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What Characteristics Are Associated With Resilience to NSCLC Tx in Older Patients?

– Joy Tang, MD, on her research showing that age or performance status are not the best predictors


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Medpage Today

In this exclusive video, Joy Tang, MD, of Ohio State Wexner Medical Center in Columbus, discusses her research into the characteristics associated with functional resilience versus functional decline among adults with advanced non-small cell lung cancer.

The following is a transcript of her remarks:

Hi, my name is Joy Tang. I'm one of the second-year hematology/oncology fellows at the Ohio State University.

My research interest is primarily in geriatric oncology, specifically in lung cancer patients. So my project looks at advanced non-small cell lung cancer patients, and looks at which characteristics can help us predict who will tolerate therapy the best. And so right now, especially with more therapies coming out like targeted therapies and immunotherapy, we really don't have a great way to predict -- especially in older patients -- who will tolerate the therapies really well.

We know that patients who have functional decline over time have worse overall survival, but interestingly, some patients will bounce back and they'll recover their baseline function throughout therapy, and chronological age is actually not a great predictor of this.

So we looked at patients who are getting treated over time, and once a month we would send out surveys and we would look at characteristics and see who would bounce back and try to recover their baseline functional status throughout therapy.

Interestingly, I think in cancer a lot of times one of the best tools we have is using ECOG Performance Status to see who can tolerate treatment the best. We actually found that performance status is not a great predictor of who has resilience and who can bounce back through treatment.

We actually found there's no correlation between functional decline or functional resilience in correlation with ECOG performance status, which is really interesting, because that's one of the biggest tools we use nowadays to assign who will get treated and who won't get treated.

So we looked at a bunch of characteristics like smoking status, living in a metro setting or not, symptom burden, if they had brain meds or bone meds, education level, and income level to kind of see if any of those could help us predict who will tolerate treatment better and who will have resilience throughout treatment.

We found things like living settings, so living in a non-metro setting, and being employed actually seem to be associated with increased resilience throughout treatment, but then interestingly, the ECOG Performance Status was not predictive, and we're using that a lot.

So even in mapping out a survival curve, we're seeing that there's no statistically significant survival in patients who have better performance status and those who don't.

I think we need to do more research to figure out better predictors of who can tolerate treatment better.

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