriate endpoint to characterize this unique pattern of response that happens with immuno-oncology agents and not so much with other systemic therapies. That was what got us started down this path of looking at treatment-free survival.
Does TFS provide a more complete picture of patient experience?
The concept is straightforward: it's the period from when the first-line therapy is discontinued until the second-line therapy is started. But what happens is often just the patients who discontinued therapy get summarized, but if the clinician and patient are sitting together at the beginning of therapy and thinking about the path that they want to go on, you want to know about the entire population who stared down this pathway. For example, if you're being treated with nivolumab plus ipilimumab, because if a patient is staying on therapy with continued disease control, that's also a good thing. In a lot of the analyses, that's not there. We want to take a more integrated approach to treatment-free survival and characterizing it in a way that included all of the aspects. Treatment-free survival is one aspect of patients now living longer for advanced kidney cancer, which is great.
How can this information be leveraged to clinical trials of the future?
It's just the principle that now that survival is longer, we can really focus on how that survival time is spent. Treatment-free is one time. We try to integrate it and think about it as the time on, so the first-line therapy or protocol therapy if it's a clinical trial, the time they are able to be treatment-free, and then the time on subsequent therapies. But also, with the good that has come with immune checkpoint inhibitors, there is also some bad. That's also an important part for clinicians and patients to be thinking about: toxicities that happen during treatment, which happens with all systemic therapies. Also, some of those toxicities can persist even after treatment is discontinued. We wanted to be able to bring that into the analyses as well, so you can understand treatment-free survival: how much of it was spent with ongoing side effects and adverse events that had started from therapy and how much was without those events. That's how we tie the whole picture together, and we'll be able to weigh the pros and cons of the different approaches.